{ "discoveryVersion": "v1", "parameters": { "oauth_token": { "description": "OAuth 2.0 token for the current user.", "location": "query", "type": "string" }, "callback": { "type": "string", "location": "query", "description": "JSONP" }, "upload_protocol": { "type": "string", "description": "Upload protocol for media (e.g. \"raw\", \"multipart\").", "location": "query" }, "quotaUser": { "description": "Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.", "location": "query", "type": "string" }, "fields": { "type": "string", "description": "Selector specifying which fields to include in a partial response.", "location": "query" }, "$.xgafv": { "description": "V1 error format.", "enum": [ "1", "2" ], "location": "query", "type": "string", "enumDescriptions": [ "v1 error format", "v2 error format" ] }, "prettyPrint": { "location": "query", "description": "Returns response with indentations and line breaks.", "default": "true", "type": "boolean" }, "key": { "type": "string", "location": "query", "description": "API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token." }, "uploadType": { "location": "query", "description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\").", "type": "string" }, "access_token": { "type": "string", "description": "OAuth access token.", "location": "query" }, "alt": { "enum": [ "json", "media", "proto" ], "location": "query", "description": "Data format for response.", "type": "string", "enumDescriptions": [ "Responses with Content-Type of application/json", "Media download with context-dependent Content-Type", "Responses with Content-Type of application/x-protobuf" ], "default": "json" } }, "title": "Vertex AI API", "schemas": { "GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfig": { "id": "GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfig", "type": "object", "description": "The config for the corpus type of the RagCorpus.", "properties": { "memoryCorpus": { "description": "Optional. Config for the memory corpus.", "$ref": "GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfigMemoryCorpus" }, "documentCorpus": { "description": "Optional. Config for the document corpus.", "$ref": "GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfigDocumentCorpus" } } }, "GoogleCloudAiplatformV1beta1CreateEntityTypeOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateEntityTypeOperationMetadata", "type": "object", "description": "Details of operations that perform create EntityType.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for EntityType." } } }, "GoogleCloudAiplatformV1beta1RebootPersistentResourceRequest": { "description": "Request message for PersistentResourceService.RebootPersistentResource.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1RebootPersistentResourceRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SyncFeatureViewResponse": { "description": "Response message for FeatureOnlineStoreAdminService.SyncFeatureView.", "properties": { "featureViewSync": { "description": "Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SyncFeatureViewResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1TimestampSplit": { "id": "GoogleCloudAiplatformV1beta1TimestampSplit", "type": "object", "properties": { "trainingFraction": { "description": "The fraction of the input data that is to be used to train the Model.", "format": "double", "type": "number" }, "validationFraction": { "type": "number", "format": "double", "description": "The fraction of the input data that is to be used to validate the Model." }, "testFraction": { "description": "The fraction of the input data that is to be used to evaluate the Model.", "format": "double", "type": "number" }, "key": { "description": "Required. The key is a name of one of the Dataset's data columns. The values of the key (the values in the column) must be in RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z). If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.", "type": "string" } }, "description": "Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set. Supported only for tabular Datasets." }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecDeveloperConnectSource": { "description": "Specifies source code to be fetched from a Git repository managed through the Developer Connect service.", "properties": { "config": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecDeveloperConnectConfig", "description": "Required. The Developer Connect configuration that defines the specific repository, revision, and directory to use as the source code root." } }, "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecDeveloperConnectSource", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentation", "type": "object", "description": "A TrainingJob that trains and uploads an AutoML Image Segmentation Model.", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs" }, "metadata": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata", "description": "The metadata information." } } }, "GoogleCloudAiplatformV1beta1ListRagCorporaResponse": { "id": "GoogleCloudAiplatformV1beta1ListRagCorporaResponse", "type": "object", "description": "Response message for VertexRagDataService.ListRagCorpora.", "properties": { "ragCorpora": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RagCorpus" }, "description": "List of RagCorpora in the requested page." }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListRagCorporaRequest.page_token to obtain that page.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ListOptimalTrialsResponse": { "id": "GoogleCloudAiplatformV1beta1ListOptimalTrialsResponse", "type": "object", "description": "Response message for VizierService.ListOptimalTrials.", "properties": { "optimalTrials": { "description": "The pareto-optimal Trials for multiple objective Study or the optimal trial for single objective Study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Trial" } } } }, "GoogleCloudAiplatformV1beta1ClientConnectionConfig": { "properties": { "inferenceTimeout": { "type": "string", "format": "google-duration", "description": "Customizable online prediction request timeout." } }, "description": "Configurations (e.g. inference timeout) that are applied on your endpoints.", "id": "GoogleCloudAiplatformV1beta1ClientConnectionConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateModelDeploymentMonitoringJobOperationMetadata": { "description": "Runtime operation information for JobService.UpdateModelDeploymentMonitoringJob.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The operation generic information." } }, "id": "GoogleCloudAiplatformV1beta1UpdateModelDeploymentMonitoringJobOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1Rubric": { "properties": { "content": { "$ref": "GoogleCloudAiplatformV1beta1RubricContent", "description": "Required. The actual testable criteria for the rubric." }, "type": { "description": "Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: \"SUMMARIZATION_QUALITY\", \"SAFETY_HARMFUL_CONTENT\", \"INSTRUCTION_ADHERENCE\".", "type": "string" }, "importance": { "type": "string", "enumDescriptions": [ "Importance is not specified.", "High importance.", "Medium importance.", "Low importance." ], "enum": [ "IMPORTANCE_UNSPECIFIED", "HIGH", "MEDIUM", "LOW" ], "description": "Optional. The relative importance of this rubric." }, "rubricId": { "description": "Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.", "type": "string" } }, "description": "Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics.", "id": "GoogleCloudAiplatformV1beta1Rubric", "type": "object" }, "GoogleCloudAiplatformV1beta1AugmentPromptRequestModel": { "description": "Metadata of the backend deployed model.", "properties": { "modelVersion": { "description": "Optional. The model version of the backend deployed model.", "type": "string" }, "model": { "description": "Optional. The model that the user will send the augmented prompt for content generation.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1AugmentPromptRequestModel", "type": "object" }, "GoogleRpcStatus": { "id": "GoogleRpcStatus", "type": "object", "properties": { "code": { "format": "int32", "description": "The status code, which should be an enum value of google.rpc.Code.", "type": "integer" }, "message": { "description": "A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.", "type": "string" }, "details": { "description": "A list of messages that carry the error details. There is a common set of message types for APIs to use.", "type": "array", "items": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." } } } }, "description": "The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors)." }, "GoogleCloudAiplatformV1beta1ListModelVersionCheckpointsResponse": { "id": "GoogleCloudAiplatformV1beta1ListModelVersionCheckpointsResponse", "type": "object", "properties": { "checkpoints": { "description": "List of Model Version checkpoints.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelVersionCheckpoint" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListModelVersionCheckpointsRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for ModelService.ListModelVersionCheckpoints" }, "GoogleCloudAiplatformV1beta1DirectUploadSource": { "description": "The input content is encapsulated and uploaded in the request.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1DirectUploadSource", "type": "object" }, "GoogleCloudAiplatformV1beta1MetricMetadata": { "properties": { "title": { "description": "Optional. The user-friendly name for the metric. If not set for a registered metric, it will default to the metric's display name.", "type": "string" }, "scoreRange": { "description": "Optional. The range of possible scores for this metric, used for plotting.", "$ref": "GoogleCloudAiplatformV1beta1MetricMetadataScoreRange" }, "otherMetadata": { "description": "Optional. Flexible metadata for user-defined attributes.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "description": "Metadata about the metric, used for visualization and organization.", "id": "GoogleCloudAiplatformV1beta1MetricMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringObjectiveConfig": { "id": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringObjectiveConfig", "type": "object", "properties": { "objectiveConfig": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfig", "description": "The objective config of for the modelmonitoring job of this deployed model." }, "deployedModelId": { "description": "The DeployedModel ID of the objective config.", "type": "string" } }, "description": "ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig." }, "GoogleCloudAiplatformV1beta1Context": { "id": "GoogleCloudAiplatformV1beta1Context", "type": "object", "properties": { "displayName": { "description": "User provided display name of the Context. May be up to 128 Unicode characters.", "type": "string" }, "schemaVersion": { "description": "The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", "type": "string" }, "parentContexts": { "readOnly": true, "type": "array", "items": { "type": "string" }, "description": "Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts." }, "etag": { "description": "An eTag used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "description": { "description": "Description of the Context", "type": "string" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this Context was created." }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded)." }, "schemaTitle": { "description": "The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", "type": "string" }, "metadata": { "description": "Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this Context was last updated.", "readOnly": true, "type": "string" }, "name": { "description": "Immutable. The resource name of the Context.", "type": "string" } }, "description": "Instance of a general context." }, "GoogleCloudAiplatformV1beta1FeatureViewSyncSyncSummary": { "description": "Summary from the Sync job. For continuous syncs, the summary is updated periodically. For batch syncs, it gets updated on completion of the sync.", "properties": { "totalSlot": { "format": "int64", "description": "Output only. BigQuery slot milliseconds consumed for the sync job.", "readOnly": true, "type": "string" }, "systemWatermarkTime": { "description": "Lower bound of the system time watermark for the sync job. This is only set for continuously syncing feature views.", "format": "google-datetime", "type": "string" }, "rowSynced": { "readOnly": true, "type": "string", "format": "int64", "description": "Output only. Total number of rows synced." } }, "id": "GoogleCloudAiplatformV1beta1FeatureViewSyncSyncSummary", "type": "object" }, "GoogleCloudAiplatformV1beta1CancelTuningJobRequest": { "id": "GoogleCloudAiplatformV1beta1CancelTuningJobRequest", "type": "object", "properties": {}, "description": "Request message for GenAiTuningService.CancelTuningJob." }, "GoogleCloudAiplatformV1beta1ContentMap": { "id": "GoogleCloudAiplatformV1beta1ContentMap", "type": "object", "properties": { "values": { "description": "Optional. Map of placeholder to contents.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ContentMapContents" } } }, "description": "Map of placeholder in metric prompt template to contents of model input." }, "GoogleCloudAiplatformV1beta1RagContextsContext": { "id": "GoogleCloudAiplatformV1beta1RagContextsContext", "type": "object", "properties": { "sourceUri": { "description": "If the file is imported from Cloud Storage or Google Drive, source_uri will be original file URI in Cloud Storage or Google Drive; if file is uploaded, source_uri will be file display name.", "type": "string" }, "distance": { "format": "double", "description": "The distance between the query dense embedding vector and the context text vector.", "deprecated": true, "type": "number" }, "sourceDisplayName": { "description": "The file display name.", "type": "string" }, "score": { "type": "number", "format": "double", "description": "According to the underlying Vector DB and the selected metric type, the score can be either the distance or the similarity between the query and the context and its range depends on the metric type. For example, if the metric type is COSINE_DISTANCE, it represents the distance between the query and the context. The larger the distance, the less relevant the context is to the query. The range is [0, 2], while 0 means the most relevant and 2 means the least relevant." }, "chunk": { "$ref": "GoogleCloudAiplatformV1beta1RagChunk", "description": "Context of the retrieved chunk." }, "sparseDistance": { "type": "number", "deprecated": true, "description": "The distance between the query sparse embedding vector and the context text vector.", "format": "double" }, "text": { "description": "The text chunk.", "type": "string" } }, "description": "A context of the query." }, "GoogleCloudAiplatformV1beta1SchemaTextSegment": { "description": "The text segment inside of DataItem.", "properties": { "startOffset": { "type": "string", "format": "uint64", "description": "Zero-based character index of the first character of the text segment (counting characters from the beginning of the text)." }, "content": { "description": "The text content in the segment for output only.", "type": "string" }, "endOffset": { "type": "string", "description": "Zero-based character index of the first character past the end of the text segment (counting character from the beginning of the text). The character at the end_offset is NOT included in the text segment.", "format": "uint64" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTextSegment", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextExtractionPredictionInstance": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextExtractionPredictionInstance", "type": "object", "description": "Prediction input format for Text Extraction.", "properties": { "content": { "description": "The text snippet to make the predictions on.", "type": "string" }, "mimeType": { "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain", "type": "string" }, "key": { "description": "This field is only used for batch prediction. If a key is provided, the batch prediction result will by mapped to this key. If omitted, then the batch prediction result will contain the entire input instance. Vertex AI will not check if keys in the request are duplicates, so it is up to the caller to ensure the keys are unique.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ListDeploymentResourcePoolsResponse": { "properties": { "nextPageToken": { "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" }, "deploymentResourcePools": { "description": "The DeploymentResourcePools from the specified location.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DeploymentResourcePool" } } }, "description": "Response message for ListDeploymentResourcePools method.", "id": "GoogleCloudAiplatformV1beta1ListDeploymentResourcePoolsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfig": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfig", "type": "object", "properties": { "generationConfig": { "description": "Optional. Configuration for how to generate memories for the Memory Bank.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigGenerationConfig" }, "disableMemoryRevisions": { "description": "If true, no memory revisions will be created for any requests to the Memory Bank.", "type": "boolean" }, "similaritySearchConfig": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigSimilaritySearchConfig", "description": "Optional. Configuration for how to perform similarity search on memories. If not set, the Memory Bank will use the default embedding model `text-embedding-005`." }, "structuredMemoryConfigs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1StructuredMemoryConfig" }, "description": "Optional. Configuration for organizing structured memories for a particular scope." }, "customizationConfigs": { "description": "Optional. Configuration for how to customize Memory Bank behavior for a particular scope.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfig" } }, "ttlConfig": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigTtlConfig", "description": "Optional. Configuration for automatic TTL (\"time-to-live\") of the memories in the Memory Bank. If not set, TTL will not be applied automatically. The TTL can be explicitly set by modifying the `expire_time` of each Memory resource." } }, "description": "Specification for a Memory Bank." }, "GoogleCloudAiplatformV1beta1AddExecutionEventsRequest": { "properties": { "events": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Event" }, "description": "The Events to create and add." } }, "description": "Request message for MetadataService.AddExecutionEvents.", "id": "GoogleCloudAiplatformV1beta1AddExecutionEventsRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1PostStartupScriptConfig": { "id": "GoogleCloudAiplatformV1beta1PostStartupScriptConfig", "type": "object", "description": "Post startup script config.", "properties": { "postStartupScriptUrl": { "description": "Optional. Post startup script url to download. Example: `gs://bucket/script.sh`", "type": "string" }, "postStartupScript": { "description": "Optional. Post startup script to run after runtime is started.", "type": "string" }, "postStartupScriptBehavior": { "description": "Optional. Post startup script behavior that defines download and execution behavior.", "enum": [ "POST_STARTUP_SCRIPT_BEHAVIOR_UNSPECIFIED", "RUN_ONCE", "RUN_EVERY_START", "DOWNLOAD_AND_RUN_EVERY_START" ], "type": "string", "enumDescriptions": [ "Unspecified post startup script behavior.", "Run post startup script after runtime is started.", "Run post startup script after runtime is stopped.", "Download and run post startup script every time runtime is started." ] } } }, "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExample": { "description": "An example of how to generate memories for a particular scope.", "properties": { "conversationSource": { "$ref": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSource", "description": "A conversation source for the example." }, "generatedMemories": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleGeneratedMemory" }, "description": "Optional. Represents the memories that are expected to be generated from the input conversation. An empty list indicates that no memories are expected to be generated for the input conversation." } }, "id": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExample", "type": "object" }, "GoogleCloudAiplatformV1beta1TensorboardBlob": { "description": "One blob (e.g, image, graph) viewable on a blob metric plot.", "properties": { "data": { "type": "string", "description": "Optional. The bytes of the blob is not present unless it's returned by the ReadTensorboardBlobData endpoint.", "format": "byte" }, "id": { "description": "Output only. A URI safe key uniquely identifying a blob. Can be used to locate the blob stored in the Cloud Storage bucket of the consumer project.", "type": "string", "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1TensorboardBlob", "type": "object" }, "GoogleCloudAiplatformV1beta1PurgeArtifactsMetadata": { "id": "GoogleCloudAiplatformV1beta1PurgeArtifactsMetadata", "type": "object", "description": "Details of operations that perform MetadataService.PurgeArtifacts.", "properties": { "genericMetadata": { "description": "Operation metadata for purging Artifacts.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1beta1StudySpecStudyStoppingConfig": { "description": "The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.", "properties": { "minimumRuntimeConstraint": { "$ref": "GoogleCloudAiplatformV1beta1StudyTimeConstraint", "description": "Each \"stopping rule\" in this proto specifies an \"if\" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting `min_num_trials=5` and `always_stop_after= 1 hour` means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose \"if\" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to _resume_ a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study." }, "maximumRuntimeConstraint": { "$ref": "GoogleCloudAiplatformV1beta1StudyTimeConstraint", "description": "If the specified time or duration has passed, stop the study." }, "minNumTrials": { "type": "integer", "format": "int32", "description": "If there are fewer than this many COMPLETED trials, do not stop the study." }, "maxDurationNoProgress": { "type": "string", "description": "If the objective value has not improved for this much time, stop the study. WARNING: Effective only for single-objective studies.", "format": "google-duration" }, "maxNumTrialsNoProgress": { "type": "integer", "format": "int32", "description": "If the objective value has not improved for this many consecutive trials, stop the study. WARNING: Effective only for single-objective studies." }, "shouldStopAsap": { "description": "If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state. The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth).", "type": "boolean" }, "maxNumTrials": { "format": "int32", "description": "If there are more than this many trials, stop the study.", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1StudySpecStudyStoppingConfig", "type": "object" }, "GoogleIamV1Binding": { "properties": { "members": { "description": "Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workforce identity pool. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/group/{group_id}`: All workforce identities in a group. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All workforce identities with a specific attribute value. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/*`: All identities in a workforce identity pool. * `principal://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workload identity pool. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/group/{group_id}`: A workload identity pool group. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All identities in a workload identity pool with a certain attribute. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/*`: All identities in a workload identity pool. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `deleted:principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: Deleted single identity in a workforce identity pool. For example, `deleted:principal://iam.googleapis.com/locations/global/workforcePools/my-pool-id/subject/my-subject-attribute-value`.", "type": "array", "items": { "type": "string" } }, "role": { "description": "Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`. For an overview of the IAM roles and permissions, see the [IAM documentation](https://cloud.google.com/iam/docs/roles-overview). For a list of the available pre-defined roles, see [here](https://cloud.google.com/iam/docs/understanding-roles).", "type": "string" }, "condition": { "$ref": "GoogleTypeExpr", "description": "The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies)." } }, "description": "Associates `members`, or principals, with a `role`.", "id": "GoogleIamV1Binding", "type": "object" }, "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployGke": { "properties": { "gkeYamlConfigs": { "description": "Optional. GKE deployment configuration in yaml format.", "type": "array", "items": { "type": "string" } } }, "description": "Configurations for PublisherModel GKE deployment", "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployGke", "type": "object" }, "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentTemplatesResponse": { "id": "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentTemplatesResponse", "type": "object", "properties": { "sandboxEnvironmentTemplates": { "description": "The SandboxEnvironmentTemplates matching the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplate" } }, "nextPageToken": { "description": "A token, which can be sent as ListSandboxEnvironmentTemplatesRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages.", "type": "string" } }, "description": "Response message for SandboxEnvironmentService.ListSandboxEnvironmentTemplates." }, "GoogleCloudAiplatformV1beta1SummarizationQualitySpec": { "id": "GoogleCloudAiplatformV1beta1SummarizationQualitySpec", "type": "object", "properties": { "version": { "format": "int32", "description": "Optional. Which version to use for evaluation.", "type": "integer" }, "useReference": { "description": "Optional. Whether to use instance.reference to compute summarization quality.", "type": "boolean" } }, "description": "Spec for summarization quality score metric." }, "GoogleCloudAiplatformV1beta1EvaluationRequest": { "id": "GoogleCloudAiplatformV1beta1EvaluationRequest", "type": "object", "description": "A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`.", "properties": { "goldenResponse": { "$ref": "GoogleCloudAiplatformV1beta1CandidateResponse", "description": "Optional. The Ideal response or ground truth." }, "prompt": { "description": "Optional. The request/prompt to evaluate.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationPrompt" }, "rubrics": { "description": "Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1RubricGroup" } }, "candidateResponses": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1CandidateResponse" }, "description": "Optional. Responses from model under test and other baseline models for comparison." } } }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionImageSegmentationPredictionResult": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionImageSegmentationPredictionResult", "type": "object", "properties": { "categoryMask": { "description": "A PNG image where each pixel in the mask represents the category in which the pixel in the original image was predicted to belong to. The size of this image will be the same as the original image. The mapping between the AnntoationSpec and the color can be found in model's metadata. The model will choose the most likely category and if none of the categories reach the confidence threshold, the pixel will be marked as background.", "type": "string" }, "confidenceMask": { "description": "A one channel image which is encoded as an 8bit lossless PNG. The size of the image will be the same as the original image. For a specific pixel, darker color means less confidence in correctness of the cateogry in the categoryMask for the corresponding pixel. Black means no confidence and white means complete confidence.", "type": "string" } }, "description": "Prediction output format for Image Segmentation." }, "GoogleCloudAiplatformV1beta1CoherenceSpec": { "description": "Spec for coherence score metric.", "properties": { "version": { "description": "Optional. Which version to use for evaluation.", "format": "int32", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1CoherenceSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageObjectDetectionPredictionParams": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageObjectDetectionPredictionParams", "type": "object", "properties": { "confidenceThreshold": { "format": "float", "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", "type": "number" }, "maxPredictions": { "type": "integer", "format": "int32", "description": "The Model only returns up to that many top, by confidence score, predictions per instance. Note that number of returned predictions is also limited by metadata's predictionsLimit. Default value is 10." } }, "description": "Prediction model parameters for Image Object Detection." }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetrics": { "properties": { "meanAveragePrecision": { "description": "The mean average precision, most often close to `auPrc`.", "format": "float", "type": "number" }, "confidenceMetrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics" }, "description": "Metrics for each label-match confidence_threshold from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is derived from them." }, "iouThreshold": { "description": "The intersection-over-union threshold value used to compute this metrics entry.", "format": "float", "type": "number" } }, "description": "Bounding box matching model metrics for a single intersection-over-union threshold and multiple label match confidence thresholds.", "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetrics", "type": "object" }, "GoogleCloudAiplatformV1beta1MemoryMetadataValue": { "properties": { "boolValue": { "description": "Represents a boolean value.", "type": "boolean" }, "timestampValue": { "type": "string", "description": "Represents a timestamp value. When filtering on timestamp values, only the seconds field will be compared.", "format": "google-datetime" }, "stringValue": { "description": "Represents a string value.", "type": "string" }, "doubleValue": { "type": "number", "description": "Represents a double value.", "format": "double" } }, "description": "Memory metadata.", "id": "GoogleCloudAiplatformV1beta1MemoryMetadataValue", "type": "object" }, "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigPersistentResourceRuntimeDetail": { "description": "Persistent resource based runtime detail. For more information about persistent resource, refer to https://cloud.google.com/vertex-ai/docs/training/persistent-resource-overview", "properties": { "persistentResourceName": { "description": "Persistent resource name. Format: `projects/{project}/locations/{location}/persistentResources/{persistent_resource}`", "type": "string" }, "taskResourceUnavailableWaitTimeMs": { "format": "int64", "description": "The max time a pipeline task waits for the required CPU, memory, or accelerator resource to become available from the specified persistent resource. Default wait time is 0.", "type": "string" }, "taskResourceUnavailableTimeoutBehavior": { "type": "string", "enumDescriptions": [ "Unspecified. Behavior is same as `FAIL`.", "Fail the task if the timeout is reached.", "Fall back to on-demand execution if the timeout is reached." ], "description": "Specifies the behavior to take if the timeout is reached.", "enum": [ "TASK_RESOURCE_UNAVAILABLE_TIMEOUT_BEHAVIOR_UNSPECIFIED", "FAIL", "FALL_BACK_TO_ON_DEMAND" ] } }, "id": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigPersistentResourceRuntimeDetail", "type": "object" }, "GoogleCloudAiplatformV1beta1PointwiseMetricInput": { "id": "GoogleCloudAiplatformV1beta1PointwiseMetricInput", "type": "object", "description": "Input for pointwise metric.", "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1beta1PointwiseMetricInstance", "description": "Required. Pointwise metric instance." }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1PointwiseMetricSpec", "description": "Required. Spec for pointwise metric." } } }, "GoogleCloudAiplatformV1beta1UpsertDatapointsRequest": { "id": "GoogleCloudAiplatformV1beta1UpsertDatapointsRequest", "type": "object", "properties": { "datapoints": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1IndexDatapoint" }, "description": "A list of datapoints to be created/updated." }, "updateMask": { "description": "Optional. Update mask is used to specify the fields to be overwritten in the datapoints by the update. The fields specified in the update_mask are relative to each IndexDatapoint inside datapoints, not the full request. Updatable fields: * Use `all_restricts` to update both restricts and numeric_restricts.", "format": "google-fieldmask", "type": "string" } }, "description": "Request message for IndexService.UpsertDatapoints" }, "GoogleCloudAiplatformV1beta1SamplingStrategy": { "id": "GoogleCloudAiplatformV1beta1SamplingStrategy", "type": "object", "description": "Sampling Strategy for logging, can be for both training and prediction dataset.", "properties": { "randomSampleConfig": { "$ref": "GoogleCloudAiplatformV1beta1SamplingStrategyRandomSampleConfig", "description": "Random sample config. Will support more sampling strategies later." } } }, "GoogleCloudAiplatformV1beta1SchemaTextDatasetMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaTextDatasetMetadata", "type": "object", "properties": { "gcsBucket": { "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset.", "type": "string" }, "dataItemSchemaUri": { "description": "Points to a YAML file stored on Google Cloud Storage describing payload of the Text DataItems that belong to this Dataset.", "type": "string" } }, "description": "The metadata of Datasets that contain Text DataItems." }, "GoogleCloudAiplatformV1beta1EvaluationParserConfigCustomCodeParserConfig": { "properties": { "parsingFunction": { "description": "Required. Python function for parsing results. The function should be defined within this string. The function takes a list of strings (LLM responses) and should return either a list of dictionaries (for rubrics) or a single dictionary (for a metric result). Example function signature: def parse(responses: list[str]) -\u003e list[dict[str, Any]] | dict[str, Any]: When parsing rubrics, return a list of dictionaries, where each dictionary represents a Rubric. Example for rubrics: [ { \"content\": {\"property\": {\"description\": \"The response is factual.\"}}, \"type\": \"FACTUALITY\", \"importance\": \"HIGH\" }, { \"content\": {\"property\": {\"description\": \"The response is fluent.\"}}, \"type\": \"FLUENCY\", \"importance\": \"MEDIUM\" } ] When parsing critique results, return a dictionary representing a MetricResult. Example for a metric result: { \"score\": 0.8, \"explanation\": \"The model followed most instructions.\", \"rubric_verdicts\": [...] } ... code for result extraction and aggregation", "type": "string" } }, "description": "Configuration for parsing the LLM response using custom code.", "id": "GoogleCloudAiplatformV1beta1EvaluationParserConfigCustomCodeParserConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateContentRequest": { "description": "Request message for [PredictionService.GenerateContent].", "properties": { "systemInstruction": { "description": "Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.", "$ref": "GoogleCloudAiplatformV1beta1Content" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter." }, "safetySettings": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SafetySetting" }, "description": "Optional. Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates." }, "toolConfig": { "$ref": "GoogleCloudAiplatformV1beta1ToolConfig", "description": "Optional. Tool config. This config is shared for all tools provided in the request." }, "contents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "description": "Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request." }, "tools": { "description": "Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" } }, "modelArmorConfig": { "description": "Optional. Settings for prompt and response sanitization using the Model Armor service. If supplied, safety_settings must not be supplied.", "$ref": "GoogleCloudAiplatformV1beta1ModelArmorConfig" }, "generationConfig": { "description": "Optional. Generation config.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig" }, "cachedContent": { "description": "Optional. The name of the cached content used as context to serve the prediction. Note: only used in explicit caching, where users can have control over caching (e.g. what content to cache) and enjoy guaranteed cost savings. Format: `projects/{project}/locations/{location}/cachedContents/{cachedContent}`", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1GenerateContentRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1FilterSplit": { "description": "Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign). Supported only for unstructured Datasets. ", "properties": { "testFilter": { "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.", "type": "string" }, "trainingFilter": { "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.", "type": "string" }, "validationFilter": { "description": "Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1FilterSplit", "type": "object" }, "GoogleCloudAiplatformV1beta1LogprobsResultTopCandidates": { "description": "A list of the top candidate tokens and their log probabilities at each decoding step. This can be used to see what other tokens the model considered.", "properties": { "candidates": { "description": "The list of candidate tokens, sorted by log probability in descending order.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LogprobsResultCandidate" } } }, "id": "GoogleCloudAiplatformV1beta1LogprobsResultTopCandidates", "type": "object" }, "GoogleCloudAiplatformV1beta1GoogleSearchRetrieval": { "properties": { "dynamicRetrievalConfig": { "description": "Specifies the dynamic retrieval configuration for the given source.", "$ref": "GoogleCloudAiplatformV1beta1DynamicRetrievalConfig" } }, "description": "Tool to retrieve public web data for grounding, powered by Google.", "id": "GoogleCloudAiplatformV1beta1GoogleSearchRetrieval", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchDeleteRagDataSchemasRequest": { "id": "GoogleCloudAiplatformV1beta1BatchDeleteRagDataSchemasRequest", "type": "object", "description": "Request message for VertexRagDataService.BatchDeleteRagDataSchemas.", "properties": { "names": { "description": "Required. The RagDataSchemas to delete. A maximum of 500 schemas can be deleted in a batch. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragDataSchemas/{rag_data_schema}`", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchMetricValue": { "properties": { "score": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. TrajectoryAnyOrderMatch score." } }, "description": "TrajectoryAnyOrderMatch metric value for an instance.", "id": "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchMetricValue", "type": "object" }, "GoogleCloudAiplatformV1beta1ImportDataOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1ImportDataOperationMetadata", "type": "object", "description": "Runtime operation information for DatasetService.ImportData.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The common part of the operation metadata." } } }, "GoogleCloudAiplatformV1beta1SummarizationVerbositySpec": { "properties": { "useReference": { "description": "Optional. Whether to use instance.reference to compute summarization verbosity.", "type": "boolean" }, "version": { "description": "Optional. Which version to use for evaluation.", "format": "int32", "type": "integer" } }, "description": "Spec for summarization verbosity score metric.", "id": "GoogleCloudAiplatformV1beta1SummarizationVerbositySpec", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureViewBigtableMetadata": { "description": "Metadata for the Cloud Bigtable that supports directly interacting Bigtable instances.", "properties": { "readAppProfile": { "description": "Output only. The Bigtable App Profile to use for reading from Bigtable.", "type": "string", "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1FeatureViewBigtableMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataRecordError": { "id": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataRecordError", "type": "object", "properties": { "sourceGcsUri": { "description": "Cloud Storage URI pointing to the original file in user's bucket.", "type": "string" }, "embeddingId": { "description": "Empty if the embedding id is failed to parse.", "type": "string" }, "errorType": { "description": "The error type of this record.", "enum": [ "ERROR_TYPE_UNSPECIFIED", "EMPTY_LINE", "INVALID_JSON_SYNTAX", "INVALID_CSV_SYNTAX", "INVALID_AVRO_SYNTAX", "INVALID_EMBEDDING_ID", "EMBEDDING_SIZE_MISMATCH", "NAMESPACE_MISSING", "PARSING_ERROR", "DUPLICATE_NAMESPACE", "OP_IN_DATAPOINT", "MULTIPLE_VALUES", "INVALID_NUMERIC_VALUE", "INVALID_ENCODING", "INVALID_SPARSE_DIMENSIONS", "INVALID_TOKEN_VALUE", "INVALID_SPARSE_EMBEDDING", "INVALID_EMBEDDING", "INVALID_EMBEDDING_METADATA", "EMBEDDING_METADATA_EXCEEDS_SIZE_LIMIT" ], "type": "string", "enumDescriptions": [ "Default, shall not be used.", "The record is empty.", "Invalid json format.", "Invalid csv format.", "Invalid avro format.", "The embedding id is not valid.", "The size of the dense embedding vectors does not match with the specified dimension.", "The `namespace` field is missing.", "Generic catch-all error. Only used for validation failure where the root cause cannot be easily retrieved programmatically.", "There are multiple restricts with the same `namespace` value.", "Numeric restrict has operator specified in datapoint.", "Numeric restrict has multiple values specified.", "Numeric restrict has invalid numeric value specified.", "File is not in UTF_8 format.", "Error parsing sparse dimensions field.", "Token restrict value is invalid.", "Invalid sparse embedding.", "Invalid dense embedding.", "Invalid embedding metadata.", "Embedding metadata exceeds size limit." ] }, "errorMessage": { "description": "A human-readable message that is shown to the user to help them fix the error. Note that this message may change from time to time, your code should check against error_type as the source of truth.", "type": "string" }, "rawRecord": { "description": "The original content of this record.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1OutputFieldSpec": { "id": "GoogleCloudAiplatformV1beta1OutputFieldSpec", "type": "object", "description": "Specifies the properties of a single field that are included in each generated synthetic example. This helps the model understand what kind of data to generate for each field.", "properties": { "guidance": { "description": "Optional. Specific instructions for the large language model on how to generate content for this particular field. While the LLM can sometimes infer content from the field name, providing explicit guidance is preferred. For example, for a field named \"review\", the guidance could be \"A positive review about a coffee maker.\"", "type": "string" }, "fieldType": { "type": "string", "enumDescriptions": [ "The field type is not specified. Defaults to CONTENT.", "The field can contain any type of content, including text, images, and audio.", "The field contains only text.", "The field contains image data.", "The field contains audio data." ], "enum": [ "FIELD_TYPE_UNSPECIFIED", "CONTENT", "TEXT", "IMAGE", "AUDIO" ], "description": "Optional. The data type of the field. Defaults to CONTENT if not set." }, "fieldName": { "description": "Required. The name of this field in the generated synthetic data, such as \"email_subject\" or \"customer_review\".", "type": "string" } } }, "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigManualRoutingMode": { "properties": { "modelName": { "description": "The name of the model to use. Only public LLM models are accepted.", "type": "string" } }, "description": "The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided.", "id": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigManualRoutingMode", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsGranularity": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsGranularity", "type": "object", "description": "A duration of time expressed in time granularity units.", "properties": { "unit": { "description": "The time granularity unit of this time period. The supported units are: * \"minute\" * \"hour\" * \"day\" * \"week\" * \"month\" * \"year\"", "type": "string" }, "quantity": { "type": "string", "description": "The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1.", "format": "int64" } } }, "GoogleCloudAiplatformV1beta1ListDataLabelingJobsResponse": { "id": "GoogleCloudAiplatformV1beta1ListDataLabelingJobsResponse", "type": "object", "description": "Response message for JobService.ListDataLabelingJobs.", "properties": { "dataLabelingJobs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DataLabelingJob" }, "description": "A list of DataLabelingJobs that matches the specified filter in the request." }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SearchMigratableResourcesResponse": { "description": "Response message for MigrationService.SearchMigratableResources.", "properties": { "migratableResources": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MigratableResource" }, "description": "All migratable resources that can be migrated to the location specified in the request." }, "nextPageToken": { "description": "The standard next-page token. The migratable_resources may not fill page_size in SearchMigratableResourcesRequest even when there are subsequent pages.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SearchMigratableResourcesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchSpec": { "id": "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchSpec", "type": "object", "properties": {}, "description": "Spec for TrajectoryInOrderMatch metric - returns 1 if tool calls in the reference trajectory appear in the predicted trajectory in the same order, else 0." }, "GoogleCloudAiplatformV1beta1DeployRequest": { "properties": { "customModel": { "description": "The custom model to deploy from a Google Cloud Storage URI.", "$ref": "GoogleCloudAiplatformV1beta1DeployRequestCustomModel" }, "modelConfig": { "description": "Optional. The model config to use for the deployment. If not specified, the default model config will be used.", "$ref": "GoogleCloudAiplatformV1beta1DeployRequestModelConfig" }, "deployConfig": { "$ref": "GoogleCloudAiplatformV1beta1DeployRequestDeployConfig", "description": "Optional. The deploy config to use for the deployment. If not specified, the default deploy config will be used." }, "endpointConfig": { "description": "Optional. The endpoint config to use for the deployment. If not specified, the default endpoint config will be used.", "$ref": "GoogleCloudAiplatformV1beta1DeployRequestEndpointConfig" }, "huggingFaceModelId": { "description": "The Hugging Face model to deploy. Format: Hugging Face model ID like `google/gemma-2-2b-it`.", "type": "string" }, "publisherModelName": { "description": "The Model Garden model to deploy. Format: `publishers/{publisher}/models/{publisher_model}@{version_id}`, or `publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001`.", "type": "string" } }, "description": "Request message for ModelGardenService.Deploy.", "id": "GoogleCloudAiplatformV1beta1DeployRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfig": { "properties": { "generateMemoriesExamples": { "description": "Optional. Provides examples of how to generate memories for a particular scope.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExample" } }, "disableNaturalLanguageMemories": { "description": "Optional. Indicates whether natural language memory generation should be disabled for all requests. By default, natural language memory generation is enabled. Set this to `true` when you only want to generate structured memories.", "type": "boolean" }, "scopeKeys": { "description": "Optional. Represents the scope keys (i.e. 'user_id') for which to use this config. A request's scope must include all of the provided keys for the config to be used (order does not matter). If empty, then the config will be used for all requests that do not have a more specific config. Only one default config is allowed per Memory Bank.", "type": "array", "items": { "type": "string" } }, "enableThirdPersonMemories": { "description": "Optional. Indicates whether the memories will be generated in the third person (i.e. \"The user generates memories with Memory Bank.\"). By default, the memories will be generated in the first person (i.e. \"I generate memories with Memory Bank.\")", "type": "boolean" }, "memoryTopics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopic" }, "description": "Optional. Represents topics of information that should be extracted from conversations and stored as memories. If not set, then Memory Bank's default topics will be used." }, "consolidationConfig": { "description": "Optional. Represents configuration for customizing how memories are consolidated together.", "$ref": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigConsolidationConfig" } }, "description": "Represents configuration for organizing natural language memories for a particular scope.", "id": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecAppBuilderDataLinkedResource": { "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecAppBuilderDataLinkedResource", "type": "object", "description": "A linked resource attached to the application by the user.", "properties": { "type": { "description": "The type of the linked resource. e.g., \"SAVED_PROMPT\", \"AI_AGENT\" This string corresponds to the name of the LinkedResourceType enum member. See: google3/cloud/console/web/ai/platform/llm/prompts/build/services/specs_repository_service/linked_resources/linked_resource.ts", "type": "string" }, "displayName": { "description": "A user-friendly name for the data source shown in the UI.", "type": "string" }, "name": { "description": "The unique resource name of the data source. The format is determined by the 'type' field. For type \"SAVED_PROMPT\": projects/{project}/locations/{location}/datasets/{dataset} For type \"AI_AGENT\": projects/{project}/locations/{location}/agents/{agent}", "type": "string" } } }, "GoogleCloudAiplatformV1beta1KeepAliveProbe": { "description": "Represents the configuration for keep-alive probe. Contains configuration on a specified endpoint that a deployment host should use to keep the container alive based on the probe settings.", "properties": { "maxSeconds": { "description": "Optional. Specifies the maximum duration (in seconds) to keep the instance alive via this probe. Can be a maximum of 3600 seconds (1 hour).", "format": "int32", "type": "integer" }, "httpGet": { "description": "Optional. Specifies the HTTP GET configuration for the probe.", "$ref": "GoogleCloudAiplatformV1beta1KeepAliveProbeHttpGet" } }, "id": "GoogleCloudAiplatformV1beta1KeepAliveProbe", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchExamplesRequest": { "id": "GoogleCloudAiplatformV1beta1SearchExamplesRequest", "type": "object", "properties": { "storedContentsExampleParameters": { "description": "The parameters of StoredContentsExamples to be searched.", "$ref": "GoogleCloudAiplatformV1beta1StoredContentsExampleParameters" }, "topK": { "type": "string", "description": "Optional. The number of similar examples to return.", "format": "int64" } }, "description": "Request message for ExampleStoreService.SearchExamples." }, "GoogleCloudAiplatformV1beta1MemoryGenerationTriggerConfigGenerationTriggerRule": { "id": "GoogleCloudAiplatformV1beta1MemoryGenerationTriggerConfigGenerationTriggerRule", "type": "object", "properties": { "eventCount": { "type": "integer", "description": "Optional. Specifies to trigger generation when the event count reaches this limit.", "format": "int32" }, "fixedInterval": { "type": "string", "format": "google-duration", "description": "Optional. Specifies to trigger generation at a fixed interval. The duration must have a minute-level granularity." }, "idleDuration": { "type": "string", "format": "google-duration", "description": "Optional. Specifies to trigger generation if the stream is inactive for the specified duration after the most recent event. The duration must have a minute-level granularity." } }, "description": "Represents the active rule that determines when to flush the buffer." }, "GoogleCloudAiplatformV1beta1ListA2aTasksResponse": { "id": "GoogleCloudAiplatformV1beta1ListA2aTasksResponse", "type": "object", "description": "Response message for AgentEngineTaskStoreService.ListA2aTasks.", "properties": { "a2aTasks": { "description": "List of A2aTasks in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1A2aTask" } }, "nextPageToken": { "description": "A token, which can be sent as ListA2aTasksRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1PipelineJob": { "properties": { "startTime": { "description": "Output only. Pipeline start time.", "format": "google-datetime", "type": "string", "readOnly": true }, "serviceAccount": { "description": "The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.", "type": "string" }, "network": { "description": "The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.", "type": "string" }, "displayName": { "description": "The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "name": { "type": "string", "readOnly": true, "description": "Output only. The resource name of the PipelineJob." }, "satisfiesPzi": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "jobDetail": { "description": "Output only. The details of pipeline run. Not available in the list view.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1PipelineJobDetail" }, "scheduleName": { "readOnly": true, "type": "string", "description": "Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API." }, "templateUri": { "description": "A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.", "type": "string" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key." }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this PipelineJob was most recently updated.", "readOnly": true, "type": "string" }, "endTime": { "description": "Output only. Pipeline end time.", "format": "google-datetime", "type": "string", "readOnly": true }, "labels": { "description": "The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.", "type": "object", "additionalProperties": { "type": "string" } }, "createTime": { "description": "Output only. Pipeline creation time.", "format": "google-datetime", "type": "string", "readOnly": true }, "pipelineSpec": { "description": "A compiled definition of a pipeline, represented as a `JSON` object. Defines the structure of the pipeline, including its components, tasks, and parameters. This specification is generated by compiling a pipeline function defined in `Python` using the `Kubeflow Pipelines SDK`.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "state": { "readOnly": true, "type": "string", "enumDescriptions": [ "The pipeline state is unspecified.", "The pipeline has been created or resumed, and processing has not yet begun.", "The service is preparing to run the pipeline.", "The pipeline is in progress.", "The pipeline completed successfully.", "The pipeline failed.", "The pipeline is being cancelled. From this state, the pipeline may only go to either PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED.", "The pipeline has been cancelled.", "The pipeline has been stopped, and can be resumed." ], "enum": [ "PIPELINE_STATE_UNSPECIFIED", "PIPELINE_STATE_QUEUED", "PIPELINE_STATE_PENDING", "PIPELINE_STATE_RUNNING", "PIPELINE_STATE_SUCCEEDED", "PIPELINE_STATE_FAILED", "PIPELINE_STATE_CANCELLING", "PIPELINE_STATE_CANCELLED", "PIPELINE_STATE_PAUSED" ], "description": "Output only. The detailed state of the job." }, "pscInterfaceConfig": { "description": "Optional. Configuration for PSC-I for PipelineJob.", "$ref": "GoogleCloudAiplatformV1beta1PscInterfaceConfig" }, "preflightValidations": { "description": "Optional. Whether to do component level validations before job creation.", "type": "boolean" }, "templateMetadata": { "description": "Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1PipelineTemplateMetadata" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" }, "reservedIpRanges": { "description": "A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].", "type": "array", "items": { "type": "string" } }, "error": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED." }, "pipelineTaskRerunConfigs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskRerunConfig" }, "description": "Optional. The rerun configs for each task in the pipeline job. By default, the rerun will: 1. Use the same input artifacts as the original run. 2. Use the same input parameters as the original run. 3. Skip all the tasks that are already succeeded in the original run. 4. Rerun all the tasks that are not succeeded in the original run. By providing this field, users can override the default behavior and specify the rerun config for each task." }, "originalPipelineJobId": { "type": "string", "description": "Optional. The original pipeline job id if this pipeline job is a rerun of a previous pipeline job.", "format": "int64" }, "runtimeConfig": { "description": "Runtime config of the pipeline.", "$ref": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfig" } }, "description": "An instance of a machine learning PipelineJob.", "id": "GoogleCloudAiplatformV1beta1PipelineJob", "type": "object" }, "GoogleCloudAiplatformV1beta1AppendA2aTaskEventsRequest": { "id": "GoogleCloudAiplatformV1beta1AppendA2aTaskEventsRequest", "type": "object", "properties": { "taskEvents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TaskEvent" }, "description": "Required. The events to append. The number of events to append must be less than or equal to 100. Otherwise, an exception will be thrown." } }, "description": "Request message for AgentEngineTaskStoreService.AppendA2aTaskEvents." }, "GoogleCloudAiplatformV1beta1TimeSeriesDataPoint": { "properties": { "tensor": { "description": "A tensor value.", "$ref": "GoogleCloudAiplatformV1beta1TensorboardTensor" }, "wallTime": { "type": "string", "format": "google-datetime", "description": "Wall clock timestamp when this data point is generated by the end user." }, "scalar": { "$ref": "GoogleCloudAiplatformV1beta1Scalar", "description": "A scalar value." }, "blobs": { "description": "A blob sequence value.", "$ref": "GoogleCloudAiplatformV1beta1TensorboardBlobSequence" }, "step": { "type": "string", "format": "int64", "description": "Step index of this data point within the run." } }, "description": "A TensorboardTimeSeries data point.", "id": "GoogleCloudAiplatformV1beta1TimeSeriesDataPoint", "type": "object" }, "GoogleCloudAiplatformV1beta1ExecuteCodeRequest": { "id": "GoogleCloudAiplatformV1beta1ExecuteCodeRequest", "type": "object", "description": "Request message for SandboxEnvironmentExecutionService.ExecuteCode.", "properties": { "inputs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Chunk" }, "description": "Required. The inputs used for the stateless code execution." } } }, "GoogleCloudAiplatformV1beta1ListPersistentResourcesResponse": { "description": "Response message for PersistentResourceService.ListPersistentResources", "properties": { "persistentResources": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PersistentResource" } }, "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListPersistentResourcesRequest.page_token to obtain that page.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListPersistentResourcesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1Session": { "properties": { "userId": { "description": "Required. Immutable. String id provided by the user", "type": "string" }, "displayName": { "description": "Optional. The display name of the session.", "type": "string" }, "sessionState": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. Session specific memory which stores key conversation points." }, "ttl": { "description": "Optional. Input only. The TTL for this session. The minimum value is 24 hours.", "format": "google-duration", "type": "string" }, "expireTime": { "type": "string", "format": "google-datetime", "description": "Optional. Timestamp of when this session is considered expired. This is *always* provided on output, regardless of what was sent on input. The minimum value is 24 hours from the time of creation." }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when the session was created.", "format": "google-datetime" }, "name": { "description": "Identifier. The resource name of the session. Format: 'projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}'.", "type": "string" }, "updateTime": { "description": "Output only. Timestamp when the session was updated.", "format": "google-datetime", "type": "string", "readOnly": true }, "labels": { "description": "The labels with user-defined metadata to organize your Sessions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", "type": "object", "additionalProperties": { "type": "string" } } }, "description": "A session contains a set of actions between users and Vertex agents.", "id": "GoogleCloudAiplatformV1beta1Session", "type": "object" }, "GoogleCloudAiplatformV1beta1BigQueryRequestSetSamplingConfig": { "id": "GoogleCloudAiplatformV1beta1BigQueryRequestSetSamplingConfig", "type": "object", "description": "The sampling config.", "properties": { "samplingMethod": { "enum": [ "SAMPLING_METHOD_UNSPECIFIED", "RANDOM" ], "description": "Optional. The sampling method to use.", "type": "string", "enumDescriptions": [ "Unspecified sampling method.", "Random sampling." ] }, "samplingCount": { "description": "Optional. The total number of logged data to import. If available data is less than the sampling count, all data will be imported. Default is 100.", "format": "int32", "type": "integer" }, "samplingDuration": { "type": "string", "description": "Optional. How long to wait before sampling data from the BigQuery table. If not specified, defaults to 0.", "format": "google-duration" } } }, "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigAgentRunConfigUserSimulatorConfig": { "description": "Used for multi-turn agent scraping. Contains configuration for a user simulator that uses an LLM to generate messages on behalf of the user.", "properties": { "modelName": { "description": "The model name to use for multi-turn agent scraping to get next user message, e.g. \"gemini-3-flash-preview\".", "type": "string" }, "maxTurn": { "type": "integer", "description": "Maximum number of invocations allowed by the multi-turn agent scraping. This property allows us to stop a run-off conversation, where the agent and the user simulator get into a never ending loop. The initial fixed prompt is also counted as an invocation.", "format": "int32" }, "modelConfig": { "description": "The configuration for the model.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig" } }, "id": "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigAgentRunConfigUserSimulatorConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1StudySpecMetricSpec": { "id": "GoogleCloudAiplatformV1beta1StudySpecMetricSpec", "type": "object", "properties": { "safetyConfig": { "$ref": "GoogleCloudAiplatformV1beta1StudySpecMetricSpecSafetyMetricConfig", "description": "Used for safe search. In the case, the metric will be a safety metric. You must provide a separate metric for objective metric." }, "metricId": { "description": "Required. The ID of the metric. Must not contain whitespaces and must be unique amongst all MetricSpecs.", "type": "string" }, "goal": { "enum": [ "GOAL_TYPE_UNSPECIFIED", "MAXIMIZE", "MINIMIZE" ], "description": "Required. The optimization goal of the metric.", "type": "string", "enumDescriptions": [ "Goal Type will default to maximize.", "Maximize the goal metric.", "Minimize the goal metric." ] } }, "description": "Represents a metric to optimize." }, "GoogleCloudAiplatformV1beta1FunctionDeclaration": { "id": "GoogleCloudAiplatformV1beta1FunctionDeclaration", "type": "object", "description": "Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.", "properties": { "description": { "description": "Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.", "type": "string" }, "parametersJsonSchema": { "description": "Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { \"type\": \"object\", \"properties\": { \"name\": { \"type\": \"string\" }, \"age\": { \"type\": \"integer\" } }, \"additionalProperties\": false, \"required\": [\"name\", \"age\"], \"propertyOrdering\": [\"name\", \"age\"] } ``` This field is mutually exclusive with `parameters`.", "type": "any" }, "response": { "$ref": "GoogleCloudAiplatformV1beta1Schema", "description": "Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function." }, "responseJsonSchema": { "description": "Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.", "type": "any" }, "parameters": { "$ref": "GoogleCloudAiplatformV1beta1Schema", "description": "Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1" }, "name": { "description": "Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1NasJobSpec": { "description": "Represents the spec of a NasJob.", "properties": { "searchSpaceSpec": { "description": "It defines the search space for Neural Architecture Search (NAS).", "type": "string" }, "resumeNasJobId": { "description": "The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.", "type": "string" }, "multiTrialAlgorithmSpec": { "description": "The spec of multi-trial algorithms.", "$ref": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpec" } }, "id": "GoogleCloudAiplatformV1beta1NasJobSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1RetrieveProfilesResponse": { "id": "GoogleCloudAiplatformV1beta1RetrieveProfilesResponse", "type": "object", "description": "Response message for MemoryBankService.RetrieveProfiles.", "properties": { "profiles": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1MemoryProfile" }, "description": "The retrieved structured profiles, which match the schemas under the requested scope. The key is the ID of the schema that the profile is linked with, which corresponds to the `schema_id` defined inside the `SchemaConfig`, under `StructuredMemoryCustomizationConfig`." } } }, "GoogleCloudAiplatformV1beta1ListNotebookRuntimesResponse": { "id": "GoogleCloudAiplatformV1beta1ListNotebookRuntimesResponse", "type": "object", "description": "Response message for NotebookService.ListNotebookRuntimes.", "properties": { "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListNotebookRuntimesRequest.page_token to obtain that page.", "type": "string" }, "notebookRuntimes": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntime" }, "description": "List of NotebookRuntimes in the requested page." } } }, "GoogleCloudAiplatformV1beta1CreateModelMonitorOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateModelMonitorOperationMetadata", "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The operation generic information." } }, "description": "Runtime operation information for ModelMonitoringService.CreateModelMonitor." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs": { "properties": { "modelType": { "enum": [ "MODEL_TYPE_UNSPECIFIED", "CLOUD", "MOBILE_VERSATILE_1", "MOBILE_JETSON_VERSATILE_1", "MOBILE_CORAL_VERSATILE_1" ], "type": "string", "enumDescriptions": [ "Should not be set.", "A model best tailored to be used within Google Cloud, and which c annot be exported. Default.", "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards.", "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) to a Jetson device afterwards.", "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a Coral device afterwards." ] } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs", "type": "object" }, "GoogleCloudAiplatformV1beta1CustomCodeExecutionSpec": { "id": "GoogleCloudAiplatformV1beta1CustomCodeExecutionSpec", "type": "object", "properties": { "evaluationFunction": { "description": "Required. Python function. Expected user to define the following function, e.g.: def evaluate(instance: dict[str, Any]) -\u003e float: Please include this function signature in the code snippet. Instance is the evaluation instance, any fields populated in the instance are available to the function as instance[field_name]. Example: Example input: ``` instance= EvaluationInstance( response=EvaluationInstance.InstanceData(text=\"The answer is 4.\"), reference=EvaluationInstance.InstanceData(text=\"4\") ) ``` Example converted input: ``` { 'response': {'text': 'The answer is 4.'}, 'reference': {'text': '4'} } ``` Example python function: ``` def evaluate(instance: dict[str, Any]) -\u003e float: if instance'response' == instance'reference': return 1.0 return 0.0 ``` CustomCodeExecutionSpec is also supported in Batch Evaluation (EvalDataset RPC) and Tuning Evaluation. Each line in the input jsonl file will be converted to dict[str, Any] and passed to the evaluation function.", "type": "string" } }, "description": "Specificies a metric that is populated by evaluating user-defined Python code." }, "GoogleCloudAiplatformV1beta1DeployIndexRequest": { "id": "GoogleCloudAiplatformV1beta1DeployIndexRequest", "type": "object", "properties": { "deployedIndex": { "$ref": "GoogleCloudAiplatformV1beta1DeployedIndex", "description": "Required. The DeployedIndex to be created within the IndexEndpoint." } }, "description": "Request message for IndexEndpointService.DeployIndex." }, "GoogleCloudAiplatformV1beta1VeoTuningSpec": { "description": "Tuning Spec for Veo Model Tuning.", "properties": { "validationDatasetUri": { "description": "Optional. Validation dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset.", "type": "string" }, "hyperParameters": { "description": "Optional. Hyperparameters for Veo.", "$ref": "GoogleCloudAiplatformV1beta1VeoHyperParameters" }, "trainingDatasetUri": { "description": "Required. Training dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1VeoTuningSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1DistillationDataStats": { "id": "GoogleCloudAiplatformV1beta1DistillationDataStats", "type": "object", "description": "Statistics for distillation prompt dataset. These statistics do not include the responses sampled from the teacher model.", "properties": { "trainingDatasetStats": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1DatasetStats", "description": "Output only. Statistics computed for the training dataset." } } }, "GoogleCloudAiplatformV1beta1ListFeatureOnlineStoresResponse": { "properties": { "featureOnlineStores": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStore" }, "description": "The FeatureOnlineStores matching the request." }, "nextPageToken": { "description": "A token, which can be sent as ListFeatureOnlineStoresRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureOnlineStores.", "id": "GoogleCloudAiplatformV1beta1ListFeatureOnlineStoresResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1EmbedContentRequest": { "properties": { "outputDimensionality": { "format": "int32", "description": "Optional. Deprecated: Please use EmbedContentConfig.output_dimensionality instead. Reduced dimension for the output embedding. If set, excessive values in the output embedding are truncated from the end.", "deprecated": true, "type": "integer" }, "embedContentConfig": { "$ref": "GoogleCloudAiplatformV1beta1EmbedContentRequestEmbedContentConfig", "description": "Optional. Configuration for the EmbedContent request." }, "taskType": { "type": "string", "enumDescriptions": [ "Unset value, which will default to one of the other enum values.", "Specifies the given text is a query in a search/retrieval setting.", "Specifies the given text is a document from the corpus being searched.", "Specifies the given text will be used for STS.", "Specifies that the given text will be classified.", "Specifies that the embeddings will be used for clustering.", "Specifies that the embeddings will be used for question answering.", "Specifies that the embeddings will be used for fact verification.", "Specifies that the embeddings will be used for code retrieval." ], "deprecated": true, "description": "Optional. Deprecated: Please use EmbedContentConfig.task_type instead. The task type of the embedding.", "enum": [ "UNSPECIFIED", "RETRIEVAL_QUERY", "RETRIEVAL_DOCUMENT", "SEMANTIC_SIMILARITY", "CLASSIFICATION", "CLUSTERING", "QUESTION_ANSWERING", "FACT_VERIFICATION", "CODE_RETRIEVAL_QUERY" ] }, "title": { "deprecated": true, "type": "string", "description": "Optional. Deprecated: Please use EmbedContentConfig.title instead. The title for the text." }, "content": { "description": "Required. The content to be embedded.", "$ref": "GoogleCloudAiplatformV1beta1Content" }, "autoTruncate": { "description": "Optional. Deprecated: Please use EmbedContentConfig.auto_truncate instead. Whether to silently truncate the input content if it's longer than the maximum sequence length.", "type": "boolean", "deprecated": true } }, "description": "Request message for PredictionService.EmbedContent.", "id": "GoogleCloudAiplatformV1beta1EmbedContentRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceDataContents": { "id": "GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceDataContents", "type": "object", "description": "List of standard Content messages from Gemini API.", "properties": { "contents": { "description": "Optional. Repeated contents.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } } } }, "GoogleCloudAiplatformV1beta1Artifact": { "properties": { "displayName": { "description": "User provided display name of the Artifact. May be up to 128 Unicode characters.", "type": "string" }, "schemaVersion": { "description": "The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", "type": "string" }, "state": { "type": "string", "enumDescriptions": [ "Unspecified state for the Artifact.", "A state used by systems like Vertex AI Pipelines to indicate that the underlying data item represented by this Artifact is being created.", "A state indicating that the Artifact should exist, unless something external to the system deletes it." ], "description": "The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.", "enum": [ "STATE_UNSPECIFIED", "PENDING", "LIVE" ] }, "uri": { "description": "The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.", "type": "string" }, "etag": { "description": "An eTag used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this Artifact was created." }, "description": { "description": "Description of the Artifact", "type": "string" }, "labels": { "description": "The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).", "type": "object", "additionalProperties": { "type": "string" } }, "schemaTitle": { "description": "The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", "type": "string" }, "metadata": { "description": "Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "name": { "description": "Output only. The resource name of the Artifact.", "readOnly": true, "type": "string" }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this Artifact was last updated." } }, "description": "Instance of a general artifact.", "id": "GoogleCloudAiplatformV1beta1Artifact", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseInstance": { "description": "Spec for TrajectorySingleToolUse instance.", "properties": { "predictedTrajectory": { "description": "Required. Spec for predicted tool call trajectory.", "$ref": "GoogleCloudAiplatformV1beta1Trajectory" } }, "id": "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigTreeAHConfig": { "properties": { "leafNodeEmbeddingCount": { "type": "string", "format": "int64", "description": "Optional. Number of embeddings on each leaf node. The default value is 1000 if not set." } }, "description": "Configuration options for the tree-AH algorithm.", "id": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigTreeAHConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableBigtableMetadata": { "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableBigtableMetadata", "type": "object", "description": "Metadata of the Bigtable instance. This is used by direct read access to the Bigtable in tenant project.", "properties": { "tenantProjectId": { "description": "Tenant project ID.", "type": "string" }, "tableId": { "description": "The Cloud Bigtable table id.", "type": "string" }, "instanceId": { "description": "The Cloud Bigtable instance id.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SupervisedHyperParameters": { "id": "GoogleCloudAiplatformV1beta1SupervisedHyperParameters", "type": "object", "properties": { "learningRate": { "type": "number", "description": "Optional. Learning rate for tuning. Mutually exclusive with `learning_rate_multiplier`. This feature is only available for open source models.", "format": "double" }, "learningRateMultiplier": { "type": "number", "format": "double", "description": "Optional. Multiplier for adjusting the default learning rate. Mutually exclusive with `learning_rate`. This feature is only available for 1P models." }, "epochCount": { "description": "Optional. Number of complete passes the model makes over the entire training dataset during training.", "format": "int64", "type": "string" }, "adapterSize": { "enum": [ "ADAPTER_SIZE_UNSPECIFIED", "ADAPTER_SIZE_ONE", "ADAPTER_SIZE_TWO", "ADAPTER_SIZE_FOUR", "ADAPTER_SIZE_EIGHT", "ADAPTER_SIZE_SIXTEEN", "ADAPTER_SIZE_THIRTY_TWO" ], "description": "Optional. Adapter size for tuning.", "type": "string", "enumDescriptions": [ "Adapter size is unspecified.", "Adapter size 1.", "Adapter size 2.", "Adapter size 4.", "Adapter size 8.", "Adapter size 16.", "Adapter size 32." ] }, "batchSize": { "description": "Optional. Batch size for tuning. This feature is only available for open source models.", "format": "int64", "type": "string" } }, "description": "Hyperparameters for SFT." }, "GoogleCloudAiplatformV1beta1NotebookIdleShutdownConfig": { "id": "GoogleCloudAiplatformV1beta1NotebookIdleShutdownConfig", "type": "object", "properties": { "idleShutdownDisabled": { "description": "Whether Idle Shutdown is disabled in this NotebookRuntimeTemplate.", "type": "boolean" }, "idleTimeout": { "format": "google-duration", "description": "Required. Duration is accurate to the second. In Notebook, Idle Timeout is accurate to minute so the range of idle_timeout (second) is: 10 * 60 ~ 1440 * 60.", "type": "string" } }, "description": "The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field." }, "GoogleCloudAiplatformV1beta1StudySpecParameterSpecIntegerValueSpec": { "properties": { "defaultValue": { "format": "int64", "description": "A default value for an `INTEGER` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.", "type": "string" }, "minValue": { "type": "string", "format": "int64", "description": "Required. Inclusive minimum value of the parameter." }, "maxValue": { "type": "string", "format": "int64", "description": "Required. Inclusive maximum value of the parameter." } }, "description": "Value specification for a parameter in `INTEGER` type.", "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecIntegerValueSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1BigQueryDestination": { "properties": { "outputUri": { "description": "Required. BigQuery URI to a project or table, up to 2000 characters long. When only the project is specified, the Dataset and Table is created. When the full table reference is specified, the Dataset must exist and table must not exist. Accepted forms: * BigQuery path. For example: `bq://projectId` or `bq://projectId.bqDatasetId` or `bq://projectId.bqDatasetId.bqTableId`.", "type": "string" } }, "description": "The BigQuery location for the output content.", "id": "GoogleCloudAiplatformV1beta1BigQueryDestination", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecReferenceSentencePair": { "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecReferenceSentencePair", "type": "object", "properties": { "sourceSentence": { "description": "Source sentence in the sentence pair.", "type": "string" }, "targetSentence": { "description": "Target sentence in the sentence pair.", "type": "string" } }, "description": "A pair of sentences used as reference in source and target languages." }, "GoogleCloudAiplatformV1beta1PairwiseMetricInput": { "properties": { "instance": { "description": "Required. Pairwise metric instance.", "$ref": "GoogleCloudAiplatformV1beta1PairwiseMetricInstance" }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1PairwiseMetricSpec", "description": "Required. Spec for pairwise metric." } }, "description": "Input for pairwise metric.", "id": "GoogleCloudAiplatformV1beta1PairwiseMetricInput", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateSpecialistPoolOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateSpecialistPoolOperationMetadata", "type": "object", "description": "Runtime operation information for SpecialistPoolService.CreateSpecialistPool.", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchInstance": { "properties": { "predictedTrajectory": { "description": "Required. Spec for predicted tool call trajectory.", "$ref": "GoogleCloudAiplatformV1beta1Trajectory" }, "referenceTrajectory": { "description": "Required. Spec for reference tool call trajectory.", "$ref": "GoogleCloudAiplatformV1beta1Trajectory" } }, "description": "Spec for TrajectoryAnyOrderMatch instance.", "id": "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateSolverOperationMetadata": { "description": "Runtime operation information for SolverService.CreateSolver.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The generic operation information." } }, "id": "GoogleCloudAiplatformV1beta1CreateSolverOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1PSCAutomationConfig": { "id": "GoogleCloudAiplatformV1beta1PSCAutomationConfig", "type": "object", "description": "PSC config that is used to automatically create PSC endpoints in the user projects.", "properties": { "state": { "readOnly": true, "type": "string", "enumDescriptions": [ "Should not be used.", "The PSC service automation is successful.", "The PSC service automation has failed." ], "enum": [ "PSC_AUTOMATION_STATE_UNSPECIFIED", "PSC_AUTOMATION_STATE_SUCCESSFUL", "PSC_AUTOMATION_STATE_FAILED" ], "description": "Output only. The state of the PSC service automation." }, "projectId": { "description": "Required. Project id used to create forwarding rule.", "type": "string" }, "forwardingRule": { "description": "Output only. Forwarding rule created by the PSC service automation.", "readOnly": true, "type": "string" }, "errorMessage": { "description": "Output only. Error message if the PSC service automation failed.", "readOnly": true, "type": "string" }, "ipAddress": { "type": "string", "readOnly": true, "description": "Output only. IP address rule created by the PSC service automation." }, "network": { "description": "Required. The full name of the Google Compute Engine [network](https://cloud.google.com/compute/docs/networks-and-firewalls#networks). [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/get): `projects/{project}/global/networks/{network}`.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1CandidateResponse": { "description": "Responses from model or agent.", "properties": { "value": { "description": "Fields and values that can be used to populate the response template.", "type": "any" }, "text": { "description": "Text response.", "type": "string" }, "agentData": { "$ref": "GoogleCloudAiplatformV1beta1AgentData", "description": "Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This field is used to provide the full output of an agent's run, including all turns and events, for direct evaluation." }, "events": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "description": "Optional. Intermediate events (such as tool calls and responses) that led to the final response." }, "error": { "description": "Output only. Error while scraping model or agent.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "candidate": { "description": "Required. The name of the candidate that produced the response.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1CandidateResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ReportExecutionEventRequest": { "properties": { "vmToken": { "description": "Required. The VM identity token (a JWT) for authenticating the VM. https://cloud.google.com/compute/docs/instances/verifying-instance-identity", "type": "string" }, "eventType": { "type": "string", "enumDescriptions": [ "Unspecified.", "Notebook execution process has started. Expect this message within expected time to provision compute.", "Notebook execution process is completed. Expect this message within timeout.", "Notebook execution process has failed. Expect this message within timeout." ], "enum": [ "EVENT_TYPE_UNSPECIFIED", "ACTIVE", "DONE", "FAILED" ], "description": "Required. The type of the event." }, "status": { "$ref": "GoogleRpcStatus", "description": "Optional. The error details of the event." } }, "description": "Request message for NotebookInternalService.ReportExecutionEvent.", "id": "GoogleCloudAiplatformV1beta1ReportExecutionEventRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1UndeploySolverOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The generic operation information." } }, "description": "Runtime operation information for SolverService.UndeploySolver.", "id": "GoogleCloudAiplatformV1beta1UndeploySolverOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplateRef": { "id": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplateRef", "type": "object", "description": "Points to a NotebookRuntimeTemplateRef.", "properties": { "notebookRuntimeTemplate": { "description": "Immutable. A resource name of the NotebookRuntimeTemplate.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SafetyInput": { "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1SafetySpec", "description": "Required. Spec for safety metric." }, "instance": { "description": "Required. Safety instance.", "$ref": "GoogleCloudAiplatformV1beta1SafetyInstance" } }, "description": "Input for safety metric.", "id": "GoogleCloudAiplatformV1beta1SafetyInput", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest": { "id": "GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest", "type": "object", "properties": { "vmToken": { "description": "Required. The VM identity token (a JWT) for authenticating the VM. https://cloud.google.com/compute/docs/instances/verifying-instance-identity", "type": "string" } }, "description": "Request message for NotebookInternalService.GenerateAccessToken." }, "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigSessionInput": { "id": "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigSessionInput", "type": "object", "properties": { "parameters": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. Additional parameters for the session, like app_name, etc. For example, {\"app_name\": \"my-app\"}." }, "userId": { "description": "Optional. The user id for the agent session. The ID can be up to 128 characters long.", "type": "string" }, "sessionState": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. Session specific memory which stores key conversation points." } }, "description": "Session input to run an Agent." }, "GoogleCloudAiplatformV1beta1ListNotebookExecutionJobsResponse": { "id": "GoogleCloudAiplatformV1beta1ListNotebookExecutionJobsResponse", "type": "object", "properties": { "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListNotebookExecutionJobsRequest.page_token to obtain that page.", "type": "string" }, "notebookExecutionJobs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJob" }, "description": "List of NotebookExecutionJobs in the requested page." } }, "description": "Response message for [NotebookService.CreateNotebookExecutionJob]" }, "GoogleCloudAiplatformV1beta1ReservationAffinity": { "id": "GoogleCloudAiplatformV1beta1ReservationAffinity", "type": "object", "description": "A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity.", "properties": { "key": { "description": "Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.", "type": "string" }, "reservationAffinityType": { "enum": [ "TYPE_UNSPECIFIED", "NO_RESERVATION", "ANY_RESERVATION", "SPECIFIC_RESERVATION" ], "description": "Required. Specifies the reservation affinity type.", "type": "string", "enumDescriptions": [ "Default value. This should not be used.", "Do not consume from any reserved capacity, only use on-demand.", "Consume any reservation available, falling back to on-demand.", "Consume from a specific reservation. When chosen, the reservation must be identified via the `key` and `values` fields." ] }, "values": { "description": "Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation or reservation block.", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1MultiSpeakerVoiceConfig": { "id": "GoogleCloudAiplatformV1beta1MultiSpeakerVoiceConfig", "type": "object", "properties": { "speakerVoiceConfigs": { "description": "Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SpeakerVoiceConfig" } } }, "description": "Configuration for a multi-speaker text-to-speech request." }, "GoogleCloudAiplatformV1beta1UploadModelOperationMetadata": { "description": "Details of ModelService.UploadModel operation.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The common part of the operation metadata." } }, "id": "GoogleCloudAiplatformV1beta1UploadModelOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryRecallSpec": { "id": "GoogleCloudAiplatformV1beta1TrajectoryRecallSpec", "type": "object", "description": "Spec for TrajectoryRecall metric - returns a float score based on average recall of individual tool calls.", "properties": {} }, "GoogleCloudAiplatformV1beta1ExpressProject": { "id": "GoogleCloudAiplatformV1beta1ExpressProject", "type": "object", "properties": { "region": { "type": "string", "readOnly": true, "description": "Output only. The region of the project." }, "createTime": { "format": "google-datetime", "description": "Output only. The time the project was created.", "readOnly": true, "type": "string" }, "defaultApiKey": { "type": "string", "readOnly": true, "description": "Output only. The default API key string of the project." }, "projectNumber": { "description": "Output only. The number of the project.", "format": "int64", "type": "string", "readOnly": true }, "projectId": { "type": "string", "readOnly": true, "description": "Output only. The ID of the project." } }, "description": "The project for Vertex AI Express Mode." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputs": { "properties": { "optimizationObjectiveRecallValue": { "type": "number", "format": "float", "description": "Required when optimization_objective is \"maximize-precision-at-recall\". Must be between 0 and 1, inclusive." }, "predictionType": { "description": "The type of prediction the Model is to produce. \"classification\" - Predict one out of multiple target values is picked for each row. \"regression\" - Predict a value based on its relation to other values. This type is available only to columns that contain semantically numeric values, i.e. integers or floating point number, even if stored as e.g. strings.", "type": "string" }, "exportEvaluatedDataItemsConfig": { "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig" }, "additionalExperiments": { "type": "array", "items": { "type": "string" }, "description": "Additional experiment flags for the Tables training pipeline." }, "targetColumn": { "description": "The column name of the target column that the model is to predict.", "type": "string" }, "optimizationObjective": { "description": "Objective function the model is optimizing towards. The training process creates a model that maximizes/minimizes the value of the objective function over the validation set. The supported optimization objectives depend on the prediction type. If the field is not set, a default objective function is used. classification (binary): \"maximize-au-roc\" (default) - Maximize the area under the receiver operating characteristic (ROC) curve. \"minimize-log-loss\" - Minimize log loss. \"maximize-au-prc\" - Maximize the area under the precision-recall curve. \"maximize-precision-at-recall\" - Maximize precision for a specified recall value. \"maximize-recall-at-precision\" - Maximize recall for a specified precision value. classification (multi-class): \"minimize-log-loss\" (default) - Minimize log loss. regression: \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). \"minimize-mae\" - Minimize mean-absolute error (MAE). \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE).", "type": "string" }, "disableEarlyStopping": { "description": "Use the entire training budget. This disables the early stopping feature. By default, the early stopping feature is enabled, which means that AutoML Tables might stop training before the entire training budget has been used.", "type": "boolean" }, "trainBudgetMilliNodeHours": { "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive.", "format": "int64", "type": "string" }, "weightColumnName": { "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1.", "type": "string" }, "optimizationObjectivePrecisionValue": { "type": "number", "format": "float", "description": "Required when optimization_objective is \"maximize-recall-at-precision\". Must be between 0 and 1, inclusive." }, "transformations": { "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation" } } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputs", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetrics", "type": "object", "description": "Metrics for text extraction evaluation results.", "properties": { "confusionMatrix": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix", "description": "Confusion matrix of the evaluation. Only set for Models where number of AnnotationSpecs is no more than 10. Only set for ModelEvaluations, not for ModelEvaluationSlices." }, "confidenceMetrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics" }, "description": "Metrics that have confidence thresholds. Precision-recall curve can be derived from them." } } }, "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesRequest": { "properties": { "requests": { "description": "Required. The request message specifying the TensorboardTimeSeries to create. A maximum of 1000 TensorboardTimeSeries can be created in a batch.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1CreateTensorboardTimeSeriesRequest" } } }, "description": "Request message for TensorboardService.BatchCreateTensorboardTimeSeries.", "id": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1AugmentPromptRequest": { "description": "Request message for AugmentPrompt.", "properties": { "model": { "$ref": "GoogleCloudAiplatformV1beta1AugmentPromptRequestModel", "description": "Optional. Metadata of the backend deployed model." }, "vertexRagStore": { "$ref": "GoogleCloudAiplatformV1beta1VertexRagStore", "description": "Optional. Retrieves contexts from the Vertex RagStore." }, "contents": { "description": "Optional. Input content to augment, only text format is supported for now.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } } }, "id": "GoogleCloudAiplatformV1beta1AugmentPromptRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelContainerSpec": { "id": "GoogleCloudAiplatformV1beta1ModelContainerSpec", "type": "object", "properties": { "imageUri": { "description": "Required. Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.", "type": "string" }, "deploymentTimeout": { "description": "Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.", "format": "google-duration", "type": "string" }, "invokeRoutePrefix": { "description": "Immutable. Invoke route prefix for the custom container. \"/*\" is the only supported value right now. By setting this field, any non-root route on this model will be accessible with invoke http call eg: \"/invoke/foo/bar\", however the [PredictionService.Invoke] RPC is not supported yet. Only one of `predict_route` or `invoke_route_prefix` can be set, and we default to using `predict_route` if this field is not set. If this field is set, the Model can only be deployed to dedicated endpoint.", "type": "string" }, "healthProbe": { "$ref": "GoogleCloudAiplatformV1beta1Probe", "description": "Immutable. Specification for Kubernetes readiness probe." }, "env": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EnvVar" }, "description": "Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ```json [ { \"name\": \"VAR_1\", \"value\": \"foo\" }, { \"name\": \"VAR_2\", \"value\": \"$(VAR_1) bar\" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core)." }, "grpcPorts": { "description": "Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Port" } }, "args": { "description": "Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s \"default parameters\" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).", "type": "array", "items": { "type": "string" } }, "ports": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Port" }, "description": "Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: ```json [ { \"containerPort\": 8080 } ] ``` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core)." }, "healthRoute": { "description": "Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)", "type": "string" }, "sharedMemorySizeMb": { "type": "string", "format": "int64", "description": "Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes." }, "command": { "description": "Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s \"exec\" form, not its \"shell\" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).", "type": "array", "items": { "type": "string" } }, "startupProbe": { "description": "Immutable. Specification for Kubernetes startup probe.", "$ref": "GoogleCloudAiplatformV1beta1Probe" }, "livenessProbe": { "$ref": "GoogleCloudAiplatformV1beta1Probe", "description": "Immutable. Specification for Kubernetes liveness probe." }, "predictRoute": { "description": "Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)", "type": "string" } }, "description": "Specification of a container for serving predictions. Some fields in this message correspond to fields in the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core)." }, "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestEntityTypeSpec": { "id": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestEntityTypeSpec", "type": "object", "description": "Selects Features of an EntityType to read values of and specifies read settings.", "properties": { "settings": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DestinationFeatureSetting" }, "description": "Per-Feature settings for the batch read." }, "entityTypeId": { "description": "Required. ID of the EntityType to select Features. The EntityType id is the entity_type_id specified during EntityType creation.", "type": "string" }, "featureSelector": { "$ref": "GoogleCloudAiplatformV1beta1FeatureSelector", "description": "Required. Selectors choosing which Feature values to read from the EntityType." } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation", "type": "object", "properties": { "columnName": { "type": "string" } }, "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding." }, "GoogleCloudAiplatformV1beta1PersistentDiskSpec": { "id": "GoogleCloudAiplatformV1beta1PersistentDiskSpec", "type": "object", "properties": { "diskType": { "description": "Type of the disk (default is \"pd-standard\"). Valid values: \"pd-ssd\" (Persistent Disk Solid State Drive) \"pd-standard\" (Persistent Disk Hard Disk Drive) \"pd-balanced\" (Balanced Persistent Disk) \"pd-extreme\" (Extreme Persistent Disk)", "type": "string" }, "diskSizeGb": { "format": "int64", "description": "Size in GB of the disk (default is 100GB).", "type": "string" } }, "description": "Represents the spec of persistent disk options." }, "GoogleCloudAiplatformV1beta1SchemaTextExtractionAnnotation": { "properties": { "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "textSegment": { "description": "The segment of the text content.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTextSegment" }, "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" } }, "description": "Annotation details specific to text extraction.", "id": "GoogleCloudAiplatformV1beta1SchemaTextExtractionAnnotation", "type": "object" }, "GoogleCloudAiplatformV1beta1PublisherModelResourceReference": { "description": "Reference to a resource.", "properties": { "useCase": { "type": "string", "deprecated": true, "description": "Use case (CUJ) of the resource." }, "uri": { "description": "The URI of the resource.", "type": "string" }, "resourceName": { "description": "The resource name of the Google Cloud resource.", "type": "string" }, "description": { "deprecated": true, "type": "string", "description": "Description of the resource." } }, "id": "GoogleCloudAiplatformV1beta1PublisherModelResourceReference", "type": "object" }, "GoogleCloudAiplatformV1beta1ProbeTcpSocketAction": { "id": "GoogleCloudAiplatformV1beta1ProbeTcpSocketAction", "type": "object", "description": "TcpSocketAction probes the health of a container by opening a TCP socket connection.", "properties": { "port": { "type": "integer", "description": "Number of the port to access on the container. Number must be in the range 1 to 65535.", "format": "int32" }, "host": { "description": "Optional: Host name to connect to, defaults to the model serving container's IP.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ToolCallValidSpec": { "id": "GoogleCloudAiplatformV1beta1ToolCallValidSpec", "type": "object", "description": "Spec for tool call valid metric.", "properties": {} }, "GoogleCloudAiplatformV1beta1SchemaImageDataItem": { "id": "GoogleCloudAiplatformV1beta1SchemaImageDataItem", "type": "object", "description": "Payload of Image DataItem.", "properties": { "gcsUri": { "description": "Required. Google Cloud Storage URI points to the original image in user's bucket. The image is up to 30MB in size.", "type": "string" }, "mimeType": { "description": "Output only. The mime type of the content of the image. Only the images in below listed mime types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon", "readOnly": true, "type": "string" } } }, "GoogleCloudAiplatformV1beta1SandboxEnvironment": { "id": "GoogleCloudAiplatformV1beta1SandboxEnvironment", "type": "object", "properties": { "sandboxEnvironmentTemplate": { "description": "Optional. The name of the SandboxEnvironmentTemplate specified in the parent Agent Engine resource that this SandboxEnvironment is created from. Only one of `sandbox_environment_template` and `spec` should be set.", "type": "string" }, "updateTime": { "description": "Output only. The timestamp when this SandboxEnvironment was most recently updated.", "format": "google-datetime", "type": "string", "readOnly": true }, "latestSandboxEnvironmentSnapshot": { "readOnly": true, "type": "string", "description": "Output only. The resource name of the latest snapshot taken for this SandboxEnvironment." }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. The timestamp when this SandboxEnvironment was created.", "format": "google-datetime" }, "owner": { "description": "Optional. Owner information for this sandbox environment. A Sandbox can only be restored from a snapshot that belongs to the same owner. If not set, sandbox will be created as the default owner.", "type": "string" }, "ttl": { "description": "Optional. Input only. The TTL for the sandbox environment. The expiration time is computed: now + TTL.", "format": "google-duration", "type": "string" }, "name": { "description": "Identifier. The name of the SandboxEnvironment.", "type": "string" }, "connectionInfo": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentConnectionInfo", "description": "Output only. The connection information of the SandboxEnvironment." }, "spec": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSpec", "description": "Optional. The configuration of the SandboxEnvironment." }, "state": { "enum": [ "STATE_UNSPECIFIED", "STATE_PROVISIONING", "STATE_RUNNING", "STATE_DEPROVISIONING", "STATE_TERMINATED", "STATE_DELETED" ], "description": "Output only. The runtime state of the SandboxEnvironment.", "readOnly": true, "type": "string", "enumDescriptions": [ "The default value. This value is unused.", "Runtime resources are being allocated for the sandbox environment.", "Sandbox runtime is ready for serving.", "Sandbox runtime is halted, performing tear down tasks.", "Sandbox has terminated with underlying runtime failure.", "Sandbox runtime has been deleted." ] }, "expireTime": { "format": "google-datetime", "description": "Optional. Timestamp in UTC of when this SandboxEnvironment is considered expired. This is *always* provided on output, regardless of what `expiration` was sent on input.", "type": "string" }, "displayName": { "description": "Required. The display name of the SandboxEnvironment.", "type": "string" }, "sandboxEnvironmentSnapshot": { "description": "Optional. The resource name of the SandboxEnvironmentSnapshot to use for creating this SandboxEnvironment. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentSnapshots/{sandbox_environment_snapshot}`", "type": "string" } }, "description": "SandboxEnvironment is a containerized environment that provides a customizable secure execution runtime for AI agents." }, "GoogleCloudAiplatformV1beta1SchemaVideoClassificationAnnotation": { "properties": { "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "timeSegment": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTimeSegment", "description": "This Annotation applies to the time period represented by the TimeSegment. If it's not set, the Annotation applies to the whole video." }, "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" } }, "description": "Annotation details specific to video classification.", "id": "GoogleCloudAiplatformV1beta1SchemaVideoClassificationAnnotation", "type": "object" }, "GoogleCloudAiplatformV1beta1ListFeatureGroupsResponse": { "id": "GoogleCloudAiplatformV1beta1ListFeatureGroupsResponse", "type": "object", "properties": { "featureGroups": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureGroup" }, "description": "The FeatureGroups matching the request." }, "nextPageToken": { "description": "A token, which can be sent as ListFeatureGroupsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "description": "Response message for FeatureRegistryService.ListFeatureGroups." }, "GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation": { "id": "GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation", "type": "object", "properties": { "explanations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Explanation" }, "description": "The explanations of the Model's PredictResponse.predictions. It has the same number of elements as instances to be explained." } }, "description": "This message is a wrapper grouping Concurrent Explanations." }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter": { "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter", "type": "object", "properties": { "vectorSimilarityThreshold": { "format": "double", "description": "Optional. Only returns contexts with vector similarity larger than the threshold.", "type": "number" }, "metadataFilter": { "description": "Optional. String for metadata filtering.", "type": "string" }, "vectorDistanceThreshold": { "format": "double", "description": "Optional. Only returns contexts with vector distance smaller than the threshold.", "type": "number" } }, "description": "Config for filters." }, "GoogleCloudAiplatformV1beta1ApiAuth": { "id": "GoogleCloudAiplatformV1beta1ApiAuth", "type": "object", "description": "The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead.", "properties": { "apiKeyConfig": { "$ref": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig", "description": "The API secret." } } }, "GoogleCloudAiplatformV1beta1FetchExamplesResponse": { "id": "GoogleCloudAiplatformV1beta1FetchExamplesResponse", "type": "object", "properties": { "nextPageToken": { "description": "A token, which can be sent as FetchExamplesRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages.", "type": "string" }, "examples": { "description": "The examples in the Example Store that satisfy the metadata filters.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Example" } } }, "description": "Response message for ExampleStoreService.FetchExamples." }, "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoActionRecognitionPredictionInstance": { "properties": { "timeSegmentStart": { "description": "The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision.", "type": "string" }, "content": { "description": "The Google Cloud Storage location of the video on which to perform the prediction.", "type": "string" }, "mimeType": { "description": "The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime", "type": "string" }, "timeSegmentEnd": { "description": "The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision, and \"inf\" or \"Infinity\" is allowed, which means the end of the video.", "type": "string" } }, "description": "Prediction input format for Video Action Recognition.", "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoActionRecognitionPredictionInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateTensorboardOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1UpdateTensorboardOperationMetadata", "type": "object", "description": "Details of operations that perform update Tensorboard.", "properties": { "genericMetadata": { "description": "Operation metadata for Tensorboard.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1beta1TrialContext": { "id": "GoogleCloudAiplatformV1beta1TrialContext", "type": "object", "properties": { "description": { "description": "A human-readable field which can store a description of this context. This will become part of the resulting Trial's description field.", "type": "string" }, "parameters": { "description": "If/when a Trial is generated or selected from this Context, its Parameters will match any parameters specified here. (I.e. if this context specifies parameter name:'a' int_value:3, then a resulting Trial will have int_value:3 for its parameter named 'a'.) Note that we first attempt to match existing REQUESTED Trials with contexts, and if there are no matches, we generate suggestions in the subspace defined by the parameters specified here. NOTE: a Context without any Parameters matches the entire feasible search space.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrialParameter" } } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter": { "properties": { "studySpec": { "$ref": "GoogleCloudAiplatformV1beta1StudySpec", "description": "Optioinal. StudySpec of hyperparameter tuning job. Required for `model_garden_trainer`." }, "trainerConfig": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Customizable trainer settings, used in the `model_garden_trainer`." }, "datasetConfig": { "description": "Customizable dataset settings, used in the `model_garden_trainer`.", "type": "object", "additionalProperties": { "type": "string" } }, "trainerType": { "type": "string", "enumDescriptions": [ "Default value.", "", "" ], "enum": [ "TRAINER_TYPE_UNSPECIFIED", "AUTOML_TRAINER", "MODEL_GARDEN_TRAINER" ] }, "checkpointName": { "description": "Optional. An unique name of pretrained model checkpoint provided in model garden, it will be mapped to a GCS location internally.", "type": "string" } }, "description": "A wrapper class which contains the tunable parameters in an AutoML Image training job.", "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter", "type": "object" }, "CloudAiLargeModelsVisionGenerateVideoExperiments": { "id": "CloudAiLargeModelsVisionGenerateVideoExperiments", "type": "object", "description": "Experimental parameters for video generation.", "properties": { "modelName": { "description": "Model names, as defined in: xyz ", "type": "string" }, "numDiffusionSteps": { "format": "int32", "description": "Number of diffusion steps", "type": "integer" }, "humanPose": { "$ref": "CloudAiLargeModelsVisionHumanPose", "description": "Human pose parameters for Pose Control" }, "promptInputs": { "$ref": "CloudAiLargeModelsVisionPromptInputs", "description": "Prompt chunks for \"ProModel\" prompting. If set, the prompt will not be rewritten, and top-level prompt ignored." }, "videoTransformMaskGcsUri": { "description": "GCS URI of the grayscale video mask for Differential Diffusion. Maps to sdedit_video_tmax_scale_map ", "type": "string" }, "conditioningFrames": { "description": "Conditioning frames for veo experimental models ONLY, not to be confused with keyframes (ID:31) in GenerateVideoRequest.", "type": "array", "items": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsConditioningFrame" } }, "videoTransformStrength": { "type": "number", "description": "SDEdit: Scalar noise level (0.0 to 1.0) Maps to sdedit_tmax ", "format": "float" }, "requestOriginTag": { "description": "Optional tag for tracking the source of this request. Allowed values: \"colab\", \"comfyui\", \"curl\", \"flowresearch\", \"vertexstudio\". Unrecognized tags are recorded as \"unknown\" in metrics. Tags do not affect video generation behavior. Up to 16 characters, ASCII alphanumeric, hyphens, and underscores only.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1CacheConfig": { "id": "GoogleCloudAiplatformV1beta1CacheConfig", "type": "object", "description": "Config of GenAI caching features. This is a singleton resource.", "properties": { "name": { "description": "Identifier. Name of the cache config. Format: - `projects/{project}/cacheConfig`.", "type": "string" }, "disableCache": { "description": "If set to true, disables GenAI caching. Otherwise caching is enabled.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1LossTaxonomyEntry": { "id": "GoogleCloudAiplatformV1beta1LossTaxonomyEntry", "type": "object", "properties": { "l1Category": { "description": "The primary category of the loss (e.g., \"Hallucination\", \"Tool Calling\"). This field is typically required.", "type": "string" }, "l2Category": { "description": "The secondary category of the loss (e.g., \"Hallucination of Action\", \"Incorrect Tool Selection\").", "type": "string" }, "description": { "description": "A detailed description of this loss pattern. Example: \"The agent verbally confirms an action without executing the tool.\"", "type": "string" } }, "description": "Defines a specific entry in the loss pattern taxonomy." }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationSentenceFileInput": { "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationSentenceFileInput", "type": "object", "properties": { "fileInputSource": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationFileInputSource", "description": "Inlined file source." }, "gcsInputSource": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationGcsInputSource", "description": "Cloud Storage file source." } } }, "GoogleCloudAiplatformV1beta1GroundingChunkMaps": { "properties": { "uri": { "description": "The URI of the place.", "type": "string" }, "route": { "description": "Output only. Route information.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMapsRoute" }, "text": { "description": "The text of the place answer.", "type": "string" }, "title": { "description": "The title of the place.", "type": "string" }, "placeAnswerSources": { "description": "The sources that were used to generate the place answer. This includes review snippets and photos that were used to generate the answer, as well as URIs to flag content.", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSources" }, "placeId": { "description": "This Place's resource name, in `places/{place_id}` format. This can be used to look up the place in the Google Maps API.", "type": "string" } }, "description": "A `Maps` chunk is a piece of evidence that comes from Google Maps, containing information about places or routes. This is used to provide the user with rich, location-based information.", "id": "GoogleCloudAiplatformV1beta1GroundingChunkMaps", "type": "object" }, "GoogleCloudAiplatformV1beta1ListEvaluationRunsResponse": { "id": "GoogleCloudAiplatformV1beta1ListEvaluationRunsResponse", "type": "object", "description": "Response message for EvaluationManagementService.ListEvaluationRuns.", "properties": { "evaluationRuns": { "description": "List of EvaluationRuns in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRun" } }, "nextPageToken": { "description": "A token to retrieve the next page of results.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1MetadataStore": { "properties": { "name": { "readOnly": true, "type": "string", "description": "Output only. The resource name of the MetadataStore instance." }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this MetadataStore was last updated.", "format": "google-datetime" }, "state": { "description": "Output only. State information of the MetadataStore.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1MetadataStoreMetadataStoreState" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this MetadataStore was created." }, "description": { "description": "Description of the MetadataStore.", "type": "string" }, "dataplexConfig": { "description": "Optional. Dataplex integration settings.", "$ref": "GoogleCloudAiplatformV1beta1MetadataStoreDataplexConfig" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key spec for a Metadata Store. If set, this Metadata Store and all sub-resources of this Metadata Store are secured using this key." } }, "description": "Instance of a metadata store. Contains a set of metadata that can be queried.", "id": "GoogleCloudAiplatformV1beta1MetadataStore", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionRecognitionMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionRecognitionMetrics", "type": "object", "properties": { "evaluatedActionCount": { "type": "integer", "format": "int32", "description": "The number of ground truth actions used to create this evaluation." }, "videoActionMetrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetrics" }, "description": "The metric entries for precision window lengths: 1s,2s,3s." } }, "description": "Model evaluation metrics for video action recognition." }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef", "type": "object", "properties": { "id": { "description": "ID of the AnnotationSpec.", "type": "string" }, "displayName": { "description": "Display name of the AnnotationSpec.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigPromptTemplate": { "id": "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigPromptTemplate", "type": "object", "description": "Prompt template used for inference.", "properties": { "gcsUri": { "description": "Prompt template stored in Cloud Storage. Format: \"gs://my-bucket/file-name.txt\".", "type": "string" }, "promptTemplate": { "description": "Inline prompt template. Template variables should be in the format \"{var_name}\". Example: \"Translate the following from {source_lang} to {target_lang}: {text}\"", "type": "string" } } }, "GoogleCloudAiplatformV1beta1CreateIndexOperationMetadata": { "properties": { "nearestNeighborSearchOperationMetadata": { "description": "The operation metadata with regard to Matching Engine Index operation.", "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadata" }, "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The operation generic information." } }, "description": "Runtime operation information for IndexService.CreateIndex.", "id": "GoogleCloudAiplatformV1beta1CreateIndexOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadata": { "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadata", "type": "object", "description": "Metadata of the input of a feature. Fields other than InputMetadata.input_baselines are applicable only for Models that are using Vertex AI-provided images for Tensorflow.", "properties": { "inputTensorName": { "description": "Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow.", "type": "string" }, "modality": { "description": "Modality of the feature. Valid values are: numeric, image. Defaults to numeric.", "type": "string" }, "groupName": { "description": "Name of the group that the input belongs to. Features with the same group name will be treated as one feature when computing attributions. Features grouped together can have different shapes in value. If provided, there will be one single attribution generated in Attribution.feature_attributions, keyed by the group name.", "type": "string" }, "featureValueDomain": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataFeatureValueDomain", "description": "The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized." }, "inputBaselines": { "type": "array", "items": { "type": "any" }, "description": "Baseline inputs for this feature. If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions. For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor. For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri." }, "encoding": { "type": "string", "enumDescriptions": [ "Default value. This is the same as IDENTITY.", "The tensor represents one feature.", "The tensor represents a bag of features where each index maps to a feature. InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [27, 6.0, 150] index_feature_mapping = [\"age\", \"height\", \"weight\"] ```", "The tensor represents a bag of features where each index maps to a feature. Zero values in the tensor indicates feature being non-existent. InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [2, 0, 5, 0, 1] index_feature_mapping = [\"a\", \"b\", \"c\", \"d\", \"e\"] ```", "The tensor is a list of binaries representing whether a feature exists or not (1 indicates existence). InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [1, 0, 1, 0, 1] index_feature_mapping = [\"a\", \"b\", \"c\", \"d\", \"e\"] ```", "The tensor is encoded into a 1-dimensional array represented by an encoded tensor. InputMetadata.encoded_tensor_name must be provided for this encoding. For example: ``` input = [\"This\", \"is\", \"a\", \"test\", \".\"] encoded = [0.1, 0.2, 0.3, 0.4, 0.5] ```", "Select this encoding when the input tensor is encoded into a 2-dimensional array represented by an encoded tensor. InputMetadata.encoded_tensor_name must be provided for this encoding. The first dimension of the encoded tensor's shape is the same as the input tensor's shape. For example: ``` input = [\"This\", \"is\", \"a\", \"test\", \".\"] encoded = [[0.1, 0.2, 0.3, 0.4, 0.5], [0.2, 0.1, 0.4, 0.3, 0.5], [0.5, 0.1, 0.3, 0.5, 0.4], [0.5, 0.3, 0.1, 0.2, 0.4], [0.4, 0.3, 0.2, 0.5, 0.1]] ```" ], "enum": [ "ENCODING_UNSPECIFIED", "IDENTITY", "BAG_OF_FEATURES", "BAG_OF_FEATURES_SPARSE", "INDICATOR", "COMBINED_EMBEDDING", "CONCAT_EMBEDDING" ], "description": "Defines how the feature is encoded into the input tensor. Defaults to IDENTITY." }, "denseShapeTensorName": { "description": "Specifies the shape of the values of the input if the input is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.", "type": "string" }, "encodedBaselines": { "description": "A list of baselines for the encoded tensor. The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.", "type": "array", "items": { "type": "any" } }, "indexFeatureMapping": { "type": "array", "items": { "type": "string" }, "description": "A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR." }, "visualization": { "description": "Visualization configurations for image explanation.", "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataVisualization" }, "indicesTensorName": { "description": "Specifies the index of the values of the input tensor. Required when the input tensor is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.", "type": "string" }, "encodedTensorName": { "description": "Encoded tensor is a transformation of the input tensor. Must be provided if choosing Integrated Gradients attribution or XRAI attribution and the input tensor is not differentiable. An encoded tensor is generated if the input tensor is encoded by a lookup table.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse": { "id": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse", "type": "object", "description": "Response message for FeatureOnlineStoreService.FetchFeatureValues", "properties": { "protoStruct": { "description": "Feature values in proto Struct format.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "keyValues": { "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairList", "description": "Feature values in KeyValue format." }, "dataKey": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKey", "description": "The data key associated with this response. Will only be populated for FeatureOnlineStoreService.StreamingFetchFeatureValues RPCs." } } }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentSpecComputerUseEnvironment": { "properties": {}, "description": "The computer use environment with customized settings.", "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSpecComputerUseEnvironment", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputInfo": { "id": "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputInfo", "type": "object", "description": "Further describes this job's output. Supplements output_config.", "properties": { "gcsOutputDirectory": { "type": "string", "readOnly": true, "description": "Output only. The full path of the Cloud Storage directory created, into which the prediction output is written." }, "bigqueryOutputTable": { "description": "Output only. The name of the BigQuery table created, in `predictions_` format, into which the prediction output is written. Can be used by UI to generate the BigQuery output path, for example.", "type": "string", "readOnly": true }, "bigqueryOutputDataset": { "description": "Output only. The path of the BigQuery dataset created, in `bq://projectId.bqDatasetId` format, into which the prediction output is written.", "readOnly": true, "type": "string" }, "vertexMultimodalDatasetName": { "description": "Output only. The resource name of the Vertex Managed Dataset created, into which the prediction output is written. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "readOnly": true, "type": "string" } } }, "GoogleCloudAiplatformV1beta1DeleteReasoningEngineRuntimeRevisionOperationMetadata": { "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Metadata associated with DeleteReasoningEngineRuntimeRevision operation.", "id": "GoogleCloudAiplatformV1beta1DeleteReasoningEngineRuntimeRevisionOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1TunedModel": { "description": "The Model Registry Model and Online Prediction Endpoint associated with this TuningJob.", "properties": { "model": { "description": "Output only. The resource name of the TunedModel. Format: `projects/{project}/locations/{location}/models/{model}@{version_id}` When tuning from a base model, the version ID will be 1. For continuous tuning, if the provided tuned_model_display_name is set and different from parent model's display name, the tuned model will have a new parent model with version 1. Otherwise the version id will be incremented by 1 from the last version ID in the parent model. E.g., `projects/{project}/locations/{location}/models/{model}@{last_version_id + 1}`", "type": "string", "readOnly": true }, "checkpoints": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TunedModelCheckpoint" }, "readOnly": true, "description": "Output only. The checkpoints associated with this TunedModel. This field is only populated for tuning jobs that enable intermediate checkpoints." }, "endpoint": { "type": "string", "readOnly": true, "description": "Output only. A resource name of an Endpoint. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`." } }, "id": "GoogleCloudAiplatformV1beta1TunedModel", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPromptApiSchema": { "properties": { "translationPrompt": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationPrompt", "description": "The prompt variation for Translation use case." }, "apiSchemaVersion": { "description": "The Schema version that represents changes to the API behavior.", "type": "string" }, "multimodalPrompt": { "description": "Multimodal prompt which embeds preambles to prompt string.", "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecMultimodalPrompt" }, "structuredPrompt": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecStructuredPrompt", "description": "The prompt variation that stores preambles in separate fields." }, "executions": { "description": "A list of execution instances for constructing a ready-to-use prompt.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptInstancePromptExecution" } } }, "description": "The A2 schema of a prompt.", "id": "GoogleCloudAiplatformV1beta1SchemaPromptApiSchema", "type": "object" }, "GoogleCloudAiplatformV1beta1LookupStudyRequest": { "properties": { "displayName": { "description": "Required. The user-defined display name of the Study", "type": "string" } }, "description": "Request message for VizierService.LookupStudy.", "id": "GoogleCloudAiplatformV1beta1LookupStudyRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1Fact": { "id": "GoogleCloudAiplatformV1beta1Fact", "type": "object", "description": "The fact used in grounding.", "properties": { "uri": { "description": "If present, this uri links to the source of the fact.", "type": "string" }, "vectorDistance": { "deprecated": true, "type": "number", "format": "double", "description": "If present, the distance between the query vector and this fact vector." }, "title": { "description": "If present, it refers to the title of this fact.", "type": "string" }, "query": { "description": "Query that is used to retrieve this fact.", "type": "string" }, "score": { "type": "number", "description": "If present, according to the underlying Vector DB and the selected metric type, the score can be either the distance or the similarity between the query and the fact and its range depends on the metric type. For example, if the metric type is COSINE_DISTANCE, it represents the distance between the query and the fact. The larger the distance, the less relevant the fact is to the query. The range is [0, 2], while 0 means the most relevant and 2 means the least relevant.", "format": "double" }, "chunk": { "$ref": "GoogleCloudAiplatformV1beta1RagChunk", "description": "If present, chunk properties." }, "summary": { "description": "If present, the summary/snippet of the fact.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaTextPromptDatasetMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaTextPromptDatasetMetadata", "type": "object", "properties": { "seedEnabled": { "description": "Seeding enables model to return a deterministic response on a best effort basis. Determinism isn't guaranteed. This field determines whether or not seeding is enabled.", "type": "boolean" }, "promptApiSchema": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptApiSchema", "description": "The API schema of the prompt to support both UI and SDK usages." }, "systemInstruction": { "description": "The content of the prompt dataset system instruction.", "type": "string" }, "groundingConfig": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPredictParamsGroundingConfig", "description": "Grounding checking configuration." }, "text": { "description": "The content of the prompt dataset.", "type": "string" }, "note": { "description": "User-created prompt note. Note size limit is 2KB.", "type": "string" }, "hasPromptVariable": { "description": "Whether the prompt dataset has prompt variable.", "type": "boolean" }, "maxOutputTokens": { "type": "string", "description": "Value of the maximum number of tokens generated set when the dataset was saved.", "format": "int64" }, "seedValue": { "description": "The actual value of the seed.", "format": "int64", "type": "string" }, "temperature": { "type": "number", "format": "float", "description": "Temperature value used for sampling set when the dataset was saved. This value is used to tune the degree of randomness." }, "stopSequences": { "description": "Customized stop sequences.", "type": "array", "items": { "type": "string" } }, "candidateCount": { "format": "int64", "description": "Number of candidates.", "type": "string" }, "topP": { "type": "number", "description": "Top P value set when the dataset was saved. Given topK tokens for decoding, top candidates will be selected until the sum of their probabilities is topP.", "format": "float" }, "gcsUri": { "description": "The Google Cloud Storage URI that stores the prompt data.", "type": "string" }, "topK": { "type": "string", "description": "Top K value set when the dataset was saved. This value determines how many candidates with highest probability from the vocab would be selected for each decoding step.", "format": "int64" }, "promptType": { "description": "Type of the prompt dataset.", "type": "string" }, "systemInstructionGcsUri": { "description": "The Google Cloud Storage URI that stores the system instruction, starting with gs://.", "type": "string" }, "logprobs": { "description": "Whether or not the user has enabled logit probabilities in the model parameters.", "type": "boolean" } }, "description": "The metadata of Datasets that contain Text Prompt data." }, "GoogleCloudAiplatformV1beta1Blob": { "properties": { "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" }, "data": { "format": "byte", "description": "Required. The raw bytes of the data.", "type": "string" }, "displayName": { "description": "Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.", "type": "string" } }, "description": "A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video.", "id": "GoogleCloudAiplatformV1beta1Blob", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryPrecisionResults": { "description": "Results for TrajectoryPrecision metric.", "properties": { "trajectoryPrecisionMetricValues": { "description": "Output only. TrajectoryPrecision metric values.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryPrecisionMetricValue" }, "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1TrajectoryPrecisionResults", "type": "object" }, "GoogleCloudAiplatformV1beta1UndeployModelOperationMetadata": { "description": "Runtime operation information for EndpointService.UndeployModel.", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1beta1UndeployModelOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMappingNumericRestrict": { "id": "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMappingNumericRestrict", "type": "object", "description": "Restrictions on numeric values.", "properties": { "valueType": { "description": "Required. Numeric type of the restrict. Must be consistent for all datapoints within the namespace.", "enum": [ "VALUE_TYPE_UNSPECIFIED", "INT", "FLOAT", "DOUBLE" ], "type": "string", "enumDescriptions": [ "Should not be used.", "Represents 64 bit integer.", "Represents 32 bit float.", "Represents 64 bit float." ] }, "valueColumn": { "description": "Optional. The column containing the numeric value.", "type": "string" }, "namespace": { "description": "Required. The namespace of the restrict.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SummarizationQualityResult": { "id": "GoogleCloudAiplatformV1beta1SummarizationQualityResult", "type": "object", "description": "Spec for summarization quality result.", "properties": { "explanation": { "description": "Output only. Explanation for summarization quality score.", "readOnly": true, "type": "string" }, "confidence": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Confidence for summarization quality score." }, "score": { "description": "Output only. Summarization Quality score.", "format": "float", "type": "number", "readOnly": true } } }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecInteractionData": { "description": "Defines data for an interaction prompt.", "properties": { "interactionIds": { "type": "array", "items": { "type": "string" }, "description": "Optional. Lists interaction IDs associated with the prompt. This maps 1:1 to PromptMessage.contents. If InteractionData is present, every prompt message has an interaction ID." } }, "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecInteractionData", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaAnnotationSpecColor": { "properties": { "color": { "$ref": "GoogleTypeColor", "description": "The color of the AnnotationSpec in a segmentation mask." }, "displayName": { "description": "The display name of the AnnotationSpec represented by the color in the segmentation mask.", "type": "string" }, "id": { "description": "The ID of the AnnotationSpec represented by the color in the segmentation mask.", "type": "string" } }, "description": "An entry of mapping between color and AnnotationSpec. The mapping is used in segmentation mask.", "id": "GoogleCloudAiplatformV1beta1SchemaAnnotationSpecColor", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpec": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpec", "type": "object", "properties": { "inlineSource": { "description": "Source code is provided directly in the request.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecInlineSource" }, "pythonSpec": { "description": "Configuration for a Python application.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecPythonSpec" }, "developerConnectSource": { "description": "Source code is in a Git repository managed by Developer Connect.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecDeveloperConnectSource" }, "agentConfigSource": { "description": "Source code is generated from the agent config.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecAgentConfigSource" }, "imageSpec": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecImageSpec", "description": "Optional. Configuration for building an image with custom config file." } }, "description": "Specification for deploying from source code." }, "GoogleCloudAiplatformV1beta1NotebookExecutionJobWorkbenchRuntime": { "properties": {}, "description": "Configuration for a Workbench Instances-based environment.", "id": "GoogleCloudAiplatformV1beta1NotebookExecutionJobWorkbenchRuntime", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationRun": { "properties": { "evaluationConfig": { "description": "Required. The configuration used for the evaluation.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfig" }, "name": { "description": "Identifier. The resource name of the EvaluationRun. This is a unique identifier. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}`", "type": "string" }, "evaluationResults": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1EvaluationResults", "description": "Output only. The results of the evaluation run. Only populated when the evaluation run's state is SUCCEEDED." }, "displayName": { "description": "Required. The display name of the Evaluation Run.", "type": "string" }, "state": { "enum": [ "STATE_UNSPECIFIED", "PENDING", "RUNNING", "SUCCEEDED", "FAILED", "CANCELLED", "INFERENCE", "GENERATING_RUBRICS", "GENERATING_LOSS_CLUSTERS" ], "description": "Output only. The state of the evaluation run.", "readOnly": true, "type": "string", "enumDescriptions": [ "Unspecified state.", "The evaluation run is pending.", "The evaluation run is running.", "The evaluation run has succeeded.", "The evaluation run has failed.", "The evaluation run has been cancelled.", "The evaluation run is performing inference.", "The evaluation run is performing rubric generation.", "The evaluation run is performing loss analysis." ] }, "createTime": { "description": "Output only. Time when the evaluation run was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "evaluationSetSnapshot": { "type": "string", "readOnly": true, "description": "Output only. The specific evaluation set of the evaluation run. For runs with an evaluation set input, this will be that same set. For runs with BigQuery input, it's the sampled BigQuery dataset." }, "metadata": { "description": "Optional. Metadata about the evaluation run, can be used by the caller to store additional tracking information about the evaluation run.", "type": "any" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. Labels for the evaluation run." }, "error": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. Only populated when the evaluation run's state is FAILED or CANCELLED." }, "completionTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the evaluation run was completed." }, "dataSource": { "description": "Required. The data source for the evaluation run.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunDataSource" }, "inferenceConfigs": { "description": "Optional. The candidate to inference config map for the evaluation run. The candidate can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfig" } } }, "description": "EvaluationRun is a resource that represents a single evaluation run, which includes a set of prompts, model responses, evaluation configuration and the resulting metrics.", "id": "GoogleCloudAiplatformV1beta1EvaluationRun", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationPrompt": { "description": "Prompt variation for Translation use case.", "properties": { "sourceLanguageCode": { "description": "The source language code.", "type": "string" }, "option": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationOption", "description": "The translation option." }, "example": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationExample", "description": "The translation example." }, "targetLanguageCode": { "description": "The target language code.", "type": "string" }, "promptMessage": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecPromptMessage", "description": "The prompt message." } }, "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationPrompt", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentConfig": { "type": "object", "id": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentConfig", "deprecated": true, "description": "Deprecated: Use `google.cloud.aiplatform.master.AgentConfig` in `agent_eval_data` instead. Configuration for an Agent.", "properties": { "toolsText": { "description": "A JSON string containing a list of tools available to an agent with info such as name, description, parameters and required parameters.", "type": "string" }, "tools": { "description": "List of tools.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentConfigTools" }, "subAgents": { "description": "Optional. The list of valid agent IDs (names) that this agent can delegate to. This defines the directed edges in the agent system graph topology.", "type": "array", "items": { "type": "string" } }, "agentType": { "description": "Optional. The type or class of the agent (e.g., \"LlmAgent\", \"RouterAgent\", \"ToolUseAgent\"). Useful for the autorater to understand the expected behavior of the agent.", "type": "string" }, "description": { "description": "Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.", "type": "string" }, "agentId": { "description": "Optional. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.", "type": "string" }, "developerInstruction": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData", "description": "Optional. Contains instructions from the developer for the agent. Can be static or a dynamic prompt template used with the `AgentEvent.state_delta` field." } } }, "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchSpec": { "description": "Spec for tool parameter key match metric.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1SlackSourceSlackChannelsSlackChannel": { "description": "SlackChannel contains the Slack channel ID and the time range to import.", "properties": { "channelId": { "description": "Required. The Slack channel ID.", "type": "string" }, "endTime": { "description": "Optional. The ending timestamp for messages to import.", "format": "google-datetime", "type": "string" }, "startTime": { "format": "google-datetime", "description": "Optional. The starting timestamp for messages to import.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SlackSourceSlackChannelsSlackChannel", "type": "object" }, "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataResponse": { "id": "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataResponse", "type": "object", "properties": { "timeSeriesDataPoints": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TimeSeriesDataPoint" }, "description": "The returned time series data points." }, "nextPageToken": { "description": "A token, which can be sent as page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "description": "Response message for TensorboardService.ExportTensorboardTimeSeriesData." }, "GoogleCloudAiplatformV1beta1ReadIndexDatapointsResponse": { "id": "GoogleCloudAiplatformV1beta1ReadIndexDatapointsResponse", "type": "object", "properties": { "datapoints": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1IndexDatapoint" }, "description": "The result list of datapoints." } }, "description": "The response message for MatchService.ReadIndexDatapoints." }, "GoogleCloudAiplatformV1beta1PreTunedModel": { "description": "A pre-tuned model for continuous tuning.", "properties": { "baseModel": { "type": "string", "readOnly": true, "description": "Output only. The name of the base model this PreTunedModel was tuned from." }, "tunedModelName": { "description": "The resource name of the Model. E.g., a model resource name with a specified version id or alias: `projects/{project}/locations/{location}/models/{model}@{version_id}` `projects/{project}/locations/{location}/models/{model}@{alias}` Or, omit the version id to use the default version: `projects/{project}/locations/{location}/models/{model}`", "type": "string" }, "checkpointId": { "description": "Optional. The source checkpoint id. If not specified, the default checkpoint will be used.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1PreTunedModel", "type": "object" }, "GoogleCloudAiplatformV1beta1ImageConfigImageOutputOptions": { "properties": { "compressionQuality": { "description": "Optional. The compression quality of the output image.", "format": "int32", "type": "integer" }, "mimeType": { "description": "Optional. The image format that the output should be saved as.", "type": "string" } }, "description": "The image output format for generated images.", "id": "GoogleCloudAiplatformV1beta1ImageConfigImageOutputOptions", "type": "object" }, "GoogleCloudAiplatformV1beta1UndeployIndexOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1UndeployIndexOperationMetadata", "type": "object", "description": "Runtime operation information for IndexEndpointService.UndeployIndex.", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1beta1EvaluationDataset": { "description": "The dataset used for evaluation.", "properties": { "bigquerySource": { "$ref": "GoogleCloudAiplatformV1beta1BigQuerySource", "description": "BigQuery source holds the dataset." }, "gcsSource": { "$ref": "GoogleCloudAiplatformV1beta1GcsSource", "description": "Cloud storage source holds the dataset. Currently only one Cloud Storage file path is supported." } }, "id": "GoogleCloudAiplatformV1beta1EvaluationDataset", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateExtensionControllerOperationMetadata": { "description": "Details of ExtensionControllerService.CreateExtensionController operation.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The common part of the operation metadata." } }, "id": "GoogleCloudAiplatformV1beta1CreateExtensionControllerOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1RetrieveMemoriesResponse": { "properties": { "retrievedMemories": { "description": "The retrieved memories.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveMemoriesResponseRetrievedMemory" } }, "nextPageToken": { "description": "A token that can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages. This token is not set if similarity search was used for retrieval.", "type": "string" } }, "description": "Response message for MemoryBankService.RetrieveMemories.", "id": "GoogleCloudAiplatformV1beta1RetrieveMemoriesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1DirectPredictRequest": { "id": "GoogleCloudAiplatformV1beta1DirectPredictRequest", "type": "object", "description": "Request message for PredictionService.DirectPredict.", "properties": { "inputs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tensor" }, "description": "The prediction input." }, "parameters": { "description": "The parameters that govern the prediction.", "$ref": "GoogleCloudAiplatformV1beta1Tensor" } } }, "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopic": { "description": "A topic of information that should be extracted from conversations and stored as memories.", "properties": { "customMemoryTopic": { "description": "A custom memory topic defined by the developer.", "$ref": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopicCustomMemoryTopic" }, "managedMemoryTopic": { "$ref": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopicManagedMemoryTopic", "description": "A managed memory topic defined by Memory Bank." } }, "id": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopic", "type": "object" }, "GoogleCloudAiplatformV1beta1DeployRequestEndpointConfig": { "id": "GoogleCloudAiplatformV1beta1DeployRequestEndpointConfig", "type": "object", "description": "The endpoint config to use for the deployment.", "properties": { "dedicatedEndpointEnabled": { "description": "Optional. Deprecated. Use dedicated_endpoint_disabled instead. If true, the endpoint will be exposed through a dedicated DNS [Endpoint.dedicated_endpoint_dns]. Your request to the dedicated DNS will be isolated from other users' traffic and will have better performance and reliability. Note: Once you enabled dedicated endpoint, you won't be able to send request to the shared DNS {region}-aiplatform.googleapis.com. The limitations will be removed soon.", "type": "boolean", "deprecated": true }, "endpointUserId": { "description": "Optional. Immutable. The ID to use for endpoint, which will become the final component of the endpoint resource name. If not provided, Vertex AI will generate a value for this ID. If the first character is a letter, this value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The last character must be a letter or number. If the first character is a number, this value may be up to 9 characters, and valid characters are `[0-9]` with no leading zeros. When using HTTP/JSON, this field is populated based on a query string argument, such as `?endpoint_id=12345`. This is the fallback for fields that are not included in either the URI or the body.", "type": "string" }, "endpointDisplayName": { "description": "Optional. The user-specified display name of the endpoint. If not set, a default name will be used.", "type": "string" }, "dedicatedEndpointDisabled": { "description": "Optional. By default, if dedicated endpoint is enabled and private service connect config is not set, the endpoint will be exposed through a dedicated DNS [Endpoint.dedicated_endpoint_dns]. If private service connect config is set, the endpoint will be exposed through private service connect. Your request to the dedicated DNS will be isolated from other users' traffic and will have better performance and reliability. Note: Once you enabled dedicated endpoint, you won't be able to send request to the shared DNS {region}-aiplatform.googleapis.com. The limitations will be removed soon. If this field is set to true, the dedicated endpoint will be disabled and the deployed model will be exposed through the shared DNS {region}-aiplatform.googleapis.com.", "type": "boolean" }, "privateServiceConnectConfig": { "$ref": "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig", "description": "Optional. Configuration for private service connect. If set, the endpoint will be exposed through private service connect." }, "labels": { "description": "Optional. The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", "type": "object", "additionalProperties": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1UndeployModelRequest": { "properties": { "deployedModelId": { "description": "Required. The ID of the DeployedModel to be undeployed from the Endpoint.", "type": "string" }, "trafficSplit": { "description": "If this field is provided, then the Endpoint's traffic_split will be overwritten with it. If last DeployedModel is being undeployed from the Endpoint, the [Endpoint.traffic_split] will always end up empty when this call returns. A DeployedModel will be successfully undeployed only if it doesn't have any traffic assigned to it when this method executes, or if this field unassigns any traffic to it.", "type": "object", "additionalProperties": { "format": "int32", "type": "integer" } } }, "description": "Request message for EndpointService.UndeployModel.", "id": "GoogleCloudAiplatformV1beta1UndeployModelRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecPythonSpec": { "description": "Specification for running a Python application from source.", "properties": { "entrypointObject": { "description": "Optional. The name of the callable object within the `entrypoint_module` to use as the application If not specified, defaults to \"root_agent\". This field should not be set if the source is `agent_config_source`.", "type": "string" }, "requirementsFile": { "description": "Optional. The path to the requirements file, relative to the source root. If not specified, defaults to \"requirements.txt\".", "type": "string" }, "version": { "description": "Optional. The version of Python to use. Support version includes 3.9, 3.10, 3.11, 3.12, 3.13, 3.14. If not specified, default value is 3.10.", "type": "string" }, "entrypointModule": { "description": "Optional. The Python module to load as the entrypoint, specified as a fully qualified module name. For example: path.to.agent. If not specified, defaults to \"agent\". The project root will be added to Python sys.path, allowing imports to be specified relative to the root. This field should not be set if the source is `agent_config_source`.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecPythonSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateVideoResponse": { "id": "GoogleCloudAiplatformV1beta1GenerateVideoResponse", "type": "object", "properties": { "generatedSamples": { "description": "The cloud storage uris of the generated videos.", "type": "array", "items": { "type": "string" }, "deprecated": true }, "raiMediaFilteredCount": { "format": "int32", "description": "Returns if any videos were filtered due to RAI policies.", "type": "integer" }, "videos": { "description": "List of video bytes or Cloud Storage URIs of the generated videos.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GenerateVideoResponseVideo" } }, "raiMediaFilteredReasons": { "description": "Returns rai failure reasons if any.", "type": "array", "items": { "type": "string" } } }, "description": "Generate video response." }, "GoogleProtobufEmpty": { "id": "GoogleProtobufEmpty", "type": "object", "properties": {}, "description": "A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }" }, "GoogleCloudAiplatformV1beta1EvaluationRubricConfig": { "description": "Configuration for a rubric group to be generated/saved for evaluation.", "properties": { "rubricGroupKey": { "description": "Required. The key used to save the generated rubrics. If a generation spec is provided, this key will be used for the name of the generated rubric group. Otherwise, this key will be used to look up the existing rubric group on the evaluation item. Note that if a rubric group key is specified on both a rubric config and an evaluation metric, the key from the metric will be used to select the rubrics for evaluation.", "type": "string" }, "rubricGenerationSpec": { "description": "Dynamically generate rubrics using this specification.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricGenerationSpec" }, "predefinedRubricGenerationSpec": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunMetricPredefinedMetricSpec", "description": "Dynamically generate rubrics using a predefined spec." } }, "id": "GoogleCloudAiplatformV1beta1EvaluationRubricConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1Metadata": { "description": "Metadata for a chunk.", "properties": { "attributes": { "type": "object", "additionalProperties": { "type": "string", "format": "byte" }, "description": "Optional. Attributes attached to the data. The keys have semantic conventions and the consumers of the attributes should know how to deserialize the value bytes based on the keys." } }, "id": "GoogleCloudAiplatformV1beta1Metadata", "type": "object" }, "GoogleCloudAiplatformV1beta1VertexMultimodalDatasetDestination": { "id": "GoogleCloudAiplatformV1beta1VertexMultimodalDatasetDestination", "type": "object", "description": "The details for a Vertex Multimodal Dataset output.", "properties": { "bigqueryDestination": { "description": "Optional. The destination of the underlying BigQuery table that will be created for the output Multimodal Dataset. If not specified, the BigQuery table will be created in a default BigQuery dataset.", "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination" }, "displayName": { "description": "Optional. Display name of the output dataset.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1QueryReasoningEngineResponse": { "id": "GoogleCloudAiplatformV1beta1QueryReasoningEngineResponse", "type": "object", "description": "Response message for ReasoningEngineExecutionService.Query", "properties": { "output": { "description": "Response provided by users in JSON object format.", "type": "any" } } }, "GoogleCloudAiplatformV1beta1TuningJob": { "properties": { "tuningJobState": { "enum": [ "TUNING_JOB_STATE_UNSPECIFIED", "TUNING_JOB_STATE_WAITING_FOR_QUOTA", "TUNING_JOB_STATE_PROCESSING_DATASET", "TUNING_JOB_STATE_WAITING_FOR_CAPACITY", "TUNING_JOB_STATE_TUNING", "TUNING_JOB_STATE_POST_PROCESSING" ], "description": "Output only. The detail state of the tuning job (while the overall `JobState` is running).", "readOnly": true, "type": "string", "enumDescriptions": [ "Default tuning job state.", "Tuning job is waiting for job quota.", "Tuning job is validating the dataset.", "Tuning job is waiting for hardware capacity.", "Tuning job is running.", "Tuning job is doing some post processing steps." ] }, "pipelineJob": { "description": "Output only. The resource name of the PipelineJob associated with the TuningJob. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`.", "readOnly": true, "deprecated": true, "type": "string" }, "supervisedTuningSpec": { "description": "Tuning Spec for Supervised Fine Tuning.", "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningSpec" }, "tunedModelDisplayName": { "description": "Optional. The display name of the TunedModel. The name can be up to 128 characters long and can consist of any UTF-8 characters. For continuous tuning, tuned_model_display_name will by default use the same display name as the pre-tuned model. If a new display name is provided, the tuning job will create a new model instead of a new version.", "type": "string" }, "error": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`." }, "tunedModel": { "description": "Output only. The tuned model resources associated with this TuningJob.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1TunedModel" }, "state": { "type": "string", "enumDescriptions": [ "The job state is unspecified.", "The job has been just created or resumed and processing has not yet begun.", "The service is preparing to run the job.", "The job is in progress.", "The job completed successfully.", "The job failed.", "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "The job has been cancelled.", "The job has been stopped, and can be resumed.", "The job has expired.", "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", "The job is partially succeeded, some results may be missing due to errors." ], "readOnly": true, "description": "Output only. The detailed state of the job.", "enum": [ "JOB_STATE_UNSPECIFIED", "JOB_STATE_QUEUED", "JOB_STATE_PENDING", "JOB_STATE_RUNNING", "JOB_STATE_SUCCEEDED", "JOB_STATE_FAILED", "JOB_STATE_CANCELLING", "JOB_STATE_CANCELLED", "JOB_STATE_PAUSED", "JOB_STATE_EXPIRED", "JOB_STATE_UPDATING", "JOB_STATE_PARTIALLY_SUCCEEDED" ] }, "customBaseModel": { "description": "Optional. The user-provided path to custom model weights. Set this field to tune a custom model. The path must be a Cloud Storage directory that contains the model weights in .safetensors format along with associated model metadata files. If this field is set, the base_model field must still be set to indicate which base model the custom model is derived from. This feature is only available for open source models.", "type": "string" }, "experiment": { "readOnly": true, "type": "string", "description": "Output only. The Experiment associated with this TuningJob." }, "outputUri": { "description": "Optional. Cloud Storage path to the directory where tuning job outputs are written to. This field is only available and required for open source models.", "type": "string" }, "baseModel": { "description": "The base model that is being tuned. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/tuning#supported_models).", "type": "string" }, "tuningDataStats": { "description": "Output only. The tuning data statistics associated with this TuningJob.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1TuningDataStats" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key options for a TuningJob. If this is set, then all resources created by the TuningJob will be encrypted with the provided encryption key." }, "tuningJobMetadata": { "description": "Output only. Tuning Job metadata.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1TuningJobMetadata" }, "labels": { "description": "Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", "type": "object", "additionalProperties": { "type": "string" } }, "endTime": { "type": "string", "readOnly": true, "description": "Output only. Time when the TuningJob entered any of the following JobStates: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`, `JOB_STATE_EXPIRED`.", "format": "google-datetime" }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the TuningJob was most recently updated." }, "preTunedModel": { "description": "The pre-tuned model for continuous tuning.", "$ref": "GoogleCloudAiplatformV1beta1PreTunedModel" }, "evaluateDatasetRuns": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluateDatasetRun" }, "readOnly": true, "description": "Output only. Evaluation runs for the Tuning Job." }, "distillationSpec": { "description": "Tuning Spec for Distillation.", "$ref": "GoogleCloudAiplatformV1beta1DistillationSpec" }, "description": { "description": "Optional. The description of the TuningJob.", "type": "string" }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Time when the TuningJob was created.", "format": "google-datetime" }, "startTime": { "description": "Output only. Time when the TuningJob for the first time entered the `JOB_STATE_RUNNING` state.", "format": "google-datetime", "type": "string", "readOnly": true }, "partnerModelTuningSpec": { "$ref": "GoogleCloudAiplatformV1beta1PartnerModelTuningSpec", "description": "Tuning Spec for open sourced and third party Partner models." }, "preferenceOptimizationSpec": { "$ref": "GoogleCloudAiplatformV1beta1PreferenceOptimizationSpec", "description": "Tuning Spec for Preference Optimization." }, "veoTuningSpec": { "description": "Tuning Spec for Veo Tuning.", "$ref": "GoogleCloudAiplatformV1beta1VeoTuningSpec" }, "serviceAccount": { "description": "The service account that the tuningJob workload runs as. If not specified, the Vertex AI Secure Fine-Tuned Service Agent in the project will be used. See https://cloud.google.com/iam/docs/service-agents#vertex-ai-secure-fine-tuning-service-agent Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.", "type": "string" }, "fullFineTuningSpec": { "$ref": "GoogleCloudAiplatformV1beta1FullFineTuningSpec", "description": "Tuning Spec for Full Fine Tuning." }, "name": { "type": "string", "readOnly": true, "description": "Output only. Identifier. Resource name of a TuningJob. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`" }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." } }, "description": "Represents a TuningJob that runs with Google owned models.", "id": "GoogleCloudAiplatformV1beta1TuningJob", "type": "object" }, "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingInstance": { "id": "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingInstance", "type": "object", "properties": { "jsonInstance": { "description": "Required. Instance specified as a json string. String key-value pairs are expected in the json_instance to render RubricBasedInstructionFollowing prompt templates.", "type": "string" } }, "description": "Instance for RubricBasedInstructionFollowing metric - one instance corresponds to one row in an evaluation dataset." }, "GoogleCloudAiplatformV1beta1UserSpecifiedMetadata": { "properties": { "value": { "$ref": "GoogleCloudAiplatformV1beta1MetadataValue", "description": "Value of the metadata. The value must be able to convert to the type according to the data schema." }, "key": { "description": "Required. Key of the metadata. The key must be set with type by CreateRagDataSchema.", "type": "string" } }, "description": "Metadata provided by users.", "id": "GoogleCloudAiplatformV1beta1UserSpecifiedMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1SupervisedTuningSpec": { "id": "GoogleCloudAiplatformV1beta1SupervisedTuningSpec", "type": "object", "description": "Tuning Spec for Supervised Tuning for first party models.", "properties": { "trainingDatasetUri": { "description": "Required. Training dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset.", "type": "string" }, "validationDatasetUri": { "description": "Optional. Validation dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset.", "type": "string" }, "hyperParameters": { "description": "Optional. Hyperparameters for SFT.", "$ref": "GoogleCloudAiplatformV1beta1SupervisedHyperParameters" }, "exportLastCheckpointOnly": { "description": "Optional. If set to true, disable intermediate checkpoints for SFT and only the last checkpoint will be exported. Otherwise, enable intermediate checkpoints for SFT. Default is false.", "type": "boolean" }, "tuningMode": { "description": "Tuning mode.", "enum": [ "TUNING_MODE_UNSPECIFIED", "TUNING_MODE_FULL", "TUNING_MODE_PEFT_ADAPTER" ], "type": "string", "enumDescriptions": [ "Tuning mode is unspecified.", "Full fine-tuning mode.", "PEFT adapter tuning mode." ] }, "evaluationConfig": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationConfig", "description": "Optional. Evaluation Config for Tuning Job." } } }, "GoogleCloudAiplatformV1beta1TaskArtifactChange": { "properties": { "addedArtifacts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TaskArtifact" }, "description": "Optional. A list of brand-new artifacts created in this event." }, "deletedArtifactIds": { "description": "Optional. A list of artifact IDs that were removed in this event.", "type": "array", "items": { "type": "string" } }, "updatedArtifacts": { "description": "Optional. A list of existing artifacts that were modified in this event.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TaskArtifact" } } }, "description": "Describes changes to the artifact list.", "id": "GoogleCloudAiplatformV1beta1TaskArtifactChange", "type": "object" }, "GoogleCloudAiplatformV1beta1AssessDataRequestBatchPredictionValidationAssessmentConfig": { "description": "Configuration for the batch prediction validation assessment.", "properties": { "modelName": { "description": "Required. The name of the model used for batch prediction.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1AssessDataRequestBatchPredictionValidationAssessmentConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchImportModelEvaluationSlicesResponse": { "id": "GoogleCloudAiplatformV1beta1BatchImportModelEvaluationSlicesResponse", "type": "object", "description": "Response message for ModelService.BatchImportModelEvaluationSlices", "properties": { "importedModelEvaluationSlices": { "description": "Output only. List of imported ModelEvaluationSlice.name.", "readOnly": true, "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1TaskEvent": { "description": "An event that occurred for a task. Note that TaskEvent is just a record of task's change. Hence, it's not a Cloud resource.", "properties": { "eventSequenceNumber": { "type": "string", "description": "Required. The sequence number of the event. This is used to uniquely identify the event within the task and order events chronologically. This is a id generated by the SDK.", "format": "int64" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. The create time of the event." }, "eventData": { "$ref": "GoogleCloudAiplatformV1beta1TaskEventData", "description": "Required. The delta associated with the event." } }, "id": "GoogleCloudAiplatformV1beta1TaskEvent", "type": "object" }, "GoogleCloudAiplatformV1beta1LogprobsResultCandidate": { "id": "GoogleCloudAiplatformV1beta1LogprobsResultCandidate", "type": "object", "description": "A single token and its associated log probability.", "properties": { "tokenId": { "type": "integer", "description": "The token's numerical ID. While the `token` field provides the string representation of the token, the `token_id` is the numerical representation that the model uses internally. This can be useful for developers who want to build custom logic based on the model's vocabulary.", "format": "int32" }, "token": { "description": "The token's string representation.", "type": "string" }, "logProbability": { "description": "The log probability of this token. A higher value indicates that the model was more confident in this token. The log probability can be used to assess the relative likelihood of different tokens and to identify when the model is uncertain.", "format": "float", "type": "number" } } }, "GoogleCloudAiplatformV1beta1TrajectoryExactMatchInstance": { "description": "Spec for TrajectoryExactMatch instance.", "properties": { "predictedTrajectory": { "$ref": "GoogleCloudAiplatformV1beta1Trajectory", "description": "Required. Spec for predicted tool call trajectory." }, "referenceTrajectory": { "$ref": "GoogleCloudAiplatformV1beta1Trajectory", "description": "Required. Spec for reference tool call trajectory." } }, "id": "GoogleCloudAiplatformV1beta1TrajectoryExactMatchInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1RemoveExamplesResponse": { "id": "GoogleCloudAiplatformV1beta1RemoveExamplesResponse", "type": "object", "description": "Response message for ExampleStoreService.RemoveExamples.", "properties": { "exampleIds": { "type": "array", "items": { "type": "string" }, "description": "The IDs for the removed examples." } } }, "GoogleCloudAiplatformV1beta1RubricGenerationSpec": { "id": "GoogleCloudAiplatformV1beta1RubricGenerationSpec", "type": "object", "properties": { "rubricTypeOntology": { "type": "array", "items": { "type": "string" }, "description": "Optional. An optional, pre-defined list of allowed types for generated rubrics. If this field is provided, it implies `include_rubric_type` should be true, and the generated rubric types should be chosen from this ontology." }, "promptTemplate": { "description": "Template for the prompt used to generate rubrics. The details should be updated based on the most-recent recipe requirements.", "type": "string" }, "modelConfig": { "$ref": "GoogleCloudAiplatformV1beta1AutoraterConfig", "description": "Configuration for the model used in rubric generation. Configs including sampling count and base model can be specified here. Flipping is not supported for rubric generation." }, "rubricContentType": { "type": "string", "enumDescriptions": [ "The content type to generate is not specified.", "Generate rubrics based on properties.", "Generate rubrics in an NL question answer format.", "Generate rubrics in a unit test format." ], "enum": [ "RUBRIC_CONTENT_TYPE_UNSPECIFIED", "PROPERTY", "NL_QUESTION_ANSWER", "PYTHON_CODE_ASSERTION" ], "description": "The type of rubric content to be generated." } }, "description": "Specification for how rubrics should be generated." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetection": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetection", "type": "object", "description": "A TrainingJob that trains and uploads an AutoML Image Object Detection Model.", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs" }, "metadata": { "description": "The metadata information", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata" } } }, "GoogleIamV1TestIamPermissionsResponse": { "id": "GoogleIamV1TestIamPermissionsResponse", "type": "object", "properties": { "permissions": { "description": "A subset of `TestPermissionsRequest.permissions` that the caller is allowed.", "type": "array", "items": { "type": "string" } } }, "description": "Response message for `TestIamPermissions` method." }, "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair": { "description": "Feature name & value pair.", "properties": { "value": { "description": "Feature value.", "$ref": "GoogleCloudAiplatformV1beta1FeatureValue" }, "name": { "description": "Feature short name.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationGcsInputSource": { "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationGcsInputSource", "type": "object", "properties": { "inputUri": { "description": "Source data URI. For example, `gs://my_bucket/my_object`.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1FeatureView": { "properties": { "serviceAgentType": { "type": "string", "enumDescriptions": [ "By default, the project-level Vertex AI Service Agent is enabled.", "Indicates the project-level Vertex AI Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) will be used during sync jobs.", "Enable a FeatureView service account to be created by Vertex AI and output in the field `service_account_email`. This service account will be used to read from the source BigQuery table during sync." ], "enum": [ "SERVICE_AGENT_TYPE_UNSPECIFIED", "SERVICE_AGENT_TYPE_PROJECT", "SERVICE_AGENT_TYPE_FEATURE_VIEW" ], "description": "Optional. Service agent type used during data sync. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureView within a project, a separate service account should be provisioned by setting this field to `SERVICE_AGENT_TYPE_FEATURE_VIEW`. This will generate a separate service account to access the BigQuery source table." }, "indexConfig": { "description": "Optional. Configuration for index preparation for vector search. It contains the required configurations to create an index from source data, so that approximate nearest neighbor (a.k.a ANN) algorithms search can be performed during online serving.", "$ref": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfig" }, "optimizedConfig": { "description": "Optional. Configuration for FeatureView created under Optimized FeatureOnlineStore.", "$ref": "GoogleCloudAiplatformV1beta1FeatureViewOptimizedConfig" }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "serviceAccountEmail": { "readOnly": true, "type": "string", "description": "Output only. A Service Account unique to this FeatureView. The role bigquery.dataViewer should be granted to this service account to allow Vertex AI Feature Store to sync data to the online store." }, "featureRegistrySource": { "description": "Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore.", "$ref": "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySource" }, "createTime": { "description": "Output only. Timestamp when this FeatureView was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this FeatureView was last updated." }, "vertexRagSource": { "description": "Optional. The Vertex RAG Source that the FeatureView is linked to.", "$ref": "GoogleCloudAiplatformV1beta1FeatureViewVertexRagSource" }, "syncConfig": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewSyncConfig", "description": "Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving." }, "vectorSearchConfig": { "description": "Optional. Deprecated: please use FeatureView.index_config instead.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfig" }, "bigtableMetadata": { "description": "Output only. Metadata containing information about the Cloud Bigtable.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1FeatureViewBigtableMetadata" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" }, "satisfiesPzi": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "bigQuerySource": { "description": "Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.", "$ref": "GoogleCloudAiplatformV1beta1FeatureViewBigQuerySource" }, "name": { "description": "Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", "type": "string" } }, "description": "FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.", "id": "GoogleCloudAiplatformV1beta1FeatureView", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateUserScenariosRequest": { "properties": { "rootAgentId": { "description": "Required. The agent id to identify the root agent.", "type": "string" }, "agents": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1AgentConfig" }, "description": "Required. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent." }, "userScenarioGenerationConfig": { "description": "Required. Configuration for generating user scenarios.", "$ref": "GoogleCloudAiplatformV1beta1UserScenarioGenerationConfig" }, "allowCrossRegionModel": { "description": "Optional. Allows the scenario generation to use cross region models. When this flag is set, the service may route traffic to other regions if a model is unavailable in the current region (e.g., to a `global` endpoint). If a fully-qualified model endpoint resource name with a different region than the request location is provided elsewhere in the request, this flag must be set to true or the request will fail.", "type": "boolean" } }, "description": "Request message for DataFoundryService.GenerateUserScenarios.", "id": "GoogleCloudAiplatformV1beta1GenerateUserScenariosRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsResponse": { "description": "Response message for PipelineService.BatchDeletePipelineJobs.", "properties": { "pipelineJobs": { "description": "PipelineJobs deleted.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" } } }, "id": "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchNearestEntitiesRequest": { "id": "GoogleCloudAiplatformV1beta1SearchNearestEntitiesRequest", "type": "object", "description": "The request message for FeatureOnlineStoreService.SearchNearestEntities.", "properties": { "query": { "description": "Required. The query.", "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborQuery" }, "returnFullEntity": { "description": "Optional. If set to true, the full entities (including all vector values and metadata) of the nearest neighbors are returned; otherwise only entity id of the nearest neighbors will be returned. Note that returning full entities will significantly increase the latency and cost of the query.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringConfig": { "properties": { "analysisInstanceSchemaUri": { "description": "YAML schema file uri in Cloud Storage describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.", "type": "string" }, "objectiveConfigs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfig" }, "description": "Model monitoring objective config." }, "alertConfig": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig", "description": "Model monitoring alert config." }, "statsAnomaliesBaseDirectory": { "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", "description": "A Google Cloud Storage location for batch prediction model monitoring to dump statistics and anomalies. If not provided, a folder will be created in customer project to hold statistics and anomalies." } }, "description": "The model monitoring configuration used for Batch Prediction Job.", "id": "GoogleCloudAiplatformV1beta1ModelMonitoringConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1InvokeRequest": { "description": "Request message for PredictionService.Invoke.", "properties": { "httpBody": { "description": "The invoke method input. Supports HTTP headers and arbitrary data payload.", "$ref": "GoogleApiHttpBody" }, "deployedModelId": { "description": "ID of the DeployedModel that serves the invoke request.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1InvokeRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigDefaultRuntime": { "id": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigDefaultRuntime", "type": "object", "description": "The default runtime for the PipelineJob.", "properties": { "persistentResourceRuntimeDetail": { "$ref": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigPersistentResourceRuntimeDetail", "description": "Persistent resource based runtime detail." } } }, "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDataset": { "properties": { "datasetDisplayName": { "description": "The Dataset's display name in datalabeling.googleapis.com.", "type": "string" }, "dataset": { "description": "Full resource name of data labeling Dataset. Format: `projects/{project}/datasets/{dataset}`.", "type": "string" }, "dataLabelingAnnotatedDatasets": { "description": "The migratable AnnotatedDataset in datalabeling.googleapis.com belongs to the data labeling Dataset.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset" } } }, "description": "Represents one Dataset in datalabeling.googleapis.com.", "id": "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDataset", "type": "object" }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateNetworkPort": { "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateNetworkPort", "type": "object", "properties": { "protocol": { "enum": [ "PROTOCOL_UNSPECIFIED", "TCP", "UDP" ], "description": "Optional. Protocol for port. Defaults to TCP if not specified.", "type": "string", "enumDescriptions": [ "Unspecified protocol. Defaults to TCP.", "TCP protocol.", "UDP protocol." ] }, "port": { "format": "int32", "description": "Optional. Port number to expose. This must be a valid port number, between 1 and 65535.", "type": "integer" } }, "description": "Represents a network port in a container." }, "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityTraceScopePredicate": { "properties": { "duration": { "description": "Filter on the duration of a trace.", "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityNumericPredicate" }, "totalTokenUsage": { "description": "Filter on the total token usage within a trace.", "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityNumericPredicate" } }, "description": "Defines a single filter predicate.", "id": "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityTraceScopePredicate", "type": "object" }, "GoogleCloudAiplatformV1beta1OptimizePromptResponse": { "id": "GoogleCloudAiplatformV1beta1OptimizePromptResponse", "type": "object", "properties": { "content": { "description": "Output only. The optimized prompt.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "description": "Response message for GenAiTuningService.OptimizePrompt" }, "GoogleCloudAiplatformV1beta1GenerationConfig": { "id": "GoogleCloudAiplatformV1beta1GenerationConfig", "type": "object", "properties": { "presencePenalty": { "format": "float", "description": "Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].", "type": "number" }, "topP": { "type": "number", "description": "Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or `top_p`, but not both.", "format": "float" }, "topK": { "format": "float", "description": "Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.", "type": "number" }, "audioTimestamp": { "description": "Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.", "type": "boolean" }, "thinkingConfig": { "description": "Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigThinkingConfig" }, "modelConfig": { "description": "Optional. Config for model selection.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigModelConfig" }, "logprobs": { "description": "Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.", "format": "int32", "type": "integer" }, "routingConfig": { "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfig", "description": "Optional. Routing configuration." }, "frequencyPenalty": { "description": "Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].", "format": "float", "type": "number" }, "maxOutputTokens": { "type": "integer", "description": "Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.", "format": "int32" }, "seed": { "format": "int32", "description": "Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the \"random\" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.", "type": "integer" }, "candidateCount": { "description": "Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.", "format": "int32", "type": "integer" }, "stopSequences": { "description": "Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use [\"\\n\", \"###\"] to stop generation at a new line or a specific marker.", "type": "array", "items": { "type": "string" } }, "temperature": { "format": "float", "description": "Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0].", "type": "number" }, "responseSchema": { "$ref": "GoogleCloudAiplatformV1beta1Schema", "description": "Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`." }, "responseLogprobs": { "description": "Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.", "type": "boolean" }, "speechConfig": { "description": "Optional. The speech generation config.", "$ref": "GoogleCloudAiplatformV1beta1SpeechConfig" }, "mediaResolution": { "type": "string", "enumDescriptions": [ "Media resolution has not been set.", "Media resolution set to low (64 tokens).", "Media resolution set to medium (256 tokens).", "Media resolution set to high (zoomed reframing with 256 tokens)." ], "description": "Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.", "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "MEDIA_RESOLUTION_LOW", "MEDIA_RESOLUTION_MEDIUM", "MEDIA_RESOLUTION_HIGH" ] }, "imageConfig": { "description": "Optional. Config for image generation features.", "$ref": "GoogleCloudAiplatformV1beta1ImageConfig" }, "responseMimeType": { "description": "Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined.", "type": "string" }, "responseModalities": { "description": "Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.", "type": "array", "items": { "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "AUDIO", "VIDEO" ], "type": "string", "enumDescriptions": [ "Unspecified modality. Will be processed as text.", "Text modality.", "Image modality.", "Audio modality.", "Video modality." ] } }, "responseJsonSchema": { "description": "Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`.", "type": "any" }, "enableAffectiveDialog": { "description": "Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.", "type": "boolean" } }, "description": "Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output." }, "GoogleCloudAiplatformV1beta1BleuInstance": { "id": "GoogleCloudAiplatformV1beta1BleuInstance", "type": "object", "properties": { "reference": { "description": "Required. Ground truth used to compare against the prediction.", "type": "string" }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" } }, "description": "Spec for bleu instance." }, "GoogleCloudAiplatformV1beta1ListFeatureViewsResponse": { "id": "GoogleCloudAiplatformV1beta1ListFeatureViewsResponse", "type": "object", "properties": { "featureViews": { "description": "The FeatureViews matching the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureView" } }, "nextPageToken": { "description": "A token, which can be sent as ListFeatureViewsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureViews." }, "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchMetricValue": { "properties": { "score": { "type": "number", "readOnly": true, "description": "Output only. TrajectoryInOrderMatch score.", "format": "float" } }, "description": "TrajectoryInOrderMatch metric value for an instance.", "id": "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchMetricValue", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchImportModelEvaluationSlicesRequest": { "description": "Request message for ModelService.BatchImportModelEvaluationSlices", "properties": { "modelEvaluationSlices": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSlice" }, "description": "Required. Model evaluation slice resource to be imported." } }, "id": "GoogleCloudAiplatformV1beta1BatchImportModelEvaluationSlicesRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1OptimizePromptRequest": { "id": "GoogleCloudAiplatformV1beta1OptimizePromptRequest", "type": "object", "properties": { "content": { "description": "Required. The content of the prompt to optimize.", "$ref": "GoogleCloudAiplatformV1beta1Content" }, "optimizationTarget": { "enum": [ "OPTIMIZATION_TARGET_UNSPECIFIED", "OPTIMIZATION_TARGET_GENERAL", "OPTIMIZATION_TARGET_GEMINI_NANO", "OPTIMIZATION_TARGET_FEW_SHOT_RUBRICS", "OPTIMIZATION_TARGET_FEW_SHOT_TARGET_RESPONSE" ], "description": "Optional. The optimization strategy to use.", "type": "string", "enumDescriptions": [ "Unspecified optimization target. Defaults to `OPTIMIZATION_TARGET_GENERAL`.", "Optimizes the prompt for quality using a zero-shot approach.", "Optimizes the prompt for Gemini Nano models.", "Optimizes the prompt using few-shot examples with rubrics.", "Optimizes the prompt using few-shot examples with a target response." ] } }, "description": "Request message for GenAiTuningService.OptimizePrompt." }, "GoogleCloudAiplatformV1beta1DeployRequestModelConfig": { "properties": { "containerSpec": { "description": "Optional. The specification of the container that is to be used when deploying. If not set, the default container spec will be used.", "$ref": "GoogleCloudAiplatformV1beta1ModelContainerSpec" }, "huggingFaceAccessToken": { "description": "Optional. The Hugging Face read access token used to access the model artifacts of gated models.", "type": "string" }, "modelDisplayName": { "description": "Optional. The user-specified display name of the uploaded model. If not set, a default name will be used.", "type": "string" }, "modelUserId": { "description": "Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. When not provided, Vertex AI will generate a value for this ID. When Model Registry model is provided, this field will be ignored. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen.", "type": "string" }, "acceptEula": { "description": "Optional. Whether the user accepts the End User License Agreement (EULA) for the model.", "type": "boolean" }, "huggingFaceCacheEnabled": { "description": "Optional. If true, the model will deploy with a cached version instead of directly downloading the model artifacts from Hugging Face. This is suitable for VPC-SC users with limited internet access.", "type": "boolean" } }, "description": "The model config to use for the deployment.", "id": "GoogleCloudAiplatformV1beta1DeployRequestModelConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentResponse": { "properties": { "outputs": { "description": "The outputs from the sandbox environment.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Chunk" } } }, "description": "Response message for SandboxEnvironmentExecutionService.Execute.", "id": "GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ExportDataResponse": { "properties": { "exportedFiles": { "description": "All of the files that are exported in this export operation. For custom code training export, only three (training, validation and test) Cloud Storage paths in wildcard format are populated (for example, gs://.../training-*).", "type": "array", "items": { "type": "string" } } }, "description": "Response message for DatasetService.ExportData.", "id": "GoogleCloudAiplatformV1beta1ExportDataResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessSpec": { "properties": { "version": { "type": "integer", "description": "Optional. Which version to use for evaluation.", "format": "int32" }, "useReference": { "description": "Optional. Whether to use instance.reference to compute question answering correctness.", "type": "boolean" } }, "description": "Spec for question answering correctness metric.", "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1RagQueryRanking": { "id": "GoogleCloudAiplatformV1beta1RagQueryRanking", "type": "object", "description": "Configurations for hybrid search results ranking.", "properties": { "alpha": { "type": "number", "description": "Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.", "format": "float" } } }, "GoogleCloudAiplatformV1beta1TrajectoryRecallInstance": { "properties": { "predictedTrajectory": { "description": "Required. Spec for predicted tool call trajectory.", "$ref": "GoogleCloudAiplatformV1beta1Trajectory" }, "referenceTrajectory": { "$ref": "GoogleCloudAiplatformV1beta1Trajectory", "description": "Required. Spec for reference tool call trajectory." } }, "description": "Spec for TrajectoryRecall instance.", "id": "GoogleCloudAiplatformV1beta1TrajectoryRecallInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1CoherenceInput": { "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1beta1CoherenceInstance", "description": "Required. Coherence instance." }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1CoherenceSpec", "description": "Required. Spec for coherence score metric." } }, "description": "Input for coherence metric.", "id": "GoogleCloudAiplatformV1beta1CoherenceInput", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchDataItemsResponse": { "id": "GoogleCloudAiplatformV1beta1SearchDataItemsResponse", "type": "object", "description": "Response message for DatasetService.SearchDataItems.", "properties": { "dataItemViews": { "description": "The DataItemViews read.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DataItemView" } }, "nextPageToken": { "description": "A token to retrieve next page of results. Pass to SearchDataItemsRequest.page_token to obtain that page.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ResourcePool": { "properties": { "replicaCount": { "type": "string", "description": "Optional. The total number of machines to use for this resource pool.", "format": "int64" }, "id": { "description": "Immutable. The unique ID in a PersistentResource for referring to this resource pool. User can specify it if necessary. Otherwise, it's generated automatically.", "type": "string" }, "machineSpec": { "$ref": "GoogleCloudAiplatformV1beta1MachineSpec", "description": "Required. Immutable. The specification of a single machine." }, "diskSpec": { "$ref": "GoogleCloudAiplatformV1beta1DiskSpec", "description": "Optional. Disk spec for the machine in this node pool." }, "usedReplicaCount": { "format": "int64", "description": "Output only. The number of machines currently in use by training jobs for this resource pool. Will replace idle_replica_count.", "readOnly": true, "type": "string" }, "autoscalingSpec": { "$ref": "GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpec", "description": "Optional. Optional spec to configure GKE or Ray-on-Vertex autoscaling" } }, "description": "Represents the spec of a group of resources of the same type, for example machine type, disk, and accelerators, in a PersistentResource.", "id": "GoogleCloudAiplatformV1beta1ResourcePool", "type": "object" }, "GoogleCloudAiplatformV1beta1RagDataSchema": { "id": "GoogleCloudAiplatformV1beta1RagDataSchema", "type": "object", "properties": { "schemaDetails": { "description": "The schema details mapping to the key.", "$ref": "GoogleCloudAiplatformV1beta1RagMetadataSchemaDetails" }, "key": { "description": "Required. The key of this data schema. This key should be matching the key of user specified metadata and unique inside corpus. This value can be up to 63 characters, and valid characters are /a-z-/. The first character must be a letter, the last could be a letter or a number.", "type": "string" }, "name": { "description": "Identifier. Resource name of the data schema in the form of: `projects/{project_number}/locations/{location}/ragCorpora/{rag_corpus}/ragDataSchemas/{rag_data_schema}` where the {rag_data_schema} part should be the same as the `key` field below.", "type": "string" } }, "description": "The schema of the user specified metadata." }, "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesResponse": { "id": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesResponse", "type": "object", "description": "Response message for TensorboardService.BatchCreateTensorboardTimeSeries.", "properties": { "tensorboardTimeSeries": { "description": "The created TensorboardTimeSeries.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" } } } }, "GoogleCloudAiplatformV1beta1StudySpec": { "properties": { "measurementSelectionType": { "type": "string", "enumDescriptions": [ "Will be treated as LAST_MEASUREMENT.", "Use the last measurement reported.", "Use the best measurement reported." ], "description": "Describe which measurement selection type will be used", "enum": [ "MEASUREMENT_SELECTION_TYPE_UNSPECIFIED", "LAST_MEASUREMENT", "BEST_MEASUREMENT" ] }, "convexStopConfig": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1StudySpecConvexStopConfig", "description": "Deprecated. The automated early stopping using convex stopping rule." }, "decayCurveStoppingSpec": { "description": "The automated early stopping spec using decay curve rule.", "$ref": "GoogleCloudAiplatformV1beta1StudySpecDecayCurveAutomatedStoppingSpec" }, "medianAutomatedStoppingSpec": { "$ref": "GoogleCloudAiplatformV1beta1StudySpecMedianAutomatedStoppingSpec", "description": "The automated early stopping spec using median rule." }, "parameters": { "description": "Required. The set of parameters to tune.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpec" } }, "transferLearningConfig": { "description": "The configuration info/options for transfer learning. Currently supported for Vertex AI Vizier service, not HyperParameterTuningJob", "$ref": "GoogleCloudAiplatformV1beta1StudySpecTransferLearningConfig" }, "studyStoppingConfig": { "$ref": "GoogleCloudAiplatformV1beta1StudySpecStudyStoppingConfig", "description": "Conditions for automated stopping of a Study. Enable automated stopping by configuring at least one condition." }, "metrics": { "description": "Required. Metric specs for the Study.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1StudySpecMetricSpec" } }, "observationNoise": { "enum": [ "OBSERVATION_NOISE_UNSPECIFIED", "LOW", "HIGH" ], "description": "The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.", "type": "string", "enumDescriptions": [ "The default noise level chosen by Vertex AI.", "Vertex AI assumes that the objective function is (nearly) perfectly reproducible, and will never repeat the same Trial parameters.", "Vertex AI will estimate the amount of noise in metric evaluations, it may repeat the same Trial parameters more than once." ] }, "convexAutomatedStoppingSpec": { "description": "The automated early stopping spec using convex stopping rule.", "$ref": "GoogleCloudAiplatformV1beta1StudySpecConvexAutomatedStoppingSpec" }, "algorithm": { "type": "string", "enumDescriptions": [ "The default algorithm used by Vertex AI for [hyperparameter tuning](https://cloud.google.com/vertex-ai/docs/training/hyperparameter-tuning-overview) and [Vertex AI Vizier](https://cloud.google.com/vertex-ai/docs/vizier).", "Simple grid search within the feasible space. To use grid search, all parameters must be `INTEGER`, `CATEGORICAL`, or `DISCRETE`.", "Simple random search within the feasible space." ], "enum": [ "ALGORITHM_UNSPECIFIED", "GRID_SEARCH", "RANDOM_SEARCH" ], "description": "The search algorithm specified for the Study." } }, "description": "Represents specification of a Study.", "id": "GoogleCloudAiplatformV1beta1StudySpec", "type": "object" }, "GoogleCloudAiplatformV1beta1CoherenceInstance": { "id": "GoogleCloudAiplatformV1beta1CoherenceInstance", "type": "object", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" } }, "description": "Spec for coherence instance." }, "GoogleCloudAiplatformV1beta1Neighbor": { "id": "GoogleCloudAiplatformV1beta1Neighbor", "type": "object", "description": "Neighbors for example-based explanations.", "properties": { "neighborId": { "description": "Output only. The neighbor id.", "type": "string", "readOnly": true }, "neighborDistance": { "format": "double", "description": "Output only. The neighbor distance.", "readOnly": true, "type": "number" } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPoint": { "description": "Represents a single statistics data point.", "properties": { "baselineStats": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValue", "description": "Statistics from baseline dataset." }, "thresholdValue": { "format": "double", "description": "Threshold value.", "type": "number" }, "schedule": { "description": "Schedule resource name.", "type": "string" }, "algorithm": { "description": "Algorithm used to calculated the metrics, eg: jensen_shannon_divergence, l_infinity.", "type": "string" }, "hasAnomaly": { "description": "Indicate if the statistics has anomaly.", "type": "boolean" }, "createTime": { "format": "google-datetime", "description": "Statistics create time.", "type": "string" }, "modelMonitoringJob": { "description": "Model monitoring job resource name.", "type": "string" }, "currentStats": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValue", "description": "Statistics from current dataset." } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPoint", "type": "object" }, "GoogleCloudAiplatformV1beta1WriteFeatureValuesPayload": { "properties": { "featureValues": { "description": "Required. Feature values to be written, mapping from Feature ID to value. Up to 100,000 `feature_values` entries may be written across all payloads. The feature generation time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1FeatureValue" } }, "entityId": { "description": "Required. The ID of the entity.", "type": "string" } }, "description": "Contains Feature values to be written for a specific entity.", "id": "GoogleCloudAiplatformV1beta1WriteFeatureValuesPayload", "type": "object" }, "GoogleCloudAiplatformV1beta1PublisherModelCallToAction": { "properties": { "requestAccess": { "description": "Optional. Request for access.", "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences" }, "openNotebook": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", "description": "Optional. Open notebook of the PublisherModel." }, "openGenie": { "description": "Optional. Open Genie / Playground.", "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences" }, "openNotebooks": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenNotebooks", "description": "Optional. Open notebooks of the PublisherModel." }, "openPromptTuningPipeline": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", "description": "Optional. Open prompt-tuning pipeline of the PublisherModel." }, "deploy": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeploy", "description": "Optional. Deploy the PublisherModel to Vertex Endpoint." }, "openEvaluationPipeline": { "description": "Optional. Open evaluation pipeline of the PublisherModel.", "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences" }, "openFineTuningPipeline": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", "description": "Optional. Open fine-tuning pipeline of the PublisherModel." }, "multiDeployVertex": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployVertex", "description": "Optional. Multiple setups to deploy the PublisherModel to Vertex Endpoint." }, "openGenerationAiStudio": { "description": "Optional. Open in Generation AI Studio.", "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences" }, "createApplication": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", "description": "Optional. Create application using the PublisherModel." }, "openFineTuningPipelines": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenFineTuningPipelines", "description": "Optional. Open fine-tuning pipelines of the PublisherModel." }, "viewRestApi": { "description": "Optional. To view Rest API docs.", "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionViewRestApi" }, "deployGke": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployGke", "description": "Optional. Deploy PublisherModel to Google Kubernetes Engine." } }, "description": "Actions could take on this Publisher Model.", "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToAction", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateFeatureRequest": { "description": "Request message for FeaturestoreService.CreateFeature. Request message for FeatureRegistryService.CreateFeature.", "properties": { "parent": { "description": "Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "type": "string" }, "feature": { "$ref": "GoogleCloudAiplatformV1beta1Feature", "description": "Required. The Feature to create." }, "featureId": { "description": "Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1CreateFeatureRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ListExecutionsResponse": { "properties": { "nextPageToken": { "description": "A token, which can be sent as ListExecutionsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages.", "type": "string" }, "executions": { "description": "The Executions retrieved from the MetadataStore.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Execution" } } }, "description": "Response message for MetadataService.ListExecutions.", "id": "GoogleCloudAiplatformV1beta1ListExecutionsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1RawOutput": { "properties": { "rawOutput": { "description": "Output only. Raw output string.", "readOnly": true, "type": "array", "items": { "type": "string" } } }, "description": "Raw output.", "id": "GoogleCloudAiplatformV1beta1RawOutput", "type": "object" }, "GoogleCloudAiplatformV1beta1MigrateResourceRequest": { "properties": { "migrateAutomlModelConfig": { "description": "Config for migrating Model in automl.googleapis.com to Vertex AI's Model.", "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlModelConfig" }, "migrateMlEngineModelVersionConfig": { "description": "Config for migrating Version in ml.googleapis.com to Vertex AI's Model.", "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateMlEngineModelVersionConfig" }, "migrateAutomlDatasetConfig": { "description": "Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset.", "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlDatasetConfig" }, "migrateDataLabelingDatasetConfig": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfig", "description": "Deprecated: Data labeling service is shut down. Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset." } }, "description": "Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.", "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecFeatureAttributionSpec": { "properties": { "defaultAlertCondition": { "description": "Default alert condition for all the features.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition" }, "featureAlertConditions": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition" }, "description": "Per feature alert condition will override default alert condition." }, "features": { "description": "Feature names interested in monitoring. These should be a subset of the input feature names specified in the monitoring schema. If the field is not specified all features outlied in the monitoring schema will be used.", "type": "array", "items": { "type": "string" } }, "batchExplanationDedicatedResources": { "description": "The config of resources used by the Model Monitoring during the batch explanation for non-AutoML models. If not set, `n1-standard-2` machine type will be used by default.", "$ref": "GoogleCloudAiplatformV1beta1BatchDedicatedResources" } }, "description": "Feature attribution monitoring spec.", "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecFeatureAttributionSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextSentimentPredictionInstance": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextSentimentPredictionInstance", "type": "object", "properties": { "content": { "description": "The text snippet to make the predictions on.", "type": "string" }, "mimeType": { "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain", "type": "string" } }, "description": "Prediction input format for Text Sentiment." }, "GoogleCloudAiplatformV1beta1DedicatedResourcesScaleToZeroSpec": { "description": "Specification for scale-to-zero feature.", "properties": { "idleScaledownPeriod": { "format": "google-duration", "description": "Optional. Duration of no traffic before scaling to zero. [MinValue=300] (5 minutes) [MaxValue=28800] (8 hours)", "type": "string" }, "minScaleupPeriod": { "type": "string", "description": "Optional. Minimum duration that a deployment will be scaled up before traffic is evaluated for potential scale-down. [MinValue=300] (5 minutes) [MaxValue=28800] (8 hours)", "format": "google-duration" } }, "id": "GoogleCloudAiplatformV1beta1DedicatedResourcesScaleToZeroSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1FindNeighborsRequestQuery": { "id": "GoogleCloudAiplatformV1beta1FindNeighborsRequestQuery", "type": "object", "description": "A query to find a number of the nearest neighbors (most similar vectors) of a vector.", "properties": { "neighborCount": { "type": "integer", "description": "The number of nearest neighbors to be retrieved from database for each query. If not set, will use the default from the service configuration (https://cloud.google.com/vertex-ai/docs/matching-engine/configuring-indexes#nearest-neighbor-search-config).", "format": "int32" }, "approximateNeighborCount": { "type": "integer", "description": "The number of neighbors to find via approximate search before exact reordering is performed. If not set, the default value from scam config is used; if set, this value must be \u003e 0.", "format": "int32" }, "fractionLeafNodesToSearchOverride": { "type": "number", "description": "The fraction of the number of leaves to search, set at query time allows user to tune search performance. This value increase result in both search accuracy and latency increase. The value should be between 0.0 and 1.0. If not set or set to 0.0, query uses the default value specified in NearestNeighborSearchConfig.TreeAHConfig.fraction_leaf_nodes_to_search.", "format": "double" }, "datapoint": { "description": "Required. The datapoint/vector whose nearest neighbors should be searched for.", "$ref": "GoogleCloudAiplatformV1beta1IndexDatapoint" }, "perCrowdingAttributeNeighborCount": { "type": "integer", "format": "int32", "description": "Crowding is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute. It's used for improving result diversity. This field is the maximum number of matches with the same crowding tag." }, "rrf": { "description": "Optional. Represents RRF algorithm that combines search results.", "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsRequestQueryRRF" } } }, "GoogleCloudAiplatformV1beta1NotebookExecutionJobDataformRepositorySource": { "description": "The Dataform Repository containing the input notebook.", "properties": { "dataformRepositoryResourceName": { "description": "The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`", "type": "string" }, "commitSha": { "description": "The commit SHA to read repository with. If unset, the file will be read at HEAD.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1NotebookExecutionJobDataformRepositorySource", "type": "object" }, "GoogleCloudAiplatformV1beta1UrlMetadata": { "id": "GoogleCloudAiplatformV1beta1UrlMetadata", "type": "object", "properties": { "urlRetrievalStatus": { "description": "The status of the URL retrieval.", "enum": [ "URL_RETRIEVAL_STATUS_UNSPECIFIED", "URL_RETRIEVAL_STATUS_SUCCESS", "URL_RETRIEVAL_STATUS_ERROR" ], "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "The URL was retrieved successfully.", "The URL retrieval failed." ] }, "retrievedUrl": { "description": "The URL retrieved by the tool.", "type": "string" } }, "description": "The metadata for a single URL retrieval." }, "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoActionRecognitionPredictionParams": { "description": "Prediction model parameters for Video Action Recognition.", "properties": { "confidenceThreshold": { "format": "float", "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", "type": "number" }, "maxPredictions": { "format": "int32", "description": "The model only returns up to that many top, by confidence score, predictions per frame of the video. If this number is very high, the Model may return fewer predictions per frame. Default value is 50.", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoActionRecognitionPredictionParams", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureViewIndexConfig": { "id": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfig", "type": "object", "properties": { "treeAhConfig": { "description": "Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396", "$ref": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigTreeAHConfig" }, "embeddingDimension": { "type": "integer", "description": "Optional. The number of dimensions of the input embedding.", "format": "int32" }, "distanceMeasureType": { "description": "Optional. The distance measure used in nearest neighbor search.", "enum": [ "DISTANCE_MEASURE_TYPE_UNSPECIFIED", "SQUARED_L2_DISTANCE", "COSINE_DISTANCE", "DOT_PRODUCT_DISTANCE" ], "type": "string", "enumDescriptions": [ "Should not be set.", "Euclidean (L_2) Distance.", "Cosine Distance. Defined as 1 - cosine similarity. We strongly suggest using DOT_PRODUCT_DISTANCE + UNIT_L2_NORM instead of COSINE distance. Our algorithms have been more optimized for DOT_PRODUCT distance which, when combined with UNIT_L2_NORM, is mathematically equivalent to COSINE distance and results in the same ranking.", "Dot Product Distance. Defined as a negative of the dot product." ] }, "bruteForceConfig": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigBruteForceConfig", "description": "Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search." }, "embeddingColumn": { "description": "Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search.", "type": "string" }, "filterColumns": { "type": "array", "items": { "type": "string" }, "description": "Optional. Columns of features that're used to filter vector search results." }, "crowdingColumn": { "description": "Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.", "type": "string" } }, "description": "Configuration for vector indexing." }, "GoogleCloudAiplatformV1beta1DistillationSpec": { "description": "Tuning Spec for Distillation.", "properties": { "promptDatasetUri": { "description": "Optional. Cloud Storage path to file containing prompt dataset for distillation. The dataset must be formatted as a JSONL file.", "type": "string" }, "trainingDatasetUri": { "description": "Deprecated. Cloud Storage path to file containing training dataset for tuning. The dataset must be formatted as a JSONL file.", "type": "string", "deprecated": true }, "baseTeacherModel": { "description": "The base teacher model that is being distilled. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/tuning#supported_models).", "type": "string" }, "pipelineRootDirectory": { "type": "string", "deprecated": true, "description": "Deprecated. A path in a Cloud Storage bucket, which will be treated as the root output directory of the distillation pipeline. It is used by the system to generate the paths of output artifacts." }, "tunedTeacherModelSource": { "description": "The resource name of the Tuned teacher model. Format: `projects/{project}/locations/{location}/models/{model}`.", "type": "string" }, "validationDatasetUri": { "description": "Optional. Cloud Storage path to file containing validation dataset for tuning. The dataset must be formatted as a JSONL file.", "type": "string" }, "hyperParameters": { "description": "Optional. Hyperparameters for Distillation.", "$ref": "GoogleCloudAiplatformV1beta1DistillationHyperParameters" }, "tuningMode": { "description": "Optional. Specifies the tuning mode for distillation (sft part). This feature is only available for open source models.", "enum": [ "TUNING_MODE_UNSPECIFIED", "TUNING_MODE_FULL", "TUNING_MODE_PEFT_ADAPTER" ], "type": "string", "enumDescriptions": [ "Tuning mode is unspecified.", "Full fine-tuning mode.", "PEFT adapter tuning mode." ] }, "studentModel": { "description": "The student model that is being tuned, e.g., \"google/gemma-2b-1.1-it\". Deprecated. Use base_model instead.", "deprecated": true, "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1DistillationSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1RetrieveContextsRequest": { "id": "GoogleCloudAiplatformV1beta1RetrieveContextsRequest", "type": "object", "description": "Request message for VertexRagService.RetrieveContexts.", "properties": { "vertexRagStore": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStore", "description": "The data source for Vertex RagStore." }, "query": { "$ref": "GoogleCloudAiplatformV1beta1RagQuery", "description": "Required. Single RAG retrieve query." } } }, "GoogleCloudAiplatformV1beta1CreateDatasetVersionOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateDatasetVersionOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Runtime operation information for DatasetService.CreateDatasetVersion." }, "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesRequest": { "id": "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesRequest", "type": "object", "properties": { "dataKeys": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKey" } }, "dataFormat": { "enum": [ "FEATURE_VIEW_DATA_FORMAT_UNSPECIFIED", "KEY_VALUE", "PROTO_STRUCT" ], "description": "Specify response data format. If not set, KeyValue format will be used.", "type": "string", "enumDescriptions": [ "Not set. Will be treated as the KeyValue format.", "Return response data in key-value format.", "Return response data in proto Struct format." ] } }, "description": "Request message for FeatureOnlineStoreService.StreamingFetchFeatureValues. For the entities requested, all features under the requested feature view will be returned." }, "GoogleCloudAiplatformV1beta1IntermediateExtractedMemory": { "id": "GoogleCloudAiplatformV1beta1IntermediateExtractedMemory", "type": "object", "description": "An extracted memory that is the intermediate result before consolidation.", "properties": { "fact": { "readOnly": true, "type": "string", "description": "Output only. Represents the fact of the extracted memory." }, "structuredData": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "readOnly": true, "description": "Output only. Represents the structured value of the extracted memory." }, "context": { "description": "Output only. Represents the explanation of why the information was extracted from the source content.", "type": "string", "readOnly": true } } }, "GoogleCloudAiplatformV1beta1PartMediaResolution": { "properties": { "level": { "description": "The tokenization quality used for given media.", "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "MEDIA_RESOLUTION_LOW", "MEDIA_RESOLUTION_MEDIUM", "MEDIA_RESOLUTION_HIGH", "MEDIA_RESOLUTION_ULTRA_HIGH" ], "type": "string", "enumDescriptions": [ "Media resolution has not been set.", "Media resolution set to low.", "Media resolution set to medium.", "Media resolution set to high.", "Media resolution set to ultra high. This is for image only." ] } }, "description": "per part media resolution. Media resolution for the input media.", "id": "GoogleCloudAiplatformV1beta1PartMediaResolution", "type": "object" }, "GoogleCloudAiplatformV1beta1MigratableResource": { "id": "GoogleCloudAiplatformV1beta1MigratableResource", "type": "object", "description": "Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com.", "properties": { "automlDataset": { "description": "Output only. Represents one Dataset in automl.googleapis.com.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1MigratableResourceAutomlDataset" }, "lastUpdateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this MigratableResource was last updated.", "format": "google-datetime" }, "automlModel": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1MigratableResourceAutomlModel", "description": "Output only. Represents one Model in automl.googleapis.com." }, "mlEngineModelVersion": { "description": "Output only. Represents one Version in ml.googleapis.com.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1MigratableResourceMlEngineModelVersion" }, "dataLabelingDataset": { "readOnly": true, "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDataset", "description": "Output only. Deprecated: Data Labeling Dataset migration is no longer supported. Represents one Dataset in datalabeling.googleapis.com." }, "lastMigrateTime": { "format": "google-datetime", "description": "Output only. Timestamp when the last migration attempt on this MigratableResource started. Will not be set if there's no migration attempt on this MigratableResource.", "readOnly": true, "type": "string" } } }, "GoogleCloudAiplatformV1beta1AddContextChildrenResponse": { "properties": {}, "description": "Response message for MetadataService.AddContextChildren.", "id": "GoogleCloudAiplatformV1beta1AddContextChildrenResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityNumericPredicate": { "id": "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityNumericPredicate", "type": "object", "description": "Defines a predicate for filtering based on a numeric value.", "properties": { "comparisonOperator": { "enum": [ "COMPARISON_OPERATOR_UNSPECIFIED", "LESS", "LESS_OR_EQUAL", "EQUAL", "NOT_EQUAL", "GREATER_OR_EQUAL", "GREATER" ], "description": "Required. The comparison operator to apply.", "type": "string", "enumDescriptions": [ "Unspecified comparison operator. This value should not be used.", "Less than.", "Less than or equal to.", "Equal to.", "Not equal to.", "Greater than or equal to.", "Greater than." ] }, "value": { "description": "Required. The value to compare against.", "format": "float", "type": "number" } } }, "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigInputArtifact": { "properties": { "artifactId": { "description": "Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.", "type": "string" } }, "description": "The type of an input artifact.", "id": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigInputArtifact", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpecAgentGatewayConfig": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpecAgentGatewayConfig", "type": "object", "properties": { "clientToAgentConfig": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigClientToAgentConfig", "description": "Optional. Configuration for traffic targeting the Reasoning Engine. When unset, incoming traffic is not routed through an Agent Gateway." }, "agentToAnywhereConfig": { "description": "Optional. Configuration for traffic originating from the Reasoning Engine. When unset, outgoing traffic is not routed through an Agent Gateway.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigAgentToAnywhereConfig" } }, "description": "Agent Gateway configuration for a Reasoning Engine deployment." }, "GoogleCloudAiplatformV1beta1FasterDeploymentConfig": { "properties": { "fastTryoutEnabled": { "description": "If true, enable fast tryout feature for this deployed model.", "type": "boolean" } }, "description": "Configuration for faster model deployment.", "id": "GoogleCloudAiplatformV1beta1FasterDeploymentConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1EnterpriseWebSearch": { "description": "Tool to search public web data, powered by Vertex AI Search and Sec4 compliance.", "properties": { "excludeDomains": { "type": "array", "items": { "type": "string" }, "description": "Optional. List of domains to be excluded from the search results. The default limit is 2000 domains." }, "blockingConfidence": { "enum": [ "PHISH_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_HIGH_AND_ABOVE", "BLOCK_HIGHER_AND_ABOVE", "BLOCK_VERY_HIGH_AND_ABOVE", "BLOCK_ONLY_EXTREMELY_HIGH" ], "description": "Optional. Sites with confidence level chosen & above this value will be blocked from the search results.", "type": "string", "enumDescriptions": [ "Defaults to unspecified.", "Blocks Low and above confidence URL that is risky.", "Blocks Medium and above confidence URL that is risky.", "Blocks High and above confidence URL that is risky.", "Blocks Higher and above confidence URL that is risky.", "Blocks Very high and above confidence URL that is risky.", "Blocks Extremely high confidence URL that is risky." ] } }, "id": "GoogleCloudAiplatformV1beta1EnterpriseWebSearch", "type": "object" }, "GoogleCloudAiplatformV1beta1InputDataConfig": { "description": "Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.", "properties": { "gcsDestination": { "description": "The Cloud Storage location where the training data is to be written to. In the given directory a new directory is created with name: `dataset---` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All training input data is written into that directory. The Vertex AI environment variables representing Cloud Storage data URIs are represented in the Cloud Storage wildcard format to support sharded data. e.g.: \"gs://.../training-*.jsonl\" * AIP_DATA_FORMAT = \"jsonl\" for non-tabular data, \"csv\" for tabular data * AIP_TRAINING_DATA_URI = \"gcs_destination/dataset---/training-*.${AIP_DATA_FORMAT}\" * AIP_VALIDATION_DATA_URI = \"gcs_destination/dataset---/validation-*.${AIP_DATA_FORMAT}\" * AIP_TEST_DATA_URI = \"gcs_destination/dataset---/test-*.${AIP_DATA_FORMAT}\"", "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" }, "filterSplit": { "description": "Split based on the provided filters for each set.", "$ref": "GoogleCloudAiplatformV1beta1FilterSplit" }, "bigqueryDestination": { "description": "Only applicable to custom training with tabular Dataset with BigQuery source. The BigQuery project location where the training data is to be written to. In the given project a new dataset is created with name `dataset___` where timestamp is in YYYY_MM_DDThh_mm_ss_sssZ format. All training input data is written into that dataset. In the dataset three tables are created, `training`, `validation` and `test`. * AIP_DATA_FORMAT = \"bigquery\". * AIP_TRAINING_DATA_URI = \"bigquery_destination.dataset___.training\" * AIP_VALIDATION_DATA_URI = \"bigquery_destination.dataset___.validation\" * AIP_TEST_DATA_URI = \"bigquery_destination.dataset___.test\"", "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination" }, "fractionSplit": { "description": "Split based on fractions defining the size of each set.", "$ref": "GoogleCloudAiplatformV1beta1FractionSplit" }, "annotationsFilter": { "description": "Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem.", "type": "string" }, "annotationSchemaUri": { "description": "Applicable only to custom training with Datasets that have DataItems and Annotations. Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/ , note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id. Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.", "type": "string" }, "timestampSplit": { "$ref": "GoogleCloudAiplatformV1beta1TimestampSplit", "description": "Supported only for tabular Datasets. Split based on the timestamp of the input data pieces." }, "predefinedSplit": { "$ref": "GoogleCloudAiplatformV1beta1PredefinedSplit", "description": "Supported only for tabular Datasets. Split based on a predefined key." }, "stratifiedSplit": { "description": "Supported only for tabular Datasets. Split based on the distribution of the specified column.", "$ref": "GoogleCloudAiplatformV1beta1StratifiedSplit" }, "persistMlUseAssignment": { "description": "Whether to persist the ML use assignment to data item system labels.", "type": "boolean" }, "datasetId": { "description": "Required. The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from.", "type": "string" }, "savedQueryId": { "description": "Only applicable to Datasets that have SavedQueries. The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1InputDataConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ComputeTokensResponse": { "id": "GoogleCloudAiplatformV1beta1ComputeTokensResponse", "type": "object", "description": "Response message for ComputeTokens RPC call.", "properties": { "tokensInfo": { "description": "Lists of tokens info from the input. A ComputeTokensRequest could have multiple instances with a prompt in each instance. We also need to return lists of tokens info for the request with multiple instances.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TokensInfo" } } } }, "GoogleCloudAiplatformV1beta1ListFeatureMonitorJobsResponse": { "id": "GoogleCloudAiplatformV1beta1ListFeatureMonitorJobsResponse", "type": "object", "description": "Response message for FeatureRegistryService.ListFeatureMonitorJobs.", "properties": { "featureMonitorJobs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureMonitorJob" }, "description": "The FeatureMonitorJobs matching the request." }, "nextPageToken": { "description": "A token, which can be sent as ListFeatureMonitorJobsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpec": { "properties": { "memoryBankConfig": { "description": "Optional. Specification for a Memory Bank, which manages memories for the Agent Engine.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfig" } }, "description": "Configuration for how Agent Engine sub-resources should manage context.", "id": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline": { "description": "Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores.", "properties": { "gcs": { "description": "Cloud Storage location for BatchExplain output.", "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" }, "bigquery": { "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination", "description": "BigQuery location for BatchExplain output." }, "predictionFormat": { "enum": [ "PREDICTION_FORMAT_UNSPECIFIED", "JSONL", "BIGQUERY" ], "description": "The storage format of the predictions generated BatchPrediction job.", "type": "string", "enumDescriptions": [ "Should not be set.", "Predictions are in JSONL files.", "Predictions are in BigQuery." ] } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline", "type": "object" }, "GoogleCloudAiplatformV1beta1Model": { "description": "A trained machine learning Model.", "properties": { "explanationSpec": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec", "description": "The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob." }, "baseModelSource": { "description": "Optional. User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models.", "$ref": "GoogleCloudAiplatformV1beta1ModelBaseModelSource" }, "supportedDeploymentResourcesTypes": { "description": "Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the Endpoint.deployed_models object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an Endpoint and does not support online predictions (PredictionService.Predict or PredictionService.Explain). Such a Model can serve predictions by using a BatchPredictionJob, if it has at least one entry each in supported_input_storage_formats and supported_output_storage_formats.", "readOnly": true, "type": "array", "items": { "type": "string", "enumDescriptions": [ "Should not be used.", "Resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.", "Resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.", "Resources that can be shared by multiple DeployedModels. A pre-configured DeploymentResourcePool is required." ], "enum": [ "DEPLOYMENT_RESOURCES_TYPE_UNSPECIFIED", "DEDICATED_RESOURCES", "AUTOMATIC_RESOURCES", "SHARED_RESOURCES" ] } }, "supportedInputStorageFormats": { "type": "array", "items": { "type": "string" }, "readOnly": true, "description": "Output only. The formats this Model supports in BatchPredictionJob.input_config. If PredictSchemata.instance_schema_uri exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses GcsSource. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsSource. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses GcsSource. * `bigquery` Each instance is a single row in BigQuery. Uses BigQuerySource. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the InputConfig object. If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain." }, "satisfiesPzs": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "versionId": { "description": "Output only. Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation.", "type": "string", "readOnly": true }, "versionAliases": { "type": "array", "items": { "type": "string" }, "description": "User provided version aliases so that a model version can be referenced via alias (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_alias}` instead of auto-generated version id (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_id})`. The format is a-z{0,126}[a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model." }, "metadataSchemaUri": { "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", "type": "string" }, "originalModelInfo": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ModelOriginalModelInfo", "description": "Output only. If this Model is a copy of another Model, this contains info about the original." }, "versionCreateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this version was created." }, "trainingPipeline": { "description": "Output only. The resource name of the TrainingPipeline that uploaded this Model, if any.", "type": "string", "readOnly": true }, "deployedModels": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DeployedModelRef" }, "readOnly": true, "description": "Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations." }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "checkpoints": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Checkpoint" }, "readOnly": true, "description": "Optional. Output only. The checkpoints of the model." }, "supportedExportFormats": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelExportFormat" }, "readOnly": true, "description": "Output only. The formats in which this Model may be exported. If empty, this Model is not available for export." }, "metadataArtifact": { "description": "Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.", "type": "string", "readOnly": true }, "name": { "description": "Identifier. The resource name of the Model.", "type": "string" }, "defaultCheckpointId": { "description": "The default checkpoint id of a model version.", "type": "string" }, "versionDescription": { "description": "The description of this version.", "type": "string" }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "versionUpdateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this version was most recently updated." }, "predictSchemata": { "description": "The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.", "$ref": "GoogleCloudAiplatformV1beta1PredictSchemata" }, "displayName": { "description": "Required. The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this Model was most recently updated.", "format": "google-datetime" }, "modelSourceInfo": { "description": "Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ModelSourceInfo" }, "metadata": { "description": "Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.", "type": "any" }, "labels": { "description": "The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", "type": "object", "additionalProperties": { "type": "string" } }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this Model was uploaded into Vertex AI.", "format": "google-datetime" }, "description": { "description": "The description of the Model.", "type": "string" }, "containerSpec": { "description": "Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.", "$ref": "GoogleCloudAiplatformV1beta1ModelContainerSpec" }, "supportedOutputStorageFormats": { "description": "Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and PredictSchemata.prediction_schema_uri exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses GcsDestination. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsDestination. * `bigquery` Each prediction is a single row in a BigQuery table, uses BigQueryDestination . If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.", "readOnly": true, "type": "array", "items": { "type": "string" } }, "artifactUri": { "description": "Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not required for AutoML Models.", "type": "string" }, "encryptionSpec": { "description": "Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.", "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" } }, "id": "GoogleCloudAiplatformV1beta1Model", "type": "object" }, "GoogleCloudAiplatformV1beta1DeployIndexResponse": { "id": "GoogleCloudAiplatformV1beta1DeployIndexResponse", "type": "object", "properties": { "deployedIndex": { "description": "The DeployedIndex that had been deployed in the IndexEndpoint.", "$ref": "GoogleCloudAiplatformV1beta1DeployedIndex" } }, "description": "Response message for IndexEndpointService.DeployIndex." }, "GoogleCloudAiplatformV1beta1ListIndexesResponse": { "id": "GoogleCloudAiplatformV1beta1ListIndexesResponse", "type": "object", "properties": { "indexes": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Index" }, "description": "List of indexes in the requested page." }, "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListIndexesRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for IndexService.ListIndexes." }, "GoogleCloudAiplatformV1beta1ExportPublisherModelOperationMetadata": { "description": "Runtime operation information for ModelGardenService.ExportPublisherModel.", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1beta1ExportPublisherModelOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1BleuResults": { "id": "GoogleCloudAiplatformV1beta1BleuResults", "type": "object", "properties": { "bleuMetricValues": { "description": "Output only. Bleu metric values.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1BleuMetricValue" } } }, "description": "Results for bleu metric." }, "GoogleCloudAiplatformV1beta1ScheduleRunResponse": { "id": "GoogleCloudAiplatformV1beta1ScheduleRunResponse", "type": "object", "properties": { "scheduledRunTime": { "type": "string", "description": "The scheduled run time based on the user-specified schedule.", "format": "google-datetime" }, "runResponse": { "description": "The response of the scheduled run.", "type": "string" } }, "description": "Status of a scheduled run." }, "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest": { "id": "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest", "type": "object", "description": "Request message for ModelService.BatchImportEvaluatedAnnotations", "properties": { "evaluatedAnnotations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluatedAnnotation" }, "description": "Required. Evaluated annotations resource to be imported." } } }, "GoogleCloudAiplatformV1beta1ListTensorboardsResponse": { "description": "Response message for TensorboardService.ListTensorboards.", "properties": { "tensorboards": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tensorboard" }, "description": "The Tensorboards mathching the request." }, "nextPageToken": { "description": "A token, which can be sent as ListTensorboardsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListTensorboardsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1RemoveDatapointsRequest": { "description": "Request message for IndexService.RemoveDatapoints", "properties": { "datapointIds": { "description": "A list of datapoint ids to be deleted.", "type": "array", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1beta1RemoveDatapointsRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1FullFineTunedResources": { "id": "GoogleCloudAiplatformV1beta1FullFineTunedResources", "type": "object", "properties": { "deploymentType": { "type": "string", "enumDescriptions": [ "Unspecified deployment type.", "Eval deployment type.", "Prod deployment type." ], "description": "Required. The kind of deployment.", "enum": [ "DEPLOYMENT_TYPE_UNSPECIFIED", "DEPLOYMENT_TYPE_EVAL", "DEPLOYMENT_TYPE_PROD" ] }, "modelInferenceUnitCount": { "description": "Optional. The number of model inference units to use for this deployment. This can only be specified for DEPLOYMENT_TYPE_PROD. The following table lists the number of model inference units for different model types: * Gemini 2.5 Flash * Foundation FMIU: 25 * Expansion FMIU: 4 * Gemini 2.5 Pro * Foundation FMIU: 32 * Expansion FMIU: 16 * Veo 3.0 (undistilled) * Foundation FMIU: 63 * Expansion FMIU: 7 * Veo 3.0 (distilled) * Foundation FMIU: 30 * Expansion FMIU: 10", "format": "int32", "type": "integer" } }, "description": "Resources for an fft model." }, "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentSnapshotsResponse": { "id": "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentSnapshotsResponse", "type": "object", "properties": { "sandboxEnvironmentSnapshots": { "description": "The SandboxEnvironmentSnapshots matching the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSnapshot" } }, "nextPageToken": { "description": "A token, which can be sent as ListSandboxEnvironmentSnapshotsRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages.", "type": "string" } }, "description": "Response message for SandboxEnvironmentService.ListSandboxEnvironmentSnapshots." }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch": { "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch", "type": "object", "properties": { "alpha": { "format": "float", "description": "Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.", "type": "number" } }, "description": "Config for Hybrid Search." }, "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies", "type": "object", "description": "Statistics and anomalies generated by Model Monitoring.", "properties": { "deployedModelId": { "description": "Deployed Model ID.", "type": "string" }, "anomalyCount": { "description": "Number of anomalies within all stats.", "format": "int32", "type": "integer" }, "objective": { "type": "string", "enumDescriptions": [ "Default value, should not be set.", "Raw feature values' stats to detect skew between Training-Prediction datasets.", "Raw feature values' stats to detect drift between Serving-Prediction datasets.", "Feature attribution scores to detect skew between Training-Prediction datasets.", "Feature attribution scores to detect skew between Prediction datasets collected within different time windows." ], "description": "Model Monitoring Objective those stats and anomalies belonging to.", "enum": [ "MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_TYPE_UNSPECIFIED", "RAW_FEATURE_SKEW", "RAW_FEATURE_DRIFT", "FEATURE_ATTRIBUTION_SKEW", "FEATURE_ATTRIBUTION_DRIFT" ] }, "featureStats": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies" }, "description": "A list of historical Stats and Anomalies generated for all Features." } } }, "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInstance": { "properties": { "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "instruction": { "description": "Optional. Summarization prompt for LLM.", "type": "string" }, "context": { "description": "Required. Text to be summarized.", "type": "string" } }, "description": "Spec for summarization helpfulness instance.", "id": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1MutateDeployedIndexResponse": { "properties": { "deployedIndex": { "$ref": "GoogleCloudAiplatformV1beta1DeployedIndex", "description": "The DeployedIndex that had been updated in the IndexEndpoint." } }, "description": "Response message for IndexEndpointService.MutateDeployedIndex.", "id": "GoogleCloudAiplatformV1beta1MutateDeployedIndexResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpec": { "properties": { "configs": { "description": "Mapping configuration for this SliceSpec. The key is the name of the feature. By default, the key will be prefixed by \"instance\" as a dictionary prefix for Vertex Batch Predictions output format.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecSliceConfig" } } }, "description": "Specification for how the data should be sliced.", "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1UrlContextMetadata": { "properties": { "urlMetadata": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1UrlMetadata" }, "readOnly": true, "description": "Output only. A list of URL metadata, with one entry for each URL retrieved by the tool." } }, "description": "Metadata returned when the model uses the `url_context` tool to get information from a user-provided URL.", "id": "GoogleCloudAiplatformV1beta1UrlContextMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1PredictSchemata": { "id": "GoogleCloudAiplatformV1beta1PredictSchemata", "type": "object", "description": "Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob.", "properties": { "predictionSchemaUri": { "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single prediction produced by this Model, which are returned via PredictResponse.predictions, ExplainResponse.explanations, and BatchPredictionJob.output_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", "type": "string" }, "parametersSchemaUri": { "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing the parameters of prediction and explanation via PredictRequest.parameters, ExplainRequest.parameters and BatchPredictionJob.model_parameters. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no parameters are supported, then it is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", "type": "string" }, "instanceSchemaUri": { "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single instance, which are used in PredictRequest.instances, ExplainRequest.instances and BatchPredictionJob.input_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest": { "description": "Request message for ReasoningEngineExecutionService.StreamQuery.", "properties": { "input": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc." }, "classMethod": { "description": "Optional. Class method to be used for the stream query. It is optional and defaults to \"stream_query\" if unspecified.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateRagMetadataRequest": { "properties": { "parent": { "description": "Required. The parent resource where this metadata will be created. Format: `projects/{project_number}/locations/{location_id}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}`", "type": "string" }, "ragMetadata": { "description": "Required. The metadata to create.", "$ref": "GoogleCloudAiplatformV1beta1RagMetadata" }, "ragMetadataId": { "description": "Optional. The ID to use for the metadata, which will become the final component of the metadata's resource name if the user chooses to specify. Otherwise, metadata id will be generated by system. This value should be up to 63 characters, and valid characters are /a-z-/. The first character must be a letter, the last could be a letter or a number.", "type": "string" } }, "description": "Request message for CreateRagMetadata.", "id": "GoogleCloudAiplatformV1beta1CreateRagMetadataRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SuspendOnlineEvaluatorRequest": { "description": "Request message for SuspendOnlineEvaluator.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1SuspendOnlineEvaluatorRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateCustomContainerEnvironment": { "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateCustomContainerEnvironment", "type": "object", "description": "The customized sandbox runtime environment for BYOC.", "properties": { "ports": { "description": "Ports to expose from the container.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateNetworkPort" } }, "resources": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateResourceRequirements", "description": "Resource requests and limits for the container." }, "customContainerSpec": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateCustomContainerSpec", "description": "The specification of the custom container environment." } } }, "GoogleCloudAiplatformV1beta1RagMetadataSchemaDetailsListConfig": { "description": "Config for List data type.", "properties": { "valueSchema": { "$ref": "GoogleCloudAiplatformV1beta1RagMetadataSchemaDetails", "description": "The value's data type in the list." } }, "id": "GoogleCloudAiplatformV1beta1RagMetadataSchemaDetailsListConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecContainerSpec": { "description": "Specification for deploying from a container image.", "properties": { "imageUri": { "description": "Required. The Artifact Registry Docker image URI (e.g., us-central1-docker.pkg.dev/my-project/my-repo/my-image:tag) of the container image that is to be run on each worker replica.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecContainerSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1StructuredMemoryConfig": { "properties": { "schemaConfigs": { "description": "Optional. Represents configuration of the structured memories' schemas.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1StructuredMemoryConfigSchemaConfig" } }, "scopeKeys": { "type": "array", "items": { "type": "string" }, "description": "Optional. Represents the scope keys (i.e. 'user_id') for which to use this config. A request's scope must include all of the provided keys for the config to be used (order does not matter). If empty, then the config will be used for all requests that do not have a more specific config. Only one default config is allowed per Memory Bank." } }, "description": "Represents configuration for organizing structured memories for a particular scope.", "id": "GoogleCloudAiplatformV1beta1StructuredMemoryConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolNameMatchSpec": { "id": "GoogleCloudAiplatformV1beta1ToolNameMatchSpec", "type": "object", "properties": {}, "description": "Spec for tool name match metric." }, "GoogleCloudAiplatformV1beta1DistillationHyperParameters": { "id": "GoogleCloudAiplatformV1beta1DistillationHyperParameters", "type": "object", "properties": { "batchSize": { "description": "Optional. Batch size for tuning. This feature is only available for open source models.", "format": "int64", "type": "string" }, "epochCount": { "type": "string", "description": "Optional. Number of complete passes the model makes over the entire training dataset during training.", "format": "int64" }, "adapterSize": { "enum": [ "ADAPTER_SIZE_UNSPECIFIED", "ADAPTER_SIZE_ONE", "ADAPTER_SIZE_TWO", "ADAPTER_SIZE_FOUR", "ADAPTER_SIZE_EIGHT", "ADAPTER_SIZE_SIXTEEN", "ADAPTER_SIZE_THIRTY_TWO" ], "description": "Optional. Adapter size for distillation.", "type": "string", "enumDescriptions": [ "Adapter size is unspecified.", "Adapter size 1.", "Adapter size 2.", "Adapter size 4.", "Adapter size 8.", "Adapter size 16.", "Adapter size 32." ] }, "learningRateMultiplier": { "description": "Optional. Multiplier for adjusting the default learning rate.", "format": "double", "type": "number" }, "learningRate": { "format": "double", "description": "Optional. Specifies the learning rate for tuning. Mutually exclusive with `learning_rate_multiplier`. This feature is only available for open source models.", "type": "number" } }, "description": "Hyperparameters for Distillation." }, "GoogleCloudAiplatformV1beta1ModelEvaluation": { "properties": { "metricsSchemaUri": { "description": "Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).", "type": "string" }, "biasConfigs": { "description": "Specify the configuration for bias detection.", "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationBiasConfig" }, "displayName": { "description": "The display name of the ModelEvaluation.", "type": "string" }, "modelExplanation": { "$ref": "GoogleCloudAiplatformV1beta1ModelExplanation", "description": "Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models. " }, "metrics": { "description": "Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri", "type": "any" }, "explanationSpecs": { "description": "Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationModelEvaluationExplanationSpec" } }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this ModelEvaluation was created." }, "name": { "type": "string", "readOnly": true, "description": "Output only. The resource name of the ModelEvaluation." }, "sliceDimensions": { "description": "All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of `slice.dimension = `.", "type": "array", "items": { "type": "string" } }, "metadata": { "description": "The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of \"pipeline_job_id\", \"evaluation_dataset_type\", \"evaluation_dataset_path\", \"row_based_metrics_path\".", "type": "any" } }, "description": "A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.", "id": "GoogleCloudAiplatformV1beta1ModelEvaluation", "type": "object" }, "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMappingRestrict": { "id": "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMappingRestrict", "type": "object", "description": "Restrictions on string values.", "properties": { "namespace": { "description": "Required. The namespace of the restrict in the index.", "type": "string" }, "allowColumn": { "description": "Optional. The columns containing the allow values.", "type": "array", "items": { "type": "string" } }, "denyColumn": { "description": "Optional. The columns containing the deny values.", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringJob": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringJob", "type": "object", "description": "Represents a model monitoring job that analyze dataset using different monitoring algorithm.", "properties": { "schedule": { "description": "Output only. Schedule resource name. It will only appear when this job is triggered by a schedule.", "type": "string", "readOnly": true }, "name": { "readOnly": true, "type": "string", "description": "Output only. Resource name of a ModelMonitoringJob. Format: `projects/{project_id}/locations/{location_id}/modelMonitors/{model_monitor_id}/modelMonitoringJobs/{model_monitoring_job_id}`" }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this ModelMonitoringJob was updated most recently." }, "modelMonitoringSpec": { "description": "Monitoring monitoring job spec. It outlines the specifications for monitoring objectives, notifications, and result exports. If left blank, the default monitoring specifications from the top-level resource 'ModelMonitor' will be applied. If provided, we will use the specification defined here rather than the default one.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringSpec" }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when this ModelMonitoringJob was created.", "readOnly": true, "type": "string" }, "state": { "enum": [ "JOB_STATE_UNSPECIFIED", "JOB_STATE_QUEUED", "JOB_STATE_PENDING", "JOB_STATE_RUNNING", "JOB_STATE_SUCCEEDED", "JOB_STATE_FAILED", "JOB_STATE_CANCELLING", "JOB_STATE_CANCELLED", "JOB_STATE_PAUSED", "JOB_STATE_EXPIRED", "JOB_STATE_UPDATING", "JOB_STATE_PARTIALLY_SUCCEEDED" ], "description": "Output only. The state of the monitoring job. * When the job is still creating, the state will be 'JOB_STATE_PENDING'. * Once the job is successfully created, the state will be 'JOB_STATE_RUNNING'. * Once the job is finished, the state will be one of 'JOB_STATE_FAILED', 'JOB_STATE_SUCCEEDED', 'JOB_STATE_PARTIALLY_SUCCEEDED'.", "readOnly": true, "type": "string", "enumDescriptions": [ "The job state is unspecified.", "The job has been just created or resumed and processing has not yet begun.", "The service is preparing to run the job.", "The job is in progress.", "The job completed successfully.", "The job failed.", "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "The job has been cancelled.", "The job has been stopped, and can be resumed.", "The job has expired.", "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", "The job is partially succeeded, some results may be missing due to errors." ] }, "jobExecutionDetail": { "description": "Output only. Execution results for all the monitoring objectives.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetail" }, "scheduleTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this ModelMonitoringJob was scheduled. It will only appear when this job is triggered by a schedule." }, "displayName": { "description": "The display name of the ModelMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpec": { "properties": { "minReplicaCount": { "type": "string", "description": "Optional. min replicas in the node pool, must be ≤ replica_count and \u003c max_replica_count or will throw error. For autoscaling enabled Ray-on-Vertex, we allow min_replica_count of a resource_pool to be 0 to match the OSS Ray behavior(https://docs.ray.io/en/latest/cluster/vms/user-guides/configuring-autoscaling.html#cluster-config-parameters). As for Persistent Resource, the min_replica_count must be \u003e 0, we added a corresponding validation inside CreatePersistentResourceRequestValidator.java.", "format": "int64" }, "maxReplicaCount": { "description": "Optional. max replicas in the node pool, must be ≥ replica_count and \u003e min_replica_count or will throw error", "format": "int64", "type": "string" } }, "description": "The min/max number of replicas allowed if enabling autoscaling", "id": "GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1MutateDeployedModelResponse": { "description": "Response message for EndpointService.MutateDeployedModel.", "properties": { "deployedModel": { "$ref": "GoogleCloudAiplatformV1beta1DeployedModel", "description": "The DeployedModel that's being mutated." } }, "id": "GoogleCloudAiplatformV1beta1MutateDeployedModelResponse", "type": "object" }, "GoogleTypeLatLng": { "properties": { "longitude": { "description": "The longitude in degrees. It must be in the range [-180.0, +180.0].", "format": "double", "type": "number" }, "latitude": { "description": "The latitude in degrees. It must be in the range [-90.0, +90.0].", "format": "double", "type": "number" } }, "description": "An object that represents a latitude/longitude pair. This is expressed as a pair of doubles to represent degrees latitude and degrees longitude. Unless specified otherwise, this object must conform to the WGS84 standard. Values must be within normalized ranges.", "id": "GoogleTypeLatLng", "type": "object" }, "GoogleCloudAiplatformV1beta1BigQuerySource": { "properties": { "inputUri": { "description": "Required. BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.", "type": "string" } }, "description": "The BigQuery location for the input content.", "id": "GoogleCloudAiplatformV1beta1BigQuerySource", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationMetric": { "properties": { "metric": { "description": "Optional. The metric configuration. Only LLMMetric and CustomCodeExecutionMetric are supported.", "$ref": "GoogleCloudAiplatformV1beta1Metric" }, "displayName": { "description": "Required. The user-friendly display name for the EvaluationMetric.", "type": "string" }, "createTime": { "format": "google-datetime", "description": "Output only. The time when the EvaluationMetric was created.", "readOnly": true, "type": "string" }, "description": { "description": "Optional. A description of the EvaluationMetric.", "type": "string" }, "labels": { "description": "Optional. Labels for the evaluation metric.", "type": "object", "additionalProperties": { "type": "string" } }, "gcsUri": { "description": "Optional. The Google Cloud Storage URI that stores the metric specification..", "type": "string" }, "name": { "description": "Identifier. The resource name of the EvaluationMetric. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}`", "type": "string" }, "updateTime": { "description": "Output only. The time when the EvaluationMetric was last updated.", "format": "google-datetime", "type": "string", "readOnly": true } }, "description": "EvaluationMetric is a resource that represents a reusable metric configuration.", "id": "GoogleCloudAiplatformV1beta1EvaluationMetric", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecPartList": { "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecPartList", "type": "object", "properties": { "parts": { "description": "A list of elements that can be part of a prompt.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Part" } } }, "description": "A list of elements and information that make up a portion of prompt." }, "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesOperationMetadata": { "description": "Details of operations that batch reads Feature values.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for Featurestore batch read Features values." } }, "id": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1PreferenceOptimizationSpec": { "properties": { "trainingDatasetUri": { "description": "Required. Cloud Storage path to file containing training dataset for preference optimization tuning. The dataset must be formatted as a JSONL file.", "type": "string" }, "validationDatasetUri": { "description": "Optional. Cloud Storage path to file containing validation dataset for preference optimization tuning. The dataset must be formatted as a JSONL file.", "type": "string" }, "hyperParameters": { "$ref": "GoogleCloudAiplatformV1beta1PreferenceOptimizationHyperParameters", "description": "Optional. Hyperparameters for Preference Optimization." }, "exportLastCheckpointOnly": { "description": "Optional. If set to true, disable intermediate checkpoints for Preference Optimization and only the last checkpoint will be exported. Otherwise, enable intermediate checkpoints for Preference Optimization. Default is false.", "type": "boolean" } }, "description": "Tuning Spec for Preference Optimization.", "id": "GoogleCloudAiplatformV1beta1PreferenceOptimizationSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ComputationBasedMetricSpec": { "id": "GoogleCloudAiplatformV1beta1ComputationBasedMetricSpec", "type": "object", "properties": { "type": { "type": "string", "enumDescriptions": [ "Unspecified computation based metric type.", "Exact match metric.", "BLEU metric.", "ROUGE metric." ], "description": "Required. The type of the computation based metric.", "enum": [ "COMPUTATION_BASED_METRIC_TYPE_UNSPECIFIED", "EXACT_MATCH", "BLEU", "ROUGE" ] }, "parameters": { "description": "Optional. A map of parameters for the metric, e.g. {\"rouge_type\": \"rougeL\"}.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "description": "Specification for a computation based metric." }, "GoogleCloudAiplatformV1beta1TrajectoryExactMatchMetricValue": { "id": "GoogleCloudAiplatformV1beta1TrajectoryExactMatchMetricValue", "type": "object", "description": "TrajectoryExactMatch metric value for an instance.", "properties": { "score": { "description": "Output only. TrajectoryExactMatch score.", "format": "float", "type": "number", "readOnly": true } } }, "GoogleCloudAiplatformV1beta1SupervisedTuningDataStats": { "id": "GoogleCloudAiplatformV1beta1SupervisedTuningDataStats", "type": "object", "properties": { "totalTruncatedExampleCount": { "type": "string", "readOnly": true, "description": "Output only. The number of examples in the dataset that have been dropped. An example can be dropped for reasons including: too many tokens, contains an invalid image, contains too many images, etc.", "format": "int64" }, "userOutputTokenDistribution": { "description": "Output only. Dataset distributions for the user output tokens.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution" }, "droppedExampleReasons": { "description": "Output only. For each index in `truncated_example_indices`, the user-facing reason why the example was dropped.", "type": "array", "items": { "type": "string" }, "readOnly": true }, "totalBillableCharacterCount": { "readOnly": true, "type": "string", "format": "int64", "deprecated": true, "description": "Output only. Number of billable characters in the tuning dataset." }, "totalBillableTokenCount": { "description": "Output only. Number of billable tokens in the tuning dataset.", "format": "int64", "type": "string", "readOnly": true }, "userMessagePerExampleDistribution": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution", "description": "Output only. Dataset distributions for the messages per example." }, "userDatasetExamples": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "description": "Output only. Sample user messages in the training dataset uri." }, "truncatedExampleIndices": { "readOnly": true, "type": "array", "items": { "type": "string", "format": "int64" }, "description": "Output only. A partial sample of the indices (starting from 1) of the dropped examples." }, "tuningDatasetExampleCount": { "format": "int64", "description": "Output only. Number of examples in the tuning dataset.", "readOnly": true, "type": "string" }, "tuningStepCount": { "type": "string", "readOnly": true, "description": "Output only. Number of tuning steps for this Tuning Job.", "format": "int64" }, "userInputTokenDistribution": { "description": "Output only. Dataset distributions for the user input tokens.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution" }, "totalTuningCharacterCount": { "format": "int64", "description": "Output only. Number of tuning characters in the tuning dataset.", "readOnly": true, "type": "string" } }, "description": "Tuning data statistics for Supervised Tuning." }, "GoogleCloudAiplatformV1beta1CheckPublisherModelEulaAcceptanceRequest": { "id": "GoogleCloudAiplatformV1beta1CheckPublisherModelEulaAcceptanceRequest", "type": "object", "properties": { "publisherModel": { "description": "Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}`, or `publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}`", "type": "string" } }, "description": "Request message for ModelGardenService.CheckPublisherModelEula." }, "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetOperationMetadata", "type": "object", "description": "Runtime operation information for ModelService.UpdateExplanationDataset.", "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigImportFeaturesAnalysis": { "properties": { "anomalyDetectionBaseline": { "type": "string", "enumDescriptions": [ "Should not be used.", "Choose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.", "Use the statistics generated by the most recent snapshot analysis if exists.", "Use the statistics generated by the previous import features analysis if exists." ], "description": "The baseline used to do anomaly detection for the statistics generated by import features analysis.", "enum": [ "BASELINE_UNSPECIFIED", "LATEST_STATS", "MOST_RECENT_SNAPSHOT_STATS", "PREVIOUS_IMPORT_FEATURES_STATS" ] }, "state": { "type": "string", "enumDescriptions": [ "Should not be used.", "The default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.", "Explicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.", "Explicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config." ], "enum": [ "STATE_UNSPECIFIED", "DEFAULT", "ENABLED", "DISABLED" ], "description": "Whether to enable / disable / inherite default hebavior for import features analysis." } }, "description": "Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.", "id": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigImportFeaturesAnalysis", "type": "object" }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService": { "properties": { "modelName": { "description": "Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`", "type": "string" } }, "description": "Config for Rank Service.", "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService", "type": "object" }, "GoogleCloudAiplatformV1beta1ManualBatchTuningParameters": { "id": "GoogleCloudAiplatformV1beta1ManualBatchTuningParameters", "type": "object", "properties": { "batchSize": { "description": "Immutable. The number of the records (e.g. instances) of the operation given in each batch to a machine replica. Machine type, and size of a single record should be considered when setting this parameter, higher value speeds up the batch operation's execution, but too high value will result in a whole batch not fitting in a machine's memory, and the whole operation will fail. The default value is 64.", "format": "int32", "type": "integer" } }, "description": "Manual batch tuning parameters." }, "GoogleCloudAiplatformV1beta1AddExecutionEventsResponse": { "description": "Response message for MetadataService.AddExecutionEvents.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1AddExecutionEventsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ListDataItemsResponse": { "id": "GoogleCloudAiplatformV1beta1ListDataItemsResponse", "type": "object", "properties": { "dataItems": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DataItem" }, "description": "A list of DataItems that matches the specified filter in the request." }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "description": "Response message for DatasetService.ListDataItems." }, "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityTraceScope": { "id": "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityTraceScope", "type": "object", "properties": { "filter": { "description": "Optional. A list of predicates to filter traces. Multiple predicates are combined using AND. The maximum number of predicates is 10.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityTraceScopePredicate" } } }, "description": "If chosen, the online evaluator will evaluate single traces matching specified `filter`." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassification": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassification", "type": "object", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs" }, "metadata": { "description": "The metadata information.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata" } }, "description": "A TrainingJob that trains and uploads an AutoML Image Classification Model." }, "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigVertexPredictionEndpoint": { "description": "Config representing a model hosted on Vertex Prediction Endpoint.", "properties": { "model": { "readOnly": true, "type": "string", "description": "Output only. The resource name of the model that is deployed on the endpoint. Present only when the endpoint is not a publisher model. Pattern: `projects/{project}/locations/{location}/models/{model}`" }, "modelVersionId": { "description": "Output only. Version ID of the model that is deployed on the endpoint. Present only when the endpoint is not a publisher model.", "type": "string", "readOnly": true }, "endpoint": { "description": "Required. The endpoint resource name. Format: `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigVertexPredictionEndpoint", "type": "object" }, "GoogleCloudAiplatformV1beta1Measurement": { "description": "A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.", "properties": { "elapsedDuration": { "readOnly": true, "type": "string", "format": "google-duration", "description": "Output only. Time that the Trial has been running at the point of this Measurement." }, "stepCount": { "type": "string", "readOnly": true, "description": "Output only. The number of steps the machine learning model has been trained for. Must be non-negative.", "format": "int64" }, "metrics": { "description": "Output only. A list of metrics got by evaluating the objective functions using suggested Parameter values.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MeasurementMetric" }, "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1Measurement", "type": "object" }, "GoogleCloudAiplatformV1beta1DataLabelingJob": { "id": "GoogleCloudAiplatformV1beta1DataLabelingJob", "type": "object", "properties": { "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for each DataLabelingJob: * \"aiplatform.googleapis.com/schema\": output only, its value is the inputs_schema's title." }, "inputs": { "description": "Required. Input config parameters for the DataLabelingJob.", "type": "any" }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this DataLabelingJob was updated most recently.", "format": "google-datetime" }, "error": { "description": "Output only. DataLabelingJob errors. It is only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when this DataLabelingJob was created.", "readOnly": true, "type": "string" }, "inputsSchemaUri": { "description": "Required. Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.", "type": "string" }, "encryptionSpec": { "description": "Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.", "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" }, "annotationLabels": { "description": "Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", "type": "object", "additionalProperties": { "type": "string" } }, "labelingProgress": { "type": "integer", "readOnly": true, "description": "Output only. Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.", "format": "int32" }, "name": { "description": "Output only. Resource name of the DataLabelingJob.", "type": "string", "readOnly": true }, "labelerCount": { "format": "int32", "description": "Required. Number of labelers to work on each DataItem.", "type": "integer" }, "currentSpend": { "description": "Output only. Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.", "readOnly": true, "$ref": "GoogleTypeMoney" }, "instructionUri": { "description": "Required. The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.", "type": "string" }, "specialistPools": { "type": "array", "items": { "type": "string" }, "description": "The SpecialistPools' resource names associated with this job." }, "state": { "description": "Output only. The detailed state of the job.", "enum": [ "JOB_STATE_UNSPECIFIED", "JOB_STATE_QUEUED", "JOB_STATE_PENDING", "JOB_STATE_RUNNING", "JOB_STATE_SUCCEEDED", "JOB_STATE_FAILED", "JOB_STATE_CANCELLING", "JOB_STATE_CANCELLED", "JOB_STATE_PAUSED", "JOB_STATE_EXPIRED", "JOB_STATE_UPDATING", "JOB_STATE_PARTIALLY_SUCCEEDED" ], "type": "string", "enumDescriptions": [ "The job state is unspecified.", "The job has been just created or resumed and processing has not yet begun.", "The service is preparing to run the job.", "The job is in progress.", "The job completed successfully.", "The job failed.", "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "The job has been cancelled.", "The job has been stopped, and can be resumed.", "The job has expired.", "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", "The job is partially succeeded, some results may be missing due to errors." ], "readOnly": true }, "activeLearningConfig": { "description": "Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.", "$ref": "GoogleCloudAiplatformV1beta1ActiveLearningConfig" }, "displayName": { "description": "Required. The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.", "type": "string" }, "datasets": { "type": "array", "items": { "type": "string" }, "description": "Required. Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" } }, "description": "DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:" }, "GoogleCloudAiplatformV1beta1AggregationOutput": { "properties": { "dataset": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationDataset", "description": "The dataset used for evaluation & aggregation." }, "aggregationResults": { "description": "One AggregationResult per metric.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1AggregationResult" } } }, "description": "The aggregation result for the entire dataset and all metrics.", "id": "GoogleCloudAiplatformV1beta1AggregationOutput", "type": "object" }, "GoogleCloudAiplatformV1beta1SessionEvent": { "description": "An event represents a message from either the user or agent.", "properties": { "content": { "$ref": "GoogleCloudAiplatformV1beta1Content", "description": "Optional. Content of the event provided by the author." }, "errorCode": { "description": "Optional. Error code if the response is an error. Code varies by model.", "type": "string" }, "actions": { "$ref": "GoogleCloudAiplatformV1beta1EventActions", "description": "Optional. Actions executed by the agent." }, "rawEvent": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. Weakly typed raw event data in proto struct format." }, "invocationId": { "description": "Required. The invocation id of the event, multiple events can have the same invocation id.", "type": "string" }, "eventMetadata": { "$ref": "GoogleCloudAiplatformV1beta1EventMetadata", "description": "Optional. Metadata relating to this event." }, "errorMessage": { "description": "Optional. Error message if the response is an error.", "type": "string" }, "timestamp": { "type": "string", "description": "Required. Timestamp when the event was created on client side.", "format": "google-datetime" }, "name": { "description": "Identifier. The resource name of the event. Format:`projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}/events/{event}`.", "type": "string" }, "author": { "description": "Required. The name of the agent that sent the event, or user.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SessionEvent", "type": "object" }, "GoogleCloudAiplatformV1beta1StructFieldValue": { "properties": { "name": { "description": "Name of the field in the struct feature.", "type": "string" }, "value": { "$ref": "GoogleCloudAiplatformV1beta1FeatureValue", "description": "The value for this field." } }, "description": "One field of a Struct (or object) type feature value.", "id": "GoogleCloudAiplatformV1beta1StructFieldValue", "type": "object" }, "GoogleCloudAiplatformV1beta1CompleteTrialRequest": { "properties": { "finalMeasurement": { "$ref": "GoogleCloudAiplatformV1beta1Measurement", "description": "Optional. If provided, it will be used as the completed Trial's final_measurement; Otherwise, the service will auto-select a previously reported measurement as the final-measurement" }, "trialInfeasible": { "description": "Optional. True if the Trial cannot be run with the given Parameter, and final_measurement will be ignored.", "type": "boolean" }, "infeasibleReason": { "description": "Optional. A human readable reason why the trial was infeasible. This should only be provided if `trial_infeasible` is true.", "type": "string" } }, "description": "Request message for VizierService.CompleteTrial.", "id": "GoogleCloudAiplatformV1beta1CompleteTrialRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfig": { "type": "object", "deprecated": true, "id": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfig", "properties": { "bruteForceConfig": { "description": "Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search.", "$ref": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigBruteForceConfig" }, "distanceMeasureType": { "type": "string", "enumDescriptions": [ "Should not be set.", "Euclidean (L_2) Distance.", "Cosine Distance. Defined as 1 - cosine similarity. We strongly suggest using DOT_PRODUCT_DISTANCE + UNIT_L2_NORM instead of COSINE distance. Our algorithms have been more optimized for DOT_PRODUCT distance which, when combined with UNIT_L2_NORM, is mathematically equivalent to COSINE distance and results in the same ranking.", "Dot Product Distance. Defined as a negative of the dot product." ], "enum": [ "DISTANCE_MEASURE_TYPE_UNSPECIFIED", "SQUARED_L2_DISTANCE", "COSINE_DISTANCE", "DOT_PRODUCT_DISTANCE" ], "description": "Optional. The distance measure used in nearest neighbor search." }, "treeAhConfig": { "description": "Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396", "$ref": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigTreeAHConfig" }, "embeddingDimension": { "format": "int32", "description": "Optional. The number of dimensions of the input embedding.", "type": "integer" }, "crowdingColumn": { "description": "Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.", "type": "string" }, "embeddingColumn": { "description": "Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search.", "type": "string" }, "filterColumns": { "type": "array", "items": { "type": "string" }, "description": "Optional. Columns of features that're used to filter vector search results." } }, "description": "Deprecated. Use IndexConfig instead." }, "GoogleCloudAiplatformV1beta1BatchCreateFeaturesResponse": { "id": "GoogleCloudAiplatformV1beta1BatchCreateFeaturesResponse", "type": "object", "description": "Response message for FeaturestoreService.BatchCreateFeatures.", "properties": { "features": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Feature" }, "description": "The Features created." } } }, "GoogleCloudAiplatformV1beta1RougeInstance": { "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "reference": { "description": "Required. Ground truth used to compare against the prediction.", "type": "string" } }, "description": "Spec for rouge instance.", "id": "GoogleCloudAiplatformV1beta1RougeInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1Int64Array": { "id": "GoogleCloudAiplatformV1beta1Int64Array", "type": "object", "properties": { "values": { "type": "array", "items": { "format": "int64", "type": "string" }, "description": "A list of int64 values." } }, "description": "A list of int64 values." }, "GoogleCloudAiplatformV1beta1SchemaPredictParamsGroundingConfigSourceEntry": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsGroundingConfigSourceEntry", "type": "object", "properties": { "inlineContext": { "description": "The grounding text passed inline with the Predict API. It can support up to 1 million bytes.", "type": "string" }, "type": { "description": "The type of the grounding checking source.", "enum": [ "UNSPECIFIED", "WEB", "ENTERPRISE", "VERTEX_AI_SEARCH", "INLINE" ], "type": "string", "enumDescriptions": [ "", "Uses Web Search to check the grounding.", "Uses Vertex AI Search to check the grounding. Deprecated. Use VERTEX_AI_SEARCH instead.", "Uses Vertex AI Search to check the grounding", "Uses inline context to check the grounding." ], "enumDeprecated": [ false, false, true, false, false ] }, "enterpriseDatastore": { "description": "The uri of the Vertex AI Search data source. Deprecated. Use vertex_ai_search_datastore instead.", "type": "string", "deprecated": true }, "vertexAiSearchDatastore": { "description": "The uri of the Vertex AI Search data source.", "type": "string" } }, "description": "Single source entry for the grounding checking." }, "GoogleCloudAiplatformV1beta1MachineSpec": { "id": "GoogleCloudAiplatformV1beta1MachineSpec", "type": "object", "description": "Specification of a single machine.", "properties": { "acceleratorCount": { "format": "int32", "description": "The number of accelerators to attach to the machine. For accelerator optimized machine types (https://cloud.google.com/compute/docs/accelerator-optimized-machines), One may set the accelerator_count from 1 to N for machine with N GPUs. If accelerator_count is less than or equal to N / 2, Vertex will co-schedule the replicas of the model into the same VM to save cost. For example, if the machine type is a3-highgpu-8g, which has 8 H100 GPUs, one can set accelerator_count to 1 to 8. If accelerator_count is 1, 2, 3, or 4, Vertex will co-schedule 8, 4, 2, or 2 replicas of the model into the same VM to save cost. When co-scheduling, CPU, memory and storage on the VM will be distributed to replicas on the VM. For example, one can expect a co-scheduled replica requesting 2 GPUs out of a 8-GPU VM will receive 25% of the CPU, memory and storage of the VM. Note that the feature is not compatible with multihost_gpu_node_count. When multihost_gpu_node_count is set, the co-scheduling will not be enabled.", "type": "integer" }, "multihostGpuNodeCount": { "description": "Optional. Immutable. The number of nodes per replica for multihost GPU deployments.", "format": "int32", "type": "integer" }, "minGpuDriverVersion": { "description": "Optional. Immutable. The minimum GPU driver version that this machine requires. For example, \"535.104.06\". If not specified, the default GPU driver version will be used by the underlying infrastructure.", "type": "string" }, "tpuTopology": { "description": "Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: \"2x2x1\").", "type": "string" }, "machineType": { "description": "Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.", "type": "string" }, "acceleratorType": { "type": "string", "enumDescriptions": [ "Unspecified accelerator type, which means no accelerator.", "Deprecated: Nvidia Tesla K80 GPU has reached end of support, see https://cloud.google.com/compute/docs/eol/k80-eol.", "Nvidia Tesla P100 GPU.", "Nvidia Tesla V100 GPU.", "Nvidia Tesla P4 GPU.", "Nvidia Tesla T4 GPU.", "Nvidia Tesla A100 GPU.", "Nvidia A100 80GB GPU.", "Nvidia L4 GPU.", "Nvidia H100 80Gb GPU.", "Nvidia H100 Mega 80Gb GPU.", "Nvidia H200 141Gb GPU.", "Nvidia B200 GPU.", "Nvidia GB200 GPU.", "Nvidia RTX Pro 6000 GPU.", "TPU v2.", "TPU v3.", "TPU v4.", "TPU v5." ], "enumDeprecated": [ false, true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ], "enum": [ "ACCELERATOR_TYPE_UNSPECIFIED", "NVIDIA_TESLA_K80", "NVIDIA_TESLA_P100", "NVIDIA_TESLA_V100", "NVIDIA_TESLA_P4", "NVIDIA_TESLA_T4", "NVIDIA_TESLA_A100", "NVIDIA_A100_80GB", "NVIDIA_L4", "NVIDIA_H100_80GB", "NVIDIA_H100_MEGA_80GB", "NVIDIA_H200_141GB", "NVIDIA_B200", "NVIDIA_GB200", "NVIDIA_RTX_PRO_6000", "TPU_V2", "TPU_V3", "TPU_V4_POD", "TPU_V5_LITEPOD" ], "description": "Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count." }, "reservationAffinity": { "$ref": "GoogleCloudAiplatformV1beta1ReservationAffinity", "description": "Optional. Immutable. Configuration controlling how this resource pool consumes reservation." }, "gpuPartitionSize": { "description": "Optional. Immutable. The Nvidia GPU partition size. When specified, the requested accelerators will be partitioned into smaller GPU partitions. For example, if the request is for 8 units of NVIDIA A100 GPUs, and gpu_partition_size=\"1g.10gb\", the service will create 8 * 7 = 56 partitioned MIG instances. The partition size must be a value supported by the requested accelerator. Refer to [Nvidia GPU Partitioning](https://cloud.google.com/kubernetes-engine/docs/how-to/gpus-multi#multi-instance_gpu_partitions) for the available partition sizes. If set, the accelerator_count should be set to 1.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1CancelPipelineJobRequest": { "id": "GoogleCloudAiplatformV1beta1CancelPipelineJobRequest", "type": "object", "properties": {}, "description": "Request message for PipelineService.CancelPipelineJob." }, "GoogleCloudAiplatformV1beta1Index": { "properties": { "updateTime": { "description": "Output only. Timestamp when this Index was most recently updated. This also includes any update to the contents of the Index. Note that Operations working on this Index may have their Operations.metadata.generic_metadata.update_time a little after the value of this timestamp, yet that does not mean their results are not already reflected in the Index. Result of any successfully completed Operation on the Index is reflected in it.", "format": "google-datetime", "type": "string", "readOnly": true }, "metadataSchemaUri": { "description": "Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Index, that is specific to it. Unset if the Index does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", "type": "string" }, "metadata": { "description": "An additional information about the Index; the schema of the metadata can be found in metadata_schema.", "type": "any" }, "deployedIndexes": { "description": "Output only. The pointers to DeployedIndexes created from this Index. An Index can be only deleted if all its DeployedIndexes had been undeployed first.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DeployedIndexRef" } }, "labels": { "description": "The labels with user-defined metadata to organize your Indexes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", "type": "object", "additionalProperties": { "type": "string" } }, "description": { "description": "The description of the Index.", "type": "string" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this Index was created." }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "indexUpdateMethod": { "enum": [ "INDEX_UPDATE_METHOD_UNSPECIFIED", "BATCH_UPDATE", "STREAM_UPDATE" ], "description": "Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default.", "type": "string", "enumDescriptions": [ "Should not be used.", "BatchUpdate: user can call UpdateIndex with files on Cloud Storage of Datapoints to update.", "StreamUpdate: user can call UpsertDatapoints/DeleteDatapoints to update the Index and the updates will be applied in corresponding DeployedIndexes in nearly real-time." ] }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Immutable. Customer-managed encryption key spec for an Index. If set, this Index and all sub-resources of this Index will be secured by this key." }, "name": { "description": "Output only. The resource name of the Index.", "readOnly": true, "type": "string" }, "indexStats": { "description": "Output only. Stats of the index resource.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1IndexStats" }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "satisfiesPzs": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "displayName": { "description": "Required. The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" } }, "description": "A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search.", "id": "GoogleCloudAiplatformV1beta1Index", "type": "object" }, "GoogleCloudAiplatformV1beta1DeleteOnlineEvaluatorOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1DeleteOnlineEvaluatorOperationMetadata", "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Generic operation metadata." } }, "description": "Metadata for the DeleteOnlineEvaluator operation." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs": { "properties": {}, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs", "type": "object" }, "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec": { "id": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec", "type": "object", "description": "Represent spec for train trials.", "properties": { "trainTrialJobSpec": { "description": "Required. The spec of a train trial job. The same spec applies to all train trials.", "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec" }, "maxParallelTrialCount": { "description": "Required. The maximum number of trials to run in parallel.", "format": "int32", "type": "integer" }, "frequency": { "description": "Required. Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1beta1SchemaVideoDatasetMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaVideoDatasetMetadata", "type": "object", "description": "The metadata of Datasets that contain Video DataItems.", "properties": { "dataItemSchemaUri": { "description": "Points to a YAML file stored on Google Cloud Storage describing payload of the Video DataItems that belong to this Dataset.", "type": "string" }, "gcsBucket": { "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetrics": { "properties": { "precisionWindowLength": { "type": "string", "format": "google-duration", "description": "This VideoActionMetrics is calculated based on this prediction window length. If the predicted action's timestamp is inside the time window whose center is the ground truth action's timestamp with this specific length, the prediction result is treated as a true positive." }, "meanAveragePrecision": { "type": "number", "description": "The mean average precision.", "format": "float" }, "confidenceMetrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics" }, "description": "Metrics for each label-match confidence_threshold from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99." } }, "description": "The Evaluation metrics given a specific precision_window_length.", "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetrics", "type": "object" }, "GoogleCloudAiplatformV1beta1TunedModelCheckpoint": { "properties": { "endpoint": { "description": "The Endpoint resource name that the checkpoint is deployed to. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`.", "type": "string" }, "checkpointId": { "description": "The ID of the checkpoint.", "type": "string" }, "step": { "format": "int64", "description": "The step of the checkpoint.", "type": "string" }, "epoch": { "description": "The epoch of the checkpoint.", "format": "int64", "type": "string" } }, "description": "TunedModelCheckpoint for the Tuned Model of a Tuning Job.", "id": "GoogleCloudAiplatformV1beta1TunedModelCheckpoint", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolConfig": { "id": "GoogleCloudAiplatformV1beta1ToolConfig", "type": "object", "description": "Tool config. This config is shared for all tools provided in the request.", "properties": { "retrievalConfig": { "description": "Optional. Retrieval config.", "$ref": "GoogleCloudAiplatformV1beta1RetrievalConfig" }, "functionCallingConfig": { "$ref": "GoogleCloudAiplatformV1beta1FunctionCallingConfig", "description": "Optional. Function calling config." } } }, "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerMonthUsageData": { "id": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerMonthUsageData", "type": "object", "properties": { "userUsageData": { "description": "Usage data for each user in the given month.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerUserUsageData" } } }, "description": "Per month usage data" }, "GoogleCloudAiplatformV1beta1EvaluationResults": { "properties": { "lossAnalysisResults": { "description": "Output only. The results of the auto-loss analysis performed on the eval set associated with the run.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LossAnalysisResult" } }, "summaryMetrics": { "description": "Optional. The summary metrics for the evaluation run.", "$ref": "GoogleCloudAiplatformV1beta1SummaryMetrics" }, "evaluationSet": { "description": "The evaluation set where item level results are stored.", "type": "string" } }, "description": "The results of the evaluation run.", "id": "GoogleCloudAiplatformV1beta1EvaluationResults", "type": "object" }, "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigConsolidationConfig": { "id": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigConsolidationConfig", "type": "object", "properties": { "revisionsPerCandidateCount": { "type": "integer", "format": "int32", "description": "Optional. Represents the maximum number of revisions to consider for each candidate memory. If not set, then the default value (1) will be used, which means that only the latest revision will be considered." } }, "description": "Represents configuration for customizing how memories are consolidated." }, "GoogleCloudAiplatformV1beta1ExplainRequest": { "properties": { "instances": { "type": "array", "items": { "type": "any" }, "description": "Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri." }, "deployedModelId": { "description": "If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split.", "type": "string" }, "parameters": { "description": "The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.", "type": "any" }, "concurrentExplanationSpecOverride": { "description": "Optional. This field is the same as the one above, but supports multiple explanations to occur in parallel. The key can be any string. Each override will be run against the model, then its explanations will be grouped together. Note - these explanations are run **In Addition** to the default Explanation in the deployed model.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpecOverride" } }, "explanationSpecOverride": { "description": "If specified, overrides the explanation_spec of the DeployedModel. Can be used for explaining prediction results with different configurations, such as: - Explaining top-5 predictions results as opposed to top-1; - Increasing path count or step count of the attribution methods to reduce approximate errors; - Using different baselines for explaining the prediction results.", "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpecOverride" } }, "description": "Request message for PredictionService.Explain.", "id": "GoogleCloudAiplatformV1beta1ExplainRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringAnomaly": { "description": "Represents a single model monitoring anomaly.", "properties": { "algorithm": { "description": "Algorithm used to calculated the metrics, eg: jensen_shannon_divergence, l_infinity.", "type": "string" }, "modelMonitoringJob": { "description": "Model monitoring job resource name.", "type": "string" }, "tabularAnomaly": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAnomalyTabularAnomaly", "description": "Tabular anomaly." } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAnomaly", "type": "object" }, "GoogleCloudAiplatformV1beta1RaySpec": { "id": "GoogleCloudAiplatformV1beta1RaySpec", "type": "object", "description": "Configuration information for the Ray cluster. For experimental launch, Ray cluster creation and Persistent cluster creation are 1:1 mapping: We will provision all the nodes within the Persistent cluster as Ray nodes.", "properties": { "resourcePoolImages": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { \"ray_head_node_pool\": \"head image\" \"ray_worker_node_pool1\": \"worker image\" \"ray_worker_node_pool2\": \"another worker image\" }" }, "rayMetricSpec": { "$ref": "GoogleCloudAiplatformV1beta1RayMetricSpec", "description": "Optional. Ray metrics configurations." }, "headNodeResourcePoolId": { "description": "Optional. This will be used to indicate which resource pool will serve as the Ray head node(the first node within that pool). Will use the machine from the first workerpool as the head node by default if this field isn't set.", "type": "string" }, "nfsMounts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NfsMount" }, "description": "Optional. Use if you want to mount to any NFS storages." }, "rayLogsSpec": { "$ref": "GoogleCloudAiplatformV1beta1RayLogsSpec", "description": "Optional. OSS Ray logging configurations." }, "imageUri": { "description": "Optional. Default image for user to choose a preferred ML framework (for example, TensorFlow or Pytorch) by choosing from [Vertex prebuilt images](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). Either this or the resource_pool_images is required. Use this field if you need all the resource pools to have the same Ray image. Otherwise, use the {@code resource_pool_images} field.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec", "type": "object", "description": "Data drift monitoring spec. Data drift measures the distribution distance between the current dataset and a baseline dataset. A typical use case is to detect data drift between the recent production serving dataset and the training dataset, or to compare the recent production dataset with a dataset from a previous period.", "properties": { "features": { "description": "Feature names / Prediction output names interested in monitoring. These should be a subset of the input feature names or prediction output names specified in the monitoring schema. If the field is not specified all features / prediction outputs outlied in the monitoring schema will be used.", "type": "array", "items": { "type": "string" } }, "categoricalMetricType": { "description": "Supported metrics type: * l_infinity * jensen_shannon_divergence", "type": "string" }, "numericMetricType": { "description": "Supported metrics type: * jensen_shannon_divergence", "type": "string" }, "defaultCategoricalAlertCondition": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition", "description": "Default alert condition for all the categorical features." }, "defaultNumericAlertCondition": { "description": "Default alert condition for all the numeric features.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition" }, "featureAlertConditions": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition" }, "description": "Per feature alert condition will override default alert condition." } } }, "GoogleCloudAiplatformV1beta1FunctionResponseBlob": { "properties": { "displayName": { "description": "Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.", "type": "string" }, "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" }, "data": { "type": "string", "format": "byte", "description": "Required. Raw bytes." } }, "description": "Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field.", "id": "GoogleCloudAiplatformV1beta1FunctionResponseBlob", "type": "object" }, "GoogleCloudAiplatformV1beta1RecommendSpecResponseRecommendation": { "properties": { "userQuotaState": { "enum": [ "QUOTA_STATE_UNSPECIFIED", "QUOTA_STATE_USER_HAS_QUOTA", "QUOTA_STATE_NO_USER_QUOTA" ], "description": "Output only. The user accelerator quota state.", "readOnly": true, "type": "string", "enumDescriptions": [ "Unspecified quota state. Quota information not available.", "User has enough accelerator quota for the machine type.", "User does not have enough accelerator quota for the machine type." ] }, "region": { "description": "The region for the deployment spec (machine).", "type": "string" }, "spec": { "description": "Output only. The machine and model container specs.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1RecommendSpecResponseMachineAndModelContainerSpec" } }, "description": "Recommendation of one deployment option for the given custom weights model in one region. Contains the machine and container spec, and user accelerator quota state.", "id": "GoogleCloudAiplatformV1beta1RecommendSpecResponseRecommendation", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTftFeatureImportance": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTftFeatureImportance", "type": "object", "properties": { "horizonWeights": { "type": "array", "items": { "type": "number", "format": "float" } }, "attributeColumns": { "type": "array", "items": { "type": "string" } }, "contextWeights": { "type": "array", "items": { "type": "number", "format": "float" }, "description": "TFT feature importance values. Each pair for {context/horizon/attribute} should have the same shape since the weight corresponds to the column names." }, "horizonColumns": { "type": "array", "items": { "type": "string" } }, "contextColumns": { "type": "array", "items": { "type": "string" } }, "attributeWeights": { "type": "array", "items": { "format": "float", "type": "number" } } } }, "GoogleCloudAiplatformV1beta1TrajectoryExactMatchSpec": { "id": "GoogleCloudAiplatformV1beta1TrajectoryExactMatchSpec", "type": "object", "properties": {}, "description": "Spec for TrajectoryExactMatch metric - returns 1 if tool calls in the reference trajectory exactly match the predicted trajectory, else 0." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation", "type": "object", "properties": { "columnName": { "type": "string" } }, "description": "Treats the column as text array and performs following transformation functions. * Concatenate all text values in the array into a single text value using a space (\" \") as a delimiter, and then treat the result as a single text value. Apply the transformations for Text columns. * Empty arrays treated as an empty text." }, "GoogleCloudAiplatformV1beta1ModelMonitoringOutputSpec": { "properties": { "gcsBaseDirectory": { "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", "description": "Google Cloud Storage base folder path for metrics, error logs, etc." } }, "description": "Specification for the export destination of monitoring results, including metrics, logs, etc.", "id": "GoogleCloudAiplatformV1beta1ModelMonitoringOutputSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsResponse": { "id": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsResponse", "type": "object", "description": "Response message for TensorboardService.BatchCreateTensorboardRuns.", "properties": { "tensorboardRuns": { "description": "The created TensorboardRuns.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" } } } }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry", "type": "object", "properties": { "confidenceThreshold": { "format": "float", "description": "Metrics are computed with an assumption that the model never returns predictions with score lower than this value.", "type": "number" }, "confusionMatrix": { "description": "Confusion matrix for the given confidence threshold.", "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix" }, "recall": { "format": "float", "description": "Recall (True Positive Rate) for the given confidence threshold.", "type": "number" }, "precision": { "type": "number", "format": "float", "description": "Precision for the given confidence threshold." }, "diceScoreCoefficient": { "description": "DSC or the F1 score, The harmonic mean of recall and precision.", "format": "float", "type": "number" }, "iouScore": { "type": "number", "description": "The intersection-over-union score. The measure of overlap of the annotation's category mask with ground truth category mask on the DataItem.", "format": "float" } } }, "GoogleCloudAiplatformV1beta1RetrievalMetadata": { "description": "Metadata related to the retrieval grounding source. This is part of the `GroundingMetadata` returned when grounding is enabled.", "properties": { "googleSearchDynamicRetrievalScore": { "format": "float", "description": "Optional. A score indicating how likely it is that a Google Search query could help answer the prompt. The score is in the range of `[0, 1]`. A score of 1 means the model is confident that a search will be helpful, and 0 means it is not. This score is populated only when Google Search grounding and dynamic retrieval are enabled. The score is used to determine whether to trigger a search.", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1RetrievalMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1RetrieveMemoriesRequest": { "id": "GoogleCloudAiplatformV1beta1RetrieveMemoriesRequest", "type": "object", "properties": { "simpleRetrievalParams": { "description": "Parameters for simple (non-similarity search) retrieval.", "$ref": "GoogleCloudAiplatformV1beta1RetrieveMemoriesRequestSimpleRetrievalParams" }, "filter": { "description": "Optional. The standard list filter that will be applied to the retrieved memories. More detail in [AIP-160](https://google.aip.dev/160). Supported fields: * `fact` * `create_time` * `update_time` * `topics` (i.e. `topics.custom_memory_topic_label: \"example topic\" OR topics.managed_memory_topic: USER_PREFERENCES`)", "type": "string" }, "similaritySearchParams": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveMemoriesRequestSimilaritySearchParams", "description": "Parameters for semantic similarity search based retrieval." }, "scope": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Required. The scope of the memories to retrieve. A memory must have exactly the same scope (`Memory.scope`) as the scope provided here to be retrieved (same keys and values). Order does not matter, but it is case-sensitive." }, "filterGroups": { "description": "Optional. Metadata filters that will be applied to the retrieved memories' `metadata` using OR logic. Filters are defined using disjunctive normal form (OR of ANDs). For example: `filter_groups: [{filters: [{key: \"author\", value: {string_value: \"agent 123\"}, op: EQUAL}]}, {filters: [{key: \"label\", value: {string_value: \"travel\"}, op: EQUAL}, {key: \"author\", value: {string_value: \"agent 321\"}, op: EQUAL}]}]` would be equivalent to the logical expression: `(metadata.author = \"agent 123\" OR (metadata.label = \"travel\" AND metadata.author = \"agent 321\"))`.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryConjunctionFilter" } }, "memoryTypes": { "description": "Optional. Specifies the types of memories to retrieve. If this field is empty or not provided, the request will default to retrieving only memories of type `NATURAL_LANGUAGE_COLLECTION`. If populated, the request will retrieve memories matching any of the specified `MemoryType` values.", "type": "array", "items": { "type": "string", "enumDescriptions": [ "Represents an unspecified memory type. This value should not be used.", "Indicates belonging to a collection of natural language memories.", "Indicates belonging to a structured profile." ], "enum": [ "MEMORY_TYPE_UNSPECIFIED", "NATURAL_LANGUAGE_COLLECTION", "STRUCTURED_PROFILE" ] } } }, "description": "Request message for MemoryBankService.RetrieveMemories." }, "GoogleCloudAiplatformV1beta1RuntimeArtifact": { "description": "The definition of a runtime artifact.", "properties": { "name": { "description": "The name of an artifact.", "type": "string" }, "uri": { "description": "The URI of the artifact.", "type": "string" }, "customProperties": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1Value" }, "deprecated": true, "description": "The custom properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead." }, "type": { "$ref": "GoogleCloudAiplatformV1beta1ArtifactTypeSchema", "description": "The type of the artifact." }, "metadata": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Properties of the Artifact." }, "properties": { "deprecated": true, "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1Value" }, "description": "The properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead." } }, "id": "GoogleCloudAiplatformV1beta1RuntimeArtifact", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigAgentToAnywhereConfig": { "description": "Configuration for traffic originating from a Reasoning Engine.", "properties": { "agentGateway": { "description": "Required. The resource name of the Agent Gateway for outbound traffic. It must be set to a Google-managed gateway whose `governed_access_path` is `AGENT_TO_ANYWHERE`. Format: `projects/{project}/locations/{location}/agentGateways/{agent_gateway}`", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigAgentToAnywhereConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineRuntimeRevision": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineRuntimeRevision", "type": "object", "description": "ReasoningEngineRuntimeRevision is a specific version of the runtime related part of ReasoningEngine. Contains only the fields that are revision specific.", "properties": { "name": { "description": "Identifier. The resource name of the ReasoningEngineRuntimeRevision. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/runtimeRevisions/{runtime_revision}`", "type": "string" }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this ReasoningEngineRuntimeRevision was created.", "format": "google-datetime" }, "spec": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpec", "description": "Immutable. Configurations of the ReasoningEngineRuntimeRevision. Contains only revision specific fields." }, "state": { "enum": [ "STATE_UNSPECIFIED", "ACTIVE", "DEPRECATED" ], "description": "Output only. The state of the revision.", "readOnly": true, "type": "string", "enumDescriptions": [ "The unspecified state.", "Is deployed and ready to be used.", "Is deprecated, may not be used, only preserved for historical purposes." ] } } }, "GoogleCloudAiplatformV1beta1SampledShapleyAttribution": { "id": "GoogleCloudAiplatformV1beta1SampledShapleyAttribution", "type": "object", "properties": { "pathCount": { "type": "integer", "description": "Required. The number of feature permutations to consider when approximating the Shapley values. Valid range of its value is [1, 50], inclusively.", "format": "int32" } }, "description": "An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features." }, "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInstance": { "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInstance", "type": "object", "description": "Spec for question answering quality instance.", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "instruction": { "description": "Required. Question Answering prompt for LLM.", "type": "string" }, "context": { "description": "Required. Text to answer the question.", "type": "string" }, "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistributionDatasetBucket": { "description": "Dataset bucket used to create a histogram for the distribution given a population of values.", "properties": { "left": { "type": "number", "readOnly": true, "description": "Output only. Left bound of the bucket.", "format": "double" }, "right": { "format": "double", "description": "Output only. Right bound of the bucket.", "readOnly": true, "type": "number" }, "count": { "readOnly": true, "type": "number", "format": "double", "description": "Output only. Number of values in the bucket." } }, "id": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistributionDatasetBucket", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureViewOptimizedConfig": { "description": "Configuration for FeatureViews created in Optimized FeatureOnlineStore.", "properties": { "automaticResources": { "description": "Optional. A description of resources that the FeatureView uses, which to large degree are decided by Vertex AI, and optionally allows only a modest additional configuration. If min_replica_count is not set, the default value is 2. If max_replica_count is not set, the default value is 6. The max allowed replica count is 1000.", "$ref": "GoogleCloudAiplatformV1beta1AutomaticResources" } }, "id": "GoogleCloudAiplatformV1beta1FeatureViewOptimizedConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolOperationMetadata": { "description": "Runtime operation information for CreateDeploymentResourcePool method.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The operation generic information." } }, "id": "GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1QuestionAnsweringQualitySpec": { "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualitySpec", "type": "object", "description": "Spec for question answering quality score metric.", "properties": { "useReference": { "description": "Optional. Whether to use instance.reference to compute question answering quality.", "type": "boolean" }, "version": { "description": "Optional. Which version to use for evaluation.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1beta1DoubleArray": { "id": "GoogleCloudAiplatformV1beta1DoubleArray", "type": "object", "description": "A list of double values.", "properties": { "values": { "type": "array", "items": { "format": "double", "type": "number" }, "description": "A list of double values." } } }, "GoogleCloudAiplatformV1beta1CometResult": { "id": "GoogleCloudAiplatformV1beta1CometResult", "type": "object", "properties": { "score": { "description": "Output only. Comet score. Range depends on version.", "format": "float", "type": "number", "readOnly": true } }, "description": "Spec for Comet result - calculates the comet score for the given instance using the version specified in the spec." }, "GoogleCloudAiplatformV1beta1FeatureValueDestination": { "description": "A destination location for Feature values and format.", "properties": { "bigqueryDestination": { "description": "Output in BigQuery format. BigQueryDestination.output_uri in FeatureValueDestination.bigquery_destination must refer to a table.", "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination" }, "csvDestination": { "$ref": "GoogleCloudAiplatformV1beta1CsvDestination", "description": "Output in CSV format. Array Feature value types are not allowed in CSV format." }, "tfrecordDestination": { "description": "Output in TFRecord format. Below are the mapping from Feature value type in Featurestore to Feature value type in TFRecord: Value type in Featurestore | Value type in TFRecord DOUBLE, DOUBLE_ARRAY | FLOAT_LIST INT64, INT64_ARRAY | INT64_LIST STRING, STRING_ARRAY, BYTES | BYTES_LIST true -\u003e byte_string(\"true\"), false -\u003e byte_string(\"false\") BOOL, BOOL_ARRAY (true, false) | BYTES_LIST", "$ref": "GoogleCloudAiplatformV1beta1TFRecordDestination" } }, "id": "GoogleCloudAiplatformV1beta1FeatureValueDestination", "type": "object" }, "GoogleCloudAiplatformV1beta1PredictRequest": { "id": "GoogleCloudAiplatformV1beta1PredictRequest", "type": "object", "properties": { "instances": { "type": "array", "items": { "type": "any" }, "description": "Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri." }, "parameters": { "description": "The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.", "type": "any" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The user labels for Imagen billing usage only. Only Imagen supports labels. For other use cases, it will be ignored." } }, "description": "Request message for PredictionService.Predict." }, "CloudAiLargeModelsVisionMedia": { "properties": { "video": { "$ref": "CloudAiLargeModelsVisionVideo", "description": "Video" }, "image": { "description": "Image.", "$ref": "CloudAiLargeModelsVisionImage" } }, "description": "Media.", "id": "CloudAiLargeModelsVisionMedia", "type": "object" }, "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotationAttributedItem": { "description": "Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type.", "properties": { "annotationResourceName": { "description": "The unique ID for each annotation. Used by FE to allocate the annotation in DB.", "type": "string" }, "distance": { "type": "number", "format": "double", "description": "The distance of this item to the annotation." } }, "id": "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotationAttributedItem", "type": "object" }, "GoogleCloudAiplatformV1beta1CometInput": { "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1CometSpec", "description": "Required. Spec for comet metric." }, "instance": { "$ref": "GoogleCloudAiplatformV1beta1CometInstance", "description": "Required. Comet instance." } }, "description": "Input for Comet metric.", "id": "GoogleCloudAiplatformV1beta1CometInput", "type": "object" }, "GoogleCloudAiplatformV1beta1OutputInfo": { "id": "GoogleCloudAiplatformV1beta1OutputInfo", "type": "object", "properties": { "gcsOutputDirectory": { "readOnly": true, "type": "string", "description": "Output only. The full path of the Cloud Storage directory created, into which the evaluation results and aggregation results are written." } }, "description": "Describes the info for output of EvaluationService." }, "GoogleCloudAiplatformV1beta1SummarizationVerbosityInput": { "description": "Input for summarization verbosity metric.", "properties": { "instance": { "description": "Required. Summarization verbosity instance.", "$ref": "GoogleCloudAiplatformV1beta1SummarizationVerbosityInstance" }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1SummarizationVerbositySpec", "description": "Required. Spec for summarization verbosity score metric." } }, "id": "GoogleCloudAiplatformV1beta1SummarizationVerbosityInput", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetRequest": { "properties": { "examples": { "description": "The example config containing the location of the dataset.", "$ref": "GoogleCloudAiplatformV1beta1Examples" } }, "description": "Request message for ModelService.UpdateExplanationDataset.", "id": "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ListPipelineJobsResponse": { "description": "Response message for PipelineService.ListPipelineJobs", "properties": { "pipelineJobs": { "description": "List of PipelineJobs in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListPipelineJobsRequest.page_token to obtain that page.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListPipelineJobsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInput": { "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInput", "type": "object", "properties": { "instance": { "description": "Required. Question answering correctness instance.", "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInstance" }, "metricSpec": { "description": "Required. Spec for question answering correctness score metric.", "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessSpec" } }, "description": "Input for question answering correctness metric." }, "GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest": { "properties": { "requests": { "description": "Required. The request message specifying the Features to create. All Features must be created under the same parent EntityType / FeatureGroup. The `parent` field in each child request message can be omitted. If `parent` is set in a child request, then the value must match the `parent` value in this request message.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1CreateFeatureRequest" } } }, "description": "Request message for FeaturestoreService.BatchCreateFeatures. Request message for FeatureRegistryService.BatchCreateFeatures.", "id": "GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1AskContextsResponse": { "id": "GoogleCloudAiplatformV1beta1AskContextsResponse", "type": "object", "description": "Response message for VertexRagService.AskContexts.", "properties": { "response": { "description": "The Retrieval Response.", "type": "string" }, "contexts": { "description": "The contexts of the query.", "$ref": "GoogleCloudAiplatformV1beta1RagContexts" } } }, "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteResponseWriteResponse": { "id": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteResponseWriteResponse", "type": "object", "properties": { "dataKey": { "description": "What key is this write response associated with.", "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKey" }, "onlineStoreWriteTime": { "description": "When the feature values were written to the online store. If FeatureViewDirectWriteResponse.status is not OK, this field is not populated.", "format": "google-datetime", "type": "string" } }, "description": "Details about the write for each key." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation", "type": "object", "description": "Training pipeline will infer the proper transformation based on the statistic of dataset.", "properties": { "columnName": { "type": "string" } } }, "GoogleCloudAiplatformV1beta1FunctionResponseFileData": { "description": "URI based data for function response.", "properties": { "displayName": { "description": "Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.", "type": "string" }, "fileUri": { "description": "Required. URI.", "type": "string" }, "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1FunctionResponseFileData", "type": "object" }, "CloudAiLargeModelsVisionImageImageSize": { "properties": { "channels": { "type": "integer", "format": "int32" }, "width": { "type": "integer", "format": "int32" }, "height": { "type": "integer", "format": "int32" } }, "description": "Image size.", "id": "CloudAiLargeModelsVisionImageImageSize", "type": "object" }, "GoogleTypeMoney": { "id": "GoogleTypeMoney", "type": "object", "description": "Represents an amount of money with its currency type.", "properties": { "units": { "type": "string", "description": "The whole units of the amount. For example if `currencyCode` is `\"USD\"`, then 1 unit is one US dollar.", "format": "int64" }, "nanos": { "type": "integer", "format": "int32", "description": "Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If `units` is positive, `nanos` must be positive or zero. If `units` is zero, `nanos` can be positive, zero, or negative. If `units` is negative, `nanos` must be negative or zero. For example $-1.75 is represented as `units`=-1 and `nanos`=-750,000,000." }, "currencyCode": { "description": "The three-letter currency code defined in ISO 4217.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservability": { "id": "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservability", "type": "object", "description": "Data source for the OnlineEvaluator, based on GCP Observability stack (Cloud Trace & Cloud Logging).", "properties": { "traceScope": { "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityTraceScope", "description": "Scope online evaluation to single traces." }, "openTelemetry": { "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityOpenTelemetry", "description": "Data source follows OpenTelemetry convention." }, "logView": { "description": "Optional. Optional log view that will be used to query logs. If empty, the `_Default` view will be used.", "type": "string" }, "traceView": { "description": "Optional. Optional trace view that will be used to query traces. If empty, the `_Default` view will be used.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1FeatureOnlineStore": { "description": "Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container.", "properties": { "createTime": { "description": "Output only. Timestamp when this FeatureOnlineStore was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this FeatureOnlineStore was last updated." }, "labels": { "description": "Optional. The labels with user-defined metadata to organize your FeatureOnlineStore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", "type": "object", "additionalProperties": { "type": "string" } }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Optional. Customer-managed encryption key spec for data storage. If set, online store will be secured by this key." }, "bigtable": { "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtable", "description": "Contains settings for the Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore." }, "optimized": { "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized", "description": "Contains settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. When choose Optimized storage type, need to set PrivateServiceConnectConfig.enable_private_service_connect to use private endpoint. Otherwise will use public endpoint by default." }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "embeddingManagement": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreEmbeddingManagement", "description": "Optional. Deprecated: This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type." }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "name": { "description": "Identifier. Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`", "type": "string" }, "state": { "description": "Output only. State of the featureOnlineStore.", "enum": [ "STATE_UNSPECIFIED", "STABLE", "UPDATING" ], "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "State when the featureOnlineStore configuration is not being updated and the fields reflect the current configuration of the featureOnlineStore. The featureOnlineStore is usable in this state.", "The state of the featureOnlineStore configuration when it is being updated. During an update, the fields reflect either the original configuration or the updated configuration of the featureOnlineStore. The featureOnlineStore is still usable in this state." ], "readOnly": true }, "dedicatedServingEndpoint": { "description": "Optional. The dedicated serving endpoint for this FeatureOnlineStore, which is different from common Vertex service endpoint.", "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreDedicatedServingEndpoint" } }, "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStore", "type": "object" }, "GoogleCloudAiplatformV1beta1ListModelMonitorsResponse": { "description": "Response message for ModelMonitoringService.ListModelMonitors", "properties": { "modelMonitors": { "description": "List of ModelMonitor in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitor" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListModelMonitorsRequest.page_token to obtain that page.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListModelMonitorsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1UploadRagFileResponse": { "id": "GoogleCloudAiplatformV1beta1UploadRagFileResponse", "type": "object", "description": "Response message for VertexRagDataService.UploadRagFile.", "properties": { "ragFile": { "$ref": "GoogleCloudAiplatformV1beta1RagFile", "description": "The RagFile that had been uploaded into the RagCorpus." }, "error": { "description": "The error that occurred while processing the RagFile.", "$ref": "GoogleRpcStatus" } } }, "GoogleCloudAiplatformV1beta1RagFileChunkingConfig": { "id": "GoogleCloudAiplatformV1beta1RagFileChunkingConfig", "type": "object", "properties": { "chunkSize": { "type": "integer", "deprecated": true, "description": "The size of the chunks.", "format": "int32" }, "chunkOverlap": { "type": "integer", "deprecated": true, "description": "The overlap between chunks.", "format": "int32" }, "fixedLengthChunking": { "$ref": "GoogleCloudAiplatformV1beta1RagFileChunkingConfigFixedLengthChunking", "description": "Specifies the fixed length chunking config." } }, "description": "Specifies the size and overlap of chunks for RagFiles." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecasting": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecasting", "type": "object", "properties": { "inputs": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs", "description": "The input parameters of this TrainingJob." }, "metadata": { "description": "The metadata information.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata" } }, "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model." }, "GoogleCloudAiplatformV1beta1StudySpecParameterSpecCategoricalValueSpec": { "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecCategoricalValueSpec", "type": "object", "description": "Value specification for a parameter in `CATEGORICAL` type.", "properties": { "values": { "description": "Required. The list of possible categories.", "type": "array", "items": { "type": "string" } }, "defaultValue": { "description": "A default value for a `CATEGORICAL` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1AugmentPromptResponse": { "id": "GoogleCloudAiplatformV1beta1AugmentPromptResponse", "type": "object", "properties": { "facts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Fact" }, "description": "Retrieved facts from RAG data sources." }, "augmentedPrompt": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "description": "Augmented prompt, only text format is supported for now." } }, "description": "Response message for AugmentPrompt." }, "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsResponse": { "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsResponse", "type": "object", "properties": { "totalNumberAlerts": { "type": "string", "description": "The total number of alerts retrieved by the requested objectives.", "format": "int64" }, "modelMonitoringAlerts": { "description": "Alerts retrieved for the requested objectives. Sorted by alert time descendingly.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlert" } }, "nextPageToken": { "description": "The page token that can be used by the next ModelMonitoringService.SearchModelMonitoringAlerts call.", "type": "string" } }, "description": "Response message for ModelMonitoringService.SearchModelMonitoringAlerts." }, "GoogleCloudAiplatformV1beta1GenerateSyntheticDataRequest": { "id": "GoogleCloudAiplatformV1beta1GenerateSyntheticDataRequest", "type": "object", "description": "Request message for DataFoundryService.GenerateSyntheticData. It contains the settings and information needed to generate synthetic data.", "properties": { "taskDescription": { "description": "Generates synthetic data based on a high-level description of the task or data you want.", "$ref": "GoogleCloudAiplatformV1beta1TaskDescriptionStrategy" }, "outputFieldSpecs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1OutputFieldSpec" }, "description": "Required. Defines the schema of each synthetic example to be generated, defined by a list of fields." }, "count": { "type": "integer", "format": "int32", "description": "Required. The number of synthetic examples to generate. For this stateless API, you can generate up to 50 examples in a single request." }, "examples": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SyntheticExample" }, "description": "Optional. A list of few-shot examples that help the model understand the desired style, tone, and format of the generated synthetic data. Providing these few-shot examples can significantly improve the quality and relevance of the output." } } }, "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigTtlConfigGranularTtlConfig": { "properties": { "generateUpdatedTtl": { "format": "google-duration", "description": "Optional. The TTL duration for memories updated via GenerateMemories (GenerateMemoriesResponse.GeneratedMemory.Action.UPDATED). In the case of an UPDATE action, the `expire_time` of the existing memory will be updated to the new value (now + TTL).", "type": "string" }, "createTtl": { "description": "Optional. The TTL duration for memories uploaded via CreateMemory.", "format": "google-duration", "type": "string" }, "generateCreatedTtl": { "type": "string", "description": "Optional. The TTL duration for memories newly generated via GenerateMemories (GenerateMemoriesResponse.GeneratedMemory.Action.CREATED).", "format": "google-duration" } }, "description": "Configuration for TTL of the memories in the Memory Bank based on the action that created or updated the memory.", "id": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigTtlConfigGranularTtlConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1RetrieveMemoriesResponseRetrievedMemory": { "description": "A retrieved memory.", "properties": { "memory": { "description": "The retrieved Memory.", "$ref": "GoogleCloudAiplatformV1beta1Memory" }, "distance": { "format": "double", "description": "The distance between the query and the retrieved Memory. Smaller values indicate more similar memories. This is only set if similarity search was used for retrieval.", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1RetrieveMemoriesResponseRetrievedMemory", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataBigQuerySource": { "id": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataBigQuerySource", "type": "object", "properties": { "uri": { "description": "The URI of a BigQuery table.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata": { "properties": { "backingHyperparameterTuningJob": { "description": "The resource name of the HyperparameterTuningJob that has been created to carry out this HyperparameterTuning task.", "type": "string" }, "bestTrialBackingCustomJob": { "description": "The resource name of the CustomJob that has been created to run the best Trial of this HyperparameterTuning task.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1CreatePipelineJobRequest": { "properties": { "pipelineJob": { "$ref": "GoogleCloudAiplatformV1beta1PipelineJob", "description": "Required. The PipelineJob to create." }, "pipelineJobId": { "description": "The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.", "type": "string" }, "parent": { "description": "Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`", "type": "string" } }, "description": "Request message for PipelineService.CreatePipelineJob.", "id": "GoogleCloudAiplatformV1beta1CreatePipelineJobRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1GeminiTemplateConfig": { "id": "GoogleCloudAiplatformV1beta1GeminiTemplateConfig", "type": "object", "description": "Template configuration to create Gemini examples from a multimodal dataset.", "properties": { "geminiExample": { "$ref": "GoogleCloudAiplatformV1beta1GeminiExample", "description": "Required. The template that will be used for assembling the request to use for downstream applications." }, "fieldMapping": { "description": "Required. Map of template parameters to the columns in the dataset table.", "type": "object", "additionalProperties": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1MetricxInstance": { "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" }, "source": { "description": "Optional. Source text in original language.", "type": "string" } }, "description": "Spec for MetricX instance - The fields used for evaluation are dependent on the MetricX version.", "id": "GoogleCloudAiplatformV1beta1MetricxInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1RagFileParsingConfigLlmParser": { "id": "GoogleCloudAiplatformV1beta1RagFileParsingConfigLlmParser", "type": "object", "properties": { "modelName": { "description": "The name of a LLM model used for parsing. Format: * `projects/{project_id}/locations/{location}/publishers/{publisher}/models/{model}`", "type": "string" }, "maxParsingRequestsPerMin": { "description": "The maximum number of requests the job is allowed to make to the LLM model per minute. Consult https://cloud.google.com/vertex-ai/generative-ai/docs/quotas and your document size to set an appropriate value here. If unspecified, a default value of 5000 QPM would be used.", "format": "int32", "type": "integer" }, "globalMaxParsingRequestsPerMin": { "type": "integer", "format": "int32", "description": "The maximum number of requests the job is allowed to make to the LLM model per minute in this project. Consult https://cloud.google.com/vertex-ai/generative-ai/docs/quotas and your document size to set an appropriate value here. If this value is not specified, max_parsing_requests_per_min will be used by indexing pipeline job as the global limit." }, "customParsingPrompt": { "description": "The prompt to use for parsing. If not specified, a default prompt will be used.", "type": "string" } }, "description": "Specifies the LLM parsing for RagFiles." }, "GoogleCloudAiplatformV1beta1CreateIndexEndpointOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateIndexEndpointOperationMetadata", "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The operation generic information." } }, "description": "Runtime operation information for IndexEndpointService.CreateIndexEndpoint." }, "GoogleCloudAiplatformV1beta1GenerateLossClustersResponse": { "id": "GoogleCloudAiplatformV1beta1GenerateLossClustersResponse", "type": "object", "properties": { "analysisTime": { "description": "The timestamp when this analysis was completed.", "format": "google-datetime", "type": "string" }, "results": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LossAnalysisResult" }, "description": "The analysis results, one per config provided in the request." } }, "description": "Response message for EvaluationAnalyticsService.GenerateLossClusters." }, "GoogleCloudAiplatformV1beta1EvaluationSet": { "properties": { "metadata": { "description": "Optional. Metadata for the EvaluationSet.", "type": "any" }, "name": { "description": "Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`", "type": "string" }, "evaluationItems": { "type": "array", "items": { "type": "string" }, "description": "Required. The EvaluationItems that are part of this dataset." }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this item was last updated.", "format": "google-datetime" }, "displayName": { "description": "Required. The display name of the EvaluationSet.", "type": "string" }, "agentConfigs": { "description": "Optional. Static configurations for each agent associated with the items in this set. Key: `agent_id` (matches the `author` field in `events`). Value: The static configuration of the agent.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1AgentConfig" } }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this item was created." } }, "description": "EvaluationSet is a collection of related EvaluationItems that are evaluated together.", "id": "GoogleCloudAiplatformV1beta1EvaluationSet", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationPromptPromptTemplateData": { "properties": { "values": { "description": "The values for fields in the prompt template.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1Content" } } }, "description": "Message to hold a prompt template and the values to populate the template.", "id": "GoogleCloudAiplatformV1beta1EvaluationPromptPromptTemplateData", "type": "object" }, "GoogleCloudAiplatformV1beta1SuspendOnlineEvaluatorOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1SuspendOnlineEvaluatorOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "Common part of operation metadata.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Metadata for the SuspendOnlineEvaluator operation." }, "GoogleCloudAiplatformV1beta1ProbeGrpcAction": { "id": "GoogleCloudAiplatformV1beta1ProbeGrpcAction", "type": "object", "properties": { "port": { "description": "Port number of the gRPC service. Number must be in the range 1 to 65535.", "format": "int32", "type": "integer" }, "service": { "description": "Service is the name of the service to place in the gRPC HealthCheckRequest. See https://github.com/grpc/grpc/blob/master/doc/health-checking.md. If this is not specified, the default behavior is defined by gRPC.", "type": "string" } }, "description": "GrpcAction checks the health of a container using a gRPC service." }, "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInstance": { "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "reference": { "description": "Required. Ground truth used to compare against the prediction.", "type": "string" } }, "description": "Spec for tool parameter key match instance.", "id": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1StudySpecTransferLearningConfig": { "id": "GoogleCloudAiplatformV1beta1StudySpecTransferLearningConfig", "type": "object", "properties": { "disableTransferLearning": { "description": "Flag to to manually prevent vizier from using transfer learning on a new study. Otherwise, vizier will automatically determine whether or not to use transfer learning.", "type": "boolean" }, "priorStudyNames": { "description": "Output only. Names of previously completed studies", "readOnly": true, "type": "array", "items": { "type": "string" } } }, "description": "This contains flag for manually disabling transfer learning for a study. The names of prior studies being used for transfer learning (if any) are also listed here." }, "GoogleCloudAiplatformV1beta1ListFeaturesResponse": { "id": "GoogleCloudAiplatformV1beta1ListFeaturesResponse", "type": "object", "properties": { "features": { "description": "The Features matching the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Feature" } }, "nextPageToken": { "description": "A token, which can be sent as ListFeaturesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "description": "Response message for FeaturestoreService.ListFeatures. Response message for FeatureRegistryService.ListFeatures." }, "GoogleCloudAiplatformV1beta1RagFileParsingConfigLayoutParser": { "id": "GoogleCloudAiplatformV1beta1RagFileParsingConfigLayoutParser", "type": "object", "properties": { "globalMaxParsingRequestsPerMin": { "type": "integer", "description": "The maximum number of requests the job is allowed to make to the Document AI processor per minute in this project. Consult https://cloud.google.com/document-ai/quotas and the Quota page for your project to set an appropriate value here. If this value is not specified, max_parsing_requests_per_min will be used by indexing pipeline as the global limit.", "format": "int32" }, "processorName": { "description": "The full resource name of a Document AI processor or processor version. The processor must have type `LAYOUT_PARSER_PROCESSOR`. If specified, the `additional_config.parse_as_scanned_pdf` field must be false. Format: * `projects/{project_id}/locations/{location}/processors/{processor_id}` * `projects/{project_id}/locations/{location}/processors/{processor_id}/processorVersions/{processor_version_id}`", "type": "string" }, "maxParsingRequestsPerMin": { "type": "integer", "format": "int32", "description": "The maximum number of requests the job is allowed to make to the Document AI processor per minute. Consult https://cloud.google.com/document-ai/quotas and the Quota page for your project to set an appropriate value here. If unspecified, a default value of 120 QPM would be used." } }, "description": "Document AI Layout Parser config." }, "GoogleCloudAiplatformV1beta1VertexMultimodalDatasetSource": { "id": "GoogleCloudAiplatformV1beta1VertexMultimodalDatasetSource", "type": "object", "description": "The Vertex Multimodal Dataset for the input content.", "properties": { "datasetName": { "description": "Required. The resource name of the Vertex Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionImageObjectDetectionPredictionResult": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionImageObjectDetectionPredictionResult", "type": "object", "description": "Prediction output format for Image Object Detection.", "properties": { "confidences": { "description": "The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids.", "type": "array", "items": { "format": "float", "type": "number" } }, "bboxes": { "description": "Bounding boxes, i.e. the rectangles over the image, that pinpoint the found AnnotationSpecs. Given in order that matches the IDs. Each bounding box is an array of 4 numbers `xMin`, `xMax`, `yMin`, and `yMax`, which represent the extremal coordinates of the box. They are relative to the image size, and the point 0,0 is in the top left of the image.", "type": "array", "items": { "type": "array", "items": { "type": "any" } } }, "displayNames": { "type": "array", "items": { "type": "string" }, "description": "The display names of the AnnotationSpecs that had been identified, order matches the IDs." }, "ids": { "description": "The resource IDs of the AnnotationSpecs that had been identified, ordered by the confidence score descendingly.", "type": "array", "items": { "format": "int64", "type": "string" } } } }, "GoogleCloudAiplatformV1beta1CometInstance": { "properties": { "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" }, "source": { "description": "Optional. Source text in original language.", "type": "string" }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" } }, "description": "Spec for Comet instance - The fields used for evaluation are dependent on the comet version.", "id": "GoogleCloudAiplatformV1beta1CometInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1ContentsExampleExpectedContent": { "id": "GoogleCloudAiplatformV1beta1ContentsExampleExpectedContent", "type": "object", "properties": { "content": { "description": "Required. A single step's content.", "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "description": "A single step of the expected output." }, "CloudAiLargeModelsVisionVideo": { "id": "CloudAiLargeModelsVisionVideo", "type": "object", "description": "Video", "properties": { "uri": { "description": "Path to another storage (typically Google Cloud Storage).", "type": "string" }, "video": { "description": "Raw bytes.", "format": "byte", "type": "string" }, "encoding": { "description": "Video encoding, for example \"video/mp4\".", "type": "string" }, "text": { "description": "Text/Expanded text input for Help Me Write.", "type": "string" }, "encodedVideo": { "description": "Base 64 encoded video bytes.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ToolNameMatchInput": { "id": "GoogleCloudAiplatformV1beta1ToolNameMatchInput", "type": "object", "description": "Input for tool name match metric.", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1ToolNameMatchSpec", "description": "Required. Spec for tool name match metric." }, "instances": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ToolNameMatchInstance" }, "description": "Required. Repeated tool name match instances." } } }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics", "type": "object", "description": "Metrics for a single confidence threshold.", "properties": { "precision": { "type": "number", "format": "float", "description": "Output only. Precision for the given confidence threshold." }, "f1Score": { "format": "float", "description": "Output only. The harmonic mean of recall and precision.", "type": "number" }, "confidenceThreshold": { "type": "number", "format": "float", "description": "Output only. The confidence threshold value used to compute the metrics." }, "recall": { "description": "Output only. Recall for the given confidence threshold.", "format": "float", "type": "number" } } }, "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource": { "properties": { "ragCorpus": { "description": "Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "type": "string" }, "ragFileIds": { "description": "Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.", "type": "array", "items": { "type": "string" } } }, "description": "The definition of the Rag resource.", "id": "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureValueList": { "id": "GoogleCloudAiplatformV1beta1FeatureValueList", "type": "object", "properties": { "values": { "description": "A list of feature values. All of them should be the same data type.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureValue" } } }, "description": "Container for list of values." }, "GoogleCloudAiplatformV1beta1DatasetCustomMetric": { "id": "GoogleCloudAiplatformV1beta1DatasetCustomMetric", "type": "object", "properties": { "displayName": { "description": "Optional. A display name for this custom summary metric. Used to prefix keys in the output summaryMetrics map. If not provided, a default name like \"dataset_custom_metric_1\", \"dataset_custom_metric_2\", etc., will be generated based on the order in the repeated field.", "type": "string" }, "aggregationFunction": { "description": "Required. The Python code string containing the aggregation function. Expected function signature: `def aggregate(instances: list[dict[str, Any]]) -\u003e dict[str, float]:` The `instances` argument is a list of dictionaries, where each dictionary represents a single evaluation result item. The structure of each dictionary corresponds to the fields in the `EvaluationResult` message. This includes: - `\"request\"`: Contains the original input data and model inputs (from `EvaluationResult.EvaluationRequest`). - `\"candidate_results\"`: Contains the results of any instance-level metrics (from `EvaluationResult.CandidateResults`). Example of a single item in the `instances` list: { \"request\": { \"prompt\": {\"text\": \"What is the capital of France?\"}, \"golden_response\": {\"text\": \"Paris\"}, \"candidate_responses\": [{\"candidate\": \"model-v1\", \"text\": \"Paris\"}] }, \"candidate_results\": [ {\"metric\": \"exact_match\", \"score\": 1.0}, {\"metric\": \"bleu\", \"score\": 0.9} ] }", "type": "string" } }, "description": "Defines a custom dataset-level aggregation." }, "GoogleCloudAiplatformV1beta1FeatureGroupBigQueryTimeSeries": { "properties": { "timestampColumn": { "description": "Optional. Column hosting timestamp values for a time-series source. Will be used to determine the latest `feature_values` for each entity. Optional. If not provided, column named `feature_timestamp` of type `TIMESTAMP` will be used.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1FeatureGroupBigQueryTimeSeries", "type": "object" }, "GoogleCloudAiplatformV1beta1LogprobsResult": { "description": "The log probabilities of the tokens generated by the model. This is useful for understanding the model's confidence in its predictions and for debugging. For example, you can use log probabilities to identify when the model is making a less confident prediction or to explore alternative responses that the model considered. A low log probability can also indicate that the model is \"hallucinating\" or generating factually incorrect information.", "properties": { "topCandidates": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LogprobsResultTopCandidates" }, "description": "A list of the top candidate tokens at each decoding step. The length of this list is equal to the total number of decoding steps." }, "chosenCandidates": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LogprobsResultCandidate" }, "description": "A list of the chosen candidate tokens at each decoding step. The length of this list is equal to the total number of decoding steps. Note that the chosen candidate might not be in `top_candidates`." } }, "id": "GoogleCloudAiplatformV1beta1LogprobsResult", "type": "object" }, "GoogleCloudAiplatformV1beta1OnlineEvaluatorStateDetails": { "id": "GoogleCloudAiplatformV1beta1OnlineEvaluatorStateDetails", "type": "object", "properties": { "message": { "readOnly": true, "type": "string", "description": "Output only. Human-readable message describing the state of the OnlineEvaluator." } }, "description": "Contains additional information about the state of the OnlineEvaluator." }, "GoogleCloudAiplatformV1beta1RagFile": { "id": "GoogleCloudAiplatformV1beta1RagFile", "type": "object", "properties": { "userMetadata": { "type": "string", "readOnly": true, "description": "Output only. The metadata for metadata search. The user_metadata Needs to be in JSON format." }, "directUploadSource": { "description": "Output only. The RagFile is encapsulated and uploaded in the UploadRagFile request.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1DirectUploadSource" }, "displayName": { "description": "Required. The display name of the RagFile. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "jiraSource": { "description": "The RagFile is imported from a Jira query.", "$ref": "GoogleCloudAiplatformV1beta1JiraSource" }, "googleDriveSource": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1GoogleDriveSource", "description": "Output only. Google Drive location. Supports importing individual files as well as Google Drive folders." }, "name": { "description": "Output only. The resource name of the RagFile.", "readOnly": true, "type": "string" }, "fileStatus": { "description": "Output only. State of the RagFile.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1FileStatus" }, "slackSource": { "$ref": "GoogleCloudAiplatformV1beta1SlackSource", "description": "The RagFile is imported from a Slack channel." }, "sharePointSources": { "description": "The RagFile is imported from a SharePoint source.", "$ref": "GoogleCloudAiplatformV1beta1SharePointSources" }, "sizeBytes": { "description": "Output only. The size of the RagFile in bytes.", "format": "int64", "type": "string", "readOnly": true }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this RagFile was last updated.", "readOnly": true, "type": "string" }, "ragFileType": { "readOnly": true, "type": "string", "enumDescriptions": [ "RagFile type is unspecified.", "RagFile type is TXT.", "RagFile type is PDF." ], "enum": [ "RAG_FILE_TYPE_UNSPECIFIED", "RAG_FILE_TYPE_TXT", "RAG_FILE_TYPE_PDF" ], "description": "Output only. The type of the RagFile." }, "gcsSource": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1GcsSource", "description": "Output only. Google Cloud Storage location of the RagFile. It does not support wildcards in the Cloud Storage uri for now." }, "description": { "description": "Optional. The description of the RagFile.", "type": "string" }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when this RagFile was created.", "readOnly": true, "type": "string" } }, "description": "A RagFile contains user data for chunking, embedding and indexing." }, "GoogleCloudAiplatformV1beta1RagVectorDbConfigVertexVectorSearch": { "id": "GoogleCloudAiplatformV1beta1RagVectorDbConfigVertexVectorSearch", "type": "object", "properties": { "indexEndpoint": { "description": "The resource name of the Index Endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "type": "string" }, "index": { "description": "The resource name of the Index. Format: `projects/{project}/locations/{location}/indexes/{index}`", "type": "string" } }, "description": "The config for the Vertex Vector Search." }, "GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" }, "progressMessage": { "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime.", "type": "string" } }, "description": "Metadata information for NotebookService.CreateNotebookExecutionJob." }, "GoogleCloudAiplatformV1beta1SpeakerVoiceConfig": { "description": "Configuration for a single speaker in a multi-speaker setup.", "properties": { "speaker": { "description": "Required. The name of the speaker. This should be the same as the speaker name used in the prompt.", "type": "string" }, "voiceConfig": { "$ref": "GoogleCloudAiplatformV1beta1VoiceConfig", "description": "Required. The configuration for the voice of this speaker." } }, "id": "GoogleCloudAiplatformV1beta1SpeakerVoiceConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1FailedRubric": { "id": "GoogleCloudAiplatformV1beta1FailedRubric", "type": "object", "properties": { "rubricId": { "description": "The unique ID of the rubric (if available from the metric source). Clients use this ID to query the corresponding rubric verdict.", "type": "string" }, "classificationRationale": { "description": "The rationale provided by the Loss Analysis Classifier for why this failure maps to this specific Loss Cluster. e.g., \"The agent claimed an action without a tool call, matching 'Hallucination of Action'.\"", "type": "string" } }, "description": "Represents a specific failed rubric and the associated analysis." }, "GoogleCloudAiplatformV1beta1ModelMonitoringStats": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStats", "type": "object", "description": "Represents the collection of statistics for a metric.", "properties": { "tabularStats": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringTabularStats", "description": "Generated tabular statistics." } } }, "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsResponse": { "properties": { "importedEvaluatedAnnotationsCount": { "format": "int32", "description": "Output only. Number of EvaluatedAnnotations imported.", "readOnly": true, "type": "integer" } }, "description": "Response message for ModelService.BatchImportEvaluatedAnnotations", "id": "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1UpsertExamplesResponse": { "description": "Response message for ExampleStoreService.UpsertExamples.", "properties": { "results": { "description": "A list of results for creating/updating. It's either a successfully created/updated example or a status with an error message.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1UpsertExamplesResponseUpsertResult" } } }, "id": "GoogleCloudAiplatformV1beta1UpsertExamplesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ListCustomJobsResponse": { "id": "GoogleCloudAiplatformV1beta1ListCustomJobsResponse", "type": "object", "description": "Response message for JobService.ListCustomJobs", "properties": { "customJobs": { "description": "List of CustomJobs in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1CustomJob" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListCustomJobsRequest.page_token to obtain that page.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1CreateFeatureOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateFeatureOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "Operation metadata for Feature.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Details of operations that perform create Feature." }, "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponse": { "properties": { "selectTimeRangeAndFeature": { "description": "Response for request specifying time range and feature", "$ref": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectTimeRangeAndFeature" }, "selectEntity": { "$ref": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectEntity", "description": "Response for request specifying the entities to delete" } }, "description": "Response message for FeaturestoreService.DeleteFeatureValues.", "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponse", "type": "object" }, "CloudAiLargeModelsVisionImageRAIScores": { "id": "CloudAiLargeModelsVisionImageRAIScores", "type": "object", "description": "RAI scores for generated image returned.", "properties": { "agileWatermarkDetectionScore": { "format": "double", "description": "Agile watermark score for image.", "type": "number" } } }, "GoogleCloudAiplatformV1beta1NearestNeighborsNeighbor": { "id": "GoogleCloudAiplatformV1beta1NearestNeighborsNeighbor", "type": "object", "description": "A neighbor of the query vector.", "properties": { "entityId": { "description": "The id of the similar entity.", "type": "string" }, "entityKeyValues": { "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse", "description": "The attributes of the neighbor, e.g. filters, crowding and metadata Note that full entities are returned only when \"return_full_entity\" is set to true. Otherwise, only the \"entity_id\" and \"distance\" fields are populated." }, "distance": { "format": "double", "description": "The distance between the neighbor and the query vector.", "type": "number" } } }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationExample": { "properties": { "referenceSentencePairLists": { "description": "The reference sentences from inline text.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecReferenceSentencePairList" } }, "referenceSentencesFileInputs": { "description": "The reference sentences from file.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationSentenceFileInput" } } }, "description": "The translation example that contains reference sentences from various sources.", "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationExample", "type": "object" }, "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigSnapshotAnalysis": { "description": "Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.", "properties": { "monitoringInterval": { "type": "string", "deprecated": true, "description": "Configuration of the snapshot analysis based monitoring pipeline running interval. The value is rolled up to full day. If both monitoring_interval_days and the deprecated `monitoring_interval` field are set when creating/updating EntityTypes/Features, monitoring_interval_days will be used.", "format": "google-duration" }, "disabled": { "description": "The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.", "type": "boolean" }, "monitoringIntervalDays": { "type": "integer", "description": "Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.", "format": "int32" }, "stalenessDays": { "format": "int32", "description": "Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigSnapshotAnalysis", "type": "object" }, "GoogleCloudAiplatformV1beta1CsvSource": { "id": "GoogleCloudAiplatformV1beta1CsvSource", "type": "object", "properties": { "gcsSource": { "$ref": "GoogleCloudAiplatformV1beta1GcsSource", "description": "Required. Google Cloud Storage location." } }, "description": "The storage details for CSV input content." }, "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringGcsSource": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringGcsSource", "type": "object", "description": "Dataset spec for data stored in Google Cloud Storage.", "properties": { "format": { "type": "string", "enumDescriptions": [ "Data format unspecified, used when this field is unset.", "CSV files.", "TfRecord files", "JsonL files." ], "description": "Data format of the dataset.", "enum": [ "DATA_FORMAT_UNSPECIFIED", "CSV", "TF_RECORD", "JSONL" ] }, "gcsUri": { "description": "Google Cloud Storage URI to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/wildcards.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTimeSeriesForecastingPredictionResult": { "description": "Prediction output format for Time Series Forecasting.", "properties": { "quantilePredictions": { "type": "array", "items": { "format": "float", "type": "number" }, "description": "Quantile predictions, in 1-1 correspondence with quantile_values." }, "tftFeatureImportance": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTftFeatureImportance", "description": "Only use these if TFt is enabled." }, "value": { "format": "float", "description": "The regression value.", "type": "number" }, "quantileValues": { "description": "Quantile values.", "type": "array", "items": { "format": "float", "type": "number" } } }, "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTimeSeriesForecastingPredictionResult", "type": "object" }, "GoogleCloudAiplatformV1beta1PipelineTaskRerunConfigInputs": { "id": "GoogleCloudAiplatformV1beta1PipelineTaskRerunConfigInputs", "type": "object", "description": "Runtime inputs data of the task.", "properties": { "artifacts": { "description": "Optional. Input artifacts.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskRerunConfigArtifactList" } }, "parameterValues": { "type": "object", "additionalProperties": { "type": "any" }, "description": "Optional. Input parameters." } } }, "GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest": { "id": "GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest", "type": "object", "description": "Request message for SandboxEnvironmentExecutionService.Execute.", "properties": { "inputs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Chunk" }, "description": "Required. The inputs to the sandbox environment." } } }, "GoogleCloudAiplatformV1beta1EntityType": { "properties": { "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." }, "updateTime": { "description": "Output only. Timestamp when this EntityType was most recently updated.", "format": "google-datetime", "type": "string", "readOnly": true }, "name": { "description": "Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.", "type": "string" }, "offlineStorageTtlDays": { "type": "integer", "format": "int32", "description": "Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than `offline_storage_ttl_days` since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL." }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "etag": { "description": "Optional. Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "description": { "description": "Optional. Description of the EntityType.", "type": "string" }, "satisfiesPzi": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "createTime": { "description": "Output only. Timestamp when this EntityType was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "monitoringConfig": { "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfig", "description": "Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled." } }, "description": "An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver.", "id": "GoogleCloudAiplatformV1beta1EntityType", "type": "object" }, "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadata": { "properties": { "contentValidationStats": { "description": "The validation stats of the content (per file) to be inserted or updated on the Matching Engine Index resource. Populated if contentsDeltaUri is provided as part of Index.metadata. Please note that, currently for those files that are broken or has unsupported file format, we will not have the stats for those files.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataContentValidationStats" } }, "dataBytesCount": { "format": "int64", "description": "The ingested data size in bytes.", "type": "string" } }, "description": "Runtime operation metadata with regard to Matching Engine Index.", "id": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationRunMetricLLMBasedMetricSpec": { "id": "GoogleCloudAiplatformV1beta1EvaluationRunMetricLLMBasedMetricSpec", "type": "object", "properties": { "systemInstruction": { "description": "Optional. System instructions for the judge model.", "type": "string" }, "metricPromptTemplate": { "description": "Required. Template for the prompt sent to the judge model.", "type": "string" }, "judgeAutoraterConfig": { "description": "Optional. Optional configuration for the judge LLM (Autorater).", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigAutoraterConfig" }, "predefinedRubricGenerationSpec": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunMetricPredefinedMetricSpec", "description": "Dynamically generate rubrics using a predefined spec." }, "rubricGroupKey": { "description": "Use a pre-defined group of rubrics associated with the input. Refers to a key in the rubric_groups map of EvaluationInstance.", "type": "string" }, "additionalConfig": { "description": "Optional. Optional additional configuration for the metric.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "rubricGenerationSpec": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricGenerationSpec", "description": "Dynamically generate rubrics using this specification." } }, "description": "Specification for an LLM based metric." }, "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectTimeRangeAndFeature": { "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectTimeRangeAndFeature", "type": "object", "description": "Message to select time range and feature. Values of the selected feature generated within an inclusive time range will be deleted. Using this option permanently deletes the feature values from the specified feature IDs within the specified time range. This might include data from the online storage. If you want to retain any deleted historical data in the online storage, you must re-ingest it.", "properties": { "timeRange": { "$ref": "GoogleTypeInterval", "description": "Required. Select feature generated within a half-inclusive time range. The time range is lower inclusive and upper exclusive." }, "featureSelector": { "$ref": "GoogleCloudAiplatformV1beta1FeatureSelector", "description": "Required. Selectors choosing which feature values to be deleted from the EntityType." }, "skipOnlineStorageDelete": { "description": "If set, data will not be deleted from online storage. When time range is older than the data in online storage, setting this to be true will make the deletion have no impact on online serving.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1GenerateFetchAccessTokenResponse": { "id": "GoogleCloudAiplatformV1beta1GenerateFetchAccessTokenResponse", "type": "object", "description": "Response message for FeatureOnlineStoreService.GenerateFetchAccessToken.", "properties": { "accessToken": { "description": "The OAuth 2.0 access token.", "type": "string" }, "expireTime": { "type": "string", "format": "google-datetime", "description": "Token expiration time. This is always set" } } }, "GoogleCloudAiplatformV1beta1SpeechConfig": { "properties": { "multiSpeakerVoiceConfig": { "$ref": "GoogleCloudAiplatformV1beta1MultiSpeakerVoiceConfig", "description": "The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`." }, "languageCode": { "description": "Optional. The language code (ISO 639-1) for the speech synthesis.", "type": "string" }, "voiceConfig": { "description": "The configuration for the voice to use.", "$ref": "GoogleCloudAiplatformV1beta1VoiceConfig" } }, "description": "Configuration for speech generation.", "id": "GoogleCloudAiplatformV1beta1SpeechConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateFeatureOnlineStoreOperationMetadata": { "description": "Details of operations that perform create FeatureOnlineStore.", "properties": { "genericMetadata": { "description": "Operation metadata for FeatureOnlineStore.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1beta1CreateFeatureOnlineStoreOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1UploadModelResponse": { "id": "GoogleCloudAiplatformV1beta1UploadModelResponse", "type": "object", "properties": { "model": { "description": "The name of the uploaded Model resource. Format: `projects/{project}/locations/{location}/models/{model}`", "type": "string" }, "modelVersionId": { "readOnly": true, "type": "string", "description": "Output only. The version ID of the model that is uploaded." } }, "description": "Response message of ModelService.UploadModel operation." }, "GoogleCloudAiplatformV1beta1EvaluationRunMetricPredefinedMetricSpec": { "description": "Specification for a pre-defined metric.", "properties": { "metricSpecName": { "description": "Required. The name of a pre-defined metric, such as \"instruction_following_v1\" or \"text_quality_v1\".", "type": "string" }, "parameters": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. The parameters needed to run the pre-defined metric." } }, "id": "GoogleCloudAiplatformV1beta1EvaluationRunMetricPredefinedMetricSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1Dataset": { "description": "A collection of DataItems and Annotations on them.", "properties": { "dataItemCount": { "readOnly": true, "type": "string", "format": "int64", "description": "Output only. The number of DataItems in this Dataset. Only apply for non-structured Dataset." }, "displayName": { "description": "Required. The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "name": { "description": "Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "readOnly": true, "type": "string" }, "savedQueries": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SavedQuery" }, "description": "All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec." }, "encryptionSpec": { "description": "Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key.", "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" }, "metadataArtifact": { "type": "string", "readOnly": true, "description": "Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`." }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this Dataset was created." }, "description": { "description": "The description of the Dataset.", "type": "string" }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "modelReference": { "description": "Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.", "type": "string" }, "metadataSchemaUri": { "description": "Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.", "type": "string" }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this Dataset was last updated.", "readOnly": true, "type": "string" }, "metadata": { "description": "Required. Additional information about the Dataset.", "type": "any" }, "labels": { "description": "The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for each Dataset: * \"aiplatform.googleapis.com/dataset_metadata_schema\": output only, its value is the metadata_schema's title.", "type": "object", "additionalProperties": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1beta1Dataset", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataGcsSource": { "properties": { "uri": { "type": "array", "items": { "type": "string" }, "description": "Cloud Storage URI of one or more files. Only CSV files are supported. The first line of the CSV file is used as the header. If there are multiple files, the header is the first line of the lexicographically first file, the other files must either contain the exact same header or omit the header." } }, "id": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataGcsSource", "type": "object" }, "GoogleCloudAiplatformV1beta1ActivateOnlineEvaluatorOperationMetadata": { "properties": { "genericMetadata": { "description": "Common part of operation metadata.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Metadata for the ActivateOnlineEvaluator operation.", "id": "GoogleCloudAiplatformV1beta1ActivateOnlineEvaluatorOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix", "type": "object", "properties": { "annotationSpecs": { "description": "AnnotationSpecs used in the confusion matrix. For AutoML Text Extraction, a special negative AnnotationSpec with empty `id` and `displayName` of \"NULL\" will be added as the last element.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef" } }, "rows": { "type": "array", "items": { "type": "array", "items": { "type": "any" } }, "description": "Rows in the confusion matrix. The number of rows is equal to the size of `annotationSpecs`. `rowsi` is the number of DataItems that have ground truth of the `annotationSpecs[i]` and are predicted as `annotationSpecs[j]` by the Model being evaluated. For Text Extraction, when `annotationSpecs[i]` is the last element in `annotationSpecs`, i.e. the special negative AnnotationSpec, `rowsi` is the number of predicted entities of `annoatationSpec[j]` that are not labeled as any of the ground truth AnnotationSpec. When annotationSpecs[j] is the special negative AnnotationSpec, `rowsi` is the number of entities have ground truth of `annotationSpec[i]` that are not predicted as an entity by the Model. The value of the last cell, i.e. `rowi` where i == j and `annotationSpec[i]` is the special negative AnnotationSpec, is always 0." } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata", "type": "object", "properties": { "costMilliNodeHours": { "format": "int64", "description": "The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours.", "type": "string" }, "successfulStopReason": { "type": "string", "enumDescriptions": [ "Should not be set.", "The inputs.budgetMilliNodeHours had been reached.", "Further training of the Model ceased to increase its quality, since it already has converged." ], "description": "For successful job completions, this is the reason why the job has finished.", "enum": [ "SUCCESSFUL_STOP_REASON_UNSPECIFIED", "BUDGET_REACHED", "MODEL_CONVERGED" ] } } }, "GoogleCloudAiplatformV1beta1CancelEvaluationRunRequest": { "description": "Request message for EvaluationManagementService.CancelEvaluationRun.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1CancelEvaluationRunRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation", "type": "object", "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.", "properties": { "columnName": { "type": "string" } } }, "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDb": { "id": "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDb", "type": "object", "description": "The config for the default RAG-managed Vector DB.", "properties": { "knn": { "$ref": "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDbKNN", "description": "Performs a KNN search on RagCorpus. Default choice if not specified." }, "ann": { "description": "Performs an ANN search on RagCorpus. Use this if you have a lot of files (\u003e 10K) in your RagCorpus and want to reduce the search latency.", "$ref": "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDbANN" } } }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking": { "properties": { "rankService": { "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService", "description": "Optional. Config for Rank Service." }, "llmRanker": { "description": "Optional. Config for LlmRanker.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker" } }, "description": "Config for ranking and reranking.", "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluateDatasetResponse": { "id": "GoogleCloudAiplatformV1beta1EvaluateDatasetResponse", "type": "object", "properties": { "aggregationOutput": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1AggregationOutput", "description": "Output only. Aggregation statistics derived from results of EvaluationService." }, "outputInfo": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1OutputInfo", "description": "Output only. Output info for EvaluationService." } }, "description": "The results from an evaluation run performed by the EvaluationService." }, "GoogleCloudAiplatformV1beta1NotebookExecutionJobGcsNotebookSource": { "properties": { "uri": { "description": "The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`", "type": "string" }, "generation": { "description": "The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number.", "type": "string" } }, "description": "The Cloud Storage uri for the input notebook.", "id": "GoogleCloudAiplatformV1beta1NotebookExecutionJobGcsNotebookSource", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetrics": { "properties": { "confidenceMetricsEntries": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry" }, "description": "Metrics for each confidenceThreshold in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 Precision-recall curve can be derived from it." } }, "description": "Metrics for image segmentation evaluation results.", "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetrics", "type": "object" }, "GoogleCloudAiplatformV1beta1ExampleStore": { "properties": { "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this ExampleStore was created.", "format": "google-datetime" }, "description": { "description": "Optional. Description of the ExampleStore.", "type": "string" }, "exampleStoreConfig": { "$ref": "GoogleCloudAiplatformV1beta1ExampleStoreConfig", "description": "Required. Example Store config." }, "displayName": { "description": "Required. Display name of the ExampleStore.", "type": "string" }, "name": { "description": "Identifier. The resource name of the ExampleStore. This is a unique identifier. Format: projects/{project}/locations/{location}/exampleStores/{example_store}", "type": "string" }, "updateTime": { "description": "Output only. Timestamp when this ExampleStore was most recently updated.", "format": "google-datetime", "type": "string", "readOnly": true } }, "description": "Represents an executable service to manage and retrieve examples.", "id": "GoogleCloudAiplatformV1beta1ExampleStore", "type": "object" }, "GoogleCloudAiplatformV1beta1DeployedModel": { "description": "A deployment of a Model. Endpoints contain one or more DeployedModels.", "properties": { "serviceAccount": { "description": "The service account that the DeployedModel's container runs as. Specify the email address of the service account. If this service account is not specified, the container runs as a service account that doesn't have access to the resource project. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.", "type": "string" }, "disableContainerLogging": { "description": "For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.", "type": "boolean" }, "id": { "description": "Immutable. The ID of the DeployedModel. If not provided upon deployment, Vertex AI will generate a value for this ID. This value should be 1-10 characters, and valid characters are `/[0-9]/`.", "type": "string" }, "displayName": { "description": "The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.", "type": "string" }, "enableAccessLogging": { "description": "If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each prediction request. Note that logs may incur a cost, especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option.", "type": "boolean" }, "speculativeDecodingSpec": { "description": "Optional. Spec for configuring speculative decoding.", "$ref": "GoogleCloudAiplatformV1beta1SpeculativeDecodingSpec" }, "gdcConnectedModel": { "description": "GDC pretrained / Gemini model name. The model name is a plain model name, e.g. gemini-1.5-flash-002.", "type": "string" }, "model": { "description": "The resource name of the Model that this is the deployment of. Note that the Model may be in a different location than the DeployedModel's Endpoint. The resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed.", "type": "string" }, "explanationSpec": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec", "description": "Explanation configuration for this DeployedModel. When deploying a Model using EndpointService.DeployModel, this value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of explanation_spec is not populated, the value of the same field of Model.explanation_spec is inherited. If the corresponding Model.explanation_spec is not populated, all fields of the explanation_spec will be used for the explanation configuration." }, "rolloutOptions": { "$ref": "GoogleCloudAiplatformV1beta1RolloutOptions", "description": "Options for configuring rolling deployments." }, "checkpointId": { "description": "The checkpoint id of the model.", "type": "string" }, "fasterDeploymentConfig": { "description": "Configuration for faster model deployment.", "$ref": "GoogleCloudAiplatformV1beta1FasterDeploymentConfig" }, "modelVersionId": { "type": "string", "readOnly": true, "description": "Output only. The version ID of the model that is deployed." }, "enableContainerLogging": { "description": "If true, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging. Only supported for custom-trained Models and AutoML Tabular Models.", "type": "boolean" }, "disableExplanations": { "description": "If true, deploy the model without explainable feature, regardless the existence of Model.explanation_spec or explanation_spec.", "type": "boolean" }, "systemLabels": { "description": "System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only.", "type": "object", "additionalProperties": { "type": "string" } }, "createTime": { "description": "Output only. Timestamp when the DeployedModel was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "dedicatedResources": { "$ref": "GoogleCloudAiplatformV1beta1DedicatedResources", "description": "A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration." }, "status": { "description": "Output only. Runtime status of the deployed model.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1DeployedModelStatus" }, "fullFineTunedResources": { "description": "Optional. Resources for a full fine tuned model.", "$ref": "GoogleCloudAiplatformV1beta1FullFineTunedResources" }, "automaticResources": { "$ref": "GoogleCloudAiplatformV1beta1AutomaticResources", "description": "A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration." }, "sharedResources": { "description": "The resource name of the shared DeploymentResourcePool to deploy on. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", "type": "string" }, "privateEndpoints": { "description": "Output only. Provide paths for users to send predict/explain/health requests directly to the deployed model services running on Cloud via private services access. This field is populated if network is configured.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1PrivateEndpoints" } }, "id": "GoogleCloudAiplatformV1beta1DeployedModel", "type": "object" }, "GoogleCloudAiplatformV1beta1SavedQuery": { "properties": { "annotationSpecCount": { "description": "Output only. Number of AnnotationSpecs in the context of the SavedQuery.", "format": "int32", "type": "integer", "readOnly": true }, "etag": { "description": "Used to perform a consistent read-modify-write update. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this SavedQuery was created." }, "metadata": { "description": "Some additional information about the SavedQuery.", "type": "any" }, "name": { "readOnly": true, "type": "string", "description": "Output only. Resource name of the SavedQuery." }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when SavedQuery was last updated." }, "displayName": { "description": "Required. The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "annotationFilter": { "type": "string", "readOnly": true, "description": "Output only. Filters on the Annotations in the dataset." }, "problemType": { "description": "Required. Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING", "type": "string" }, "supportAutomlTraining": { "readOnly": true, "type": "boolean", "description": "Output only. If the Annotations belonging to the SavedQuery can be used for AutoML training." } }, "description": "A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.", "id": "GoogleCloudAiplatformV1beta1SavedQuery", "type": "object" }, "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDbKNN": { "properties": {}, "description": "Config for KNN search.", "id": "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDbKNN", "type": "object" }, "CloudAiLargeModelsVisionRaiInfo": { "description": "Next ID: 6", "properties": { "scores": { "description": "List of rai scores mapping to the rai categories. Rounded to 1 decimal place.", "type": "array", "items": { "type": "number", "format": "float" } }, "detectedLabels": { "description": "The list of detected labels for different rai categories.", "type": "array", "items": { "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabels" } }, "blockedEntities": { "type": "array", "items": { "type": "string" }, "description": "List of blocked entities from the blocklist if it is detected." }, "modelName": { "description": "The model name used to indexing into the RaiFilterConfig map. Would either be one of imagegeneration@002-006, imagen-3.0-... api endpoint names, or internal names used for mapping to different filter configs (genselfie, ai_watermark) than its api endpoint.", "type": "string" }, "raiCategories": { "description": "List of rai categories' information to return", "type": "array", "items": { "type": "string" } } }, "id": "CloudAiLargeModelsVisionRaiInfo", "type": "object" }, "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataVisualization": { "properties": { "clipPercentUpperbound": { "type": "number", "format": "float", "description": "Excludes attributions above the specified percentile from the highlighted areas. Using the clip_percent_upperbound and clip_percent_lowerbound together can be useful for filtering out noise and making it easier to see areas of strong attribution. Defaults to 99.9." }, "overlayType": { "type": "string", "enumDescriptions": [ "Default value. This is the same as NONE.", "No overlay.", "The attributions are shown on top of the original image.", "The attributions are shown on top of grayscaled version of the original image.", "The attributions are used as a mask to reveal predictive parts of the image and hide the un-predictive parts." ], "description": "How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.", "enum": [ "OVERLAY_TYPE_UNSPECIFIED", "NONE", "ORIGINAL", "GRAYSCALE", "MASK_BLACK" ] }, "type": { "description": "Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.", "enum": [ "TYPE_UNSPECIFIED", "PIXELS", "OUTLINES" ], "type": "string", "enumDescriptions": [ "Should not be used.", "Shows which pixel contributed to the image prediction.", "Shows which region contributed to the image prediction by outlining the region." ] }, "polarity": { "description": "Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.", "enum": [ "POLARITY_UNSPECIFIED", "POSITIVE", "NEGATIVE", "BOTH" ], "type": "string", "enumDescriptions": [ "Default value. This is the same as POSITIVE.", "Highlights the pixels/outlines that were most influential to the model's prediction.", "Setting polarity to negative highlights areas that does not lead to the models's current prediction.", "Shows both positive and negative attributions." ] }, "colorMap": { "type": "string", "enumDescriptions": [ "Should not be used.", "Positive: green. Negative: pink.", "Viridis color map: A perceptually uniform color mapping which is easier to see by those with colorblindness and progresses from yellow to green to blue. Positive: yellow. Negative: blue.", "Positive: red. Negative: red.", "Positive: green. Negative: green.", "Positive: green. Negative: red.", "PiYG palette." ], "description": "The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.", "enum": [ "COLOR_MAP_UNSPECIFIED", "PINK_GREEN", "VIRIDIS", "RED", "GREEN", "RED_GREEN", "PINK_WHITE_GREEN" ] }, "clipPercentLowerbound": { "format": "float", "description": "Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62.", "type": "number" } }, "description": "Visualization configurations for image explanation.", "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataVisualization", "type": "object" }, "GoogleCloudAiplatformV1beta1StratifiedSplit": { "description": "Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the `key` field) is mirrored within each split. The fraction values determine the relative sizes of the splits. For example, if the specified column has three values, with 50% of the rows having value \"A\", 25% value \"B\", and 25% value \"C\", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value \"A\" for the specified column, about 25% having the value \"B\", and about 25% having the value \"C\". Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned. Supported only for tabular Datasets.", "properties": { "key": { "description": "Required. The key is a name of one of the Dataset's data columns. The key provided must be for a categorical column.", "type": "string" }, "trainingFraction": { "type": "number", "format": "double", "description": "The fraction of the input data that is to be used to train the Model." }, "validationFraction": { "description": "The fraction of the input data that is to be used to validate the Model.", "format": "double", "type": "number" }, "testFraction": { "description": "The fraction of the input data that is to be used to evaluate the Model.", "format": "double", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1StratifiedSplit", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelEvaluationSlice": { "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSlice", "type": "object", "description": "A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations.", "properties": { "metrics": { "description": "Output only. Sliced evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri", "type": "any", "readOnly": true }, "name": { "description": "Output only. The resource name of the ModelEvaluationSlice.", "readOnly": true, "type": "string" }, "slice": { "description": "Output only. The slice of the test data that is used to evaluate the Model.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSlice" }, "modelExplanation": { "description": "Output only. Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for tabular Models.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ModelExplanation" }, "metricsSchemaUri": { "description": "Output only. Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluationSlice. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).", "readOnly": true, "type": "string" }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when this ModelEvaluationSlice was created.", "readOnly": true, "type": "string" } } }, "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInput": { "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInstance", "description": "Required. Pairwise summarization quality instance." }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualitySpec", "description": "Required. Spec for pairwise summarization quality score metric." } }, "description": "Input for pairwise summarization quality metric.", "id": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInput", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureViewVertexRagSource": { "id": "GoogleCloudAiplatformV1beta1FeatureViewVertexRagSource", "type": "object", "properties": { "uri": { "description": "Required. The BigQuery view/table URI that will be materialized on each manual sync trigger. The table/view is expected to have the following columns and types at least: - `corpus_id` (STRING, NULLABLE/REQUIRED) - `file_id` (STRING, NULLABLE/REQUIRED) - `chunk_id` (STRING, NULLABLE/REQUIRED) - `chunk_data_type` (STRING, NULLABLE/REQUIRED) - `chunk_data` (STRING, NULLABLE/REQUIRED) - `embeddings` (FLOAT, REPEATED) - `file_original_uri` (STRING, NULLABLE/REQUIRED)", "type": "string" }, "ragCorpusId": { "format": "int64", "description": "Optional. The RAG corpus id corresponding to this FeatureView.", "type": "string" } }, "description": "A Vertex Rag source for features that need to be synced to Online Store." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation", "type": "object", "properties": { "columnName": { "type": "string" }, "invalidValuesAllowed": { "description": "If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data.", "type": "boolean" } }, "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * A boolean value that indicates whether the value is valid." }, "GoogleCloudAiplatformV1beta1BatchPredictionJobInstanceConfig": { "id": "GoogleCloudAiplatformV1beta1BatchPredictionJobInstanceConfig", "type": "object", "properties": { "keyField": { "description": "The name of the field that is considered as a key. The values identified by the key field is not included in the transformed instances that is sent to the Model. This is similar to specifying this name of the field in excluded_fields. In addition, the batch prediction output will not include the instances. Instead the output will only include the value of the key field, in a field named `key` in the output: * For `jsonl` output format, the output will have a `key` field instead of the `instance` field. * For `csv`/`bigquery` output format, the output will have have a `key` column instead of the instance feature columns. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.", "type": "string" }, "excludedFields": { "description": "Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.", "type": "array", "items": { "type": "string" } }, "instanceType": { "description": "The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{\"b64\": }`, where `` is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{\"b64\": }`, where `` is the Base64-encoded string of the content of the file.", "type": "string" }, "includedFields": { "description": "Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord.", "type": "array", "items": { "type": "string" } } }, "description": "Configuration defining how to transform batch prediction input instances to the instances that the Model accepts." }, "GoogleCloudAiplatformV1beta1ScheduleConfig": { "description": "Schedule configuration for the FeatureMonitor.", "properties": { "cron": { "description": "Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: \"CRON_TZ=${IANA_TIME_ZONE}\" or \"TZ=${IANA_TIME_ZONE}\". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, \"CRON_TZ=America/New_York 1 * * * *\", or \"TZ=America/New_York 1 * * * *\".", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ScheduleConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1DeleteFeatureValuesOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesOperationMetadata", "type": "object", "description": "Details of operations that delete Feature values.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for Featurestore delete Features values." } } }, "GoogleCloudAiplatformV1beta1ListMetadataStoresResponse": { "id": "GoogleCloudAiplatformV1beta1ListMetadataStoresResponse", "type": "object", "description": "Response message for MetadataService.ListMetadataStores.", "properties": { "metadataStores": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MetadataStore" }, "description": "The MetadataStores found for the Location." }, "nextPageToken": { "description": "A token, which can be sent as ListMetadataStoresRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ColabImage": { "id": "GoogleCloudAiplatformV1beta1ColabImage", "type": "object", "description": "Colab image of the runtime.", "properties": { "description": { "readOnly": true, "type": "string", "description": "Output only. A human-readable description of the specified colab image release, populated by the system. Example: \"Python 3.10\", \"Latest - current Python 3.11\"" }, "releaseName": { "description": "Optional. The release name of the NotebookRuntime Colab image, e.g. \"py310\". If not specified, detault to the latest release.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1GroundingChunk": { "properties": { "maps": { "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMaps", "description": "A grounding chunk from Google Maps. See the `Maps` message for details." }, "image": { "description": "A grounding chunk from an image search result. See the `Image` message for details.", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkImage" }, "retrievedContext": { "description": "A grounding chunk from a data source retrieved by a retrieval tool, such as Vertex AI Search. See the `RetrievedContext` message for details", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext" }, "web": { "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkWeb", "description": "A grounding chunk from a web page, typically from Google Search. See the `Web` message for details." } }, "description": "A piece of evidence that supports a claim made by the model. This is used to show a citation for a claim made by the model. When grounding is enabled, the model returns a `GroundingChunk` that contains a reference to the source of the information.", "id": "GoogleCloudAiplatformV1beta1GroundingChunk", "type": "object" }, "GoogleCloudAiplatformV1beta1Checkpoint": { "description": "Describes the machine learning model version checkpoint.", "properties": { "epoch": { "type": "string", "format": "int64", "description": "The epoch of the checkpoint." }, "checkpointId": { "description": "The ID of the checkpoint.", "type": "string" }, "step": { "description": "The step of the checkpoint.", "format": "int64", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1Checkpoint", "type": "object" }, "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpec": { "id": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpec", "type": "object", "properties": { "trainTrialSpec": { "$ref": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec", "description": "Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched." }, "multiTrialAlgorithm": { "description": "The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`.", "enum": [ "MULTI_TRIAL_ALGORITHM_UNSPECIFIED", "REINFORCEMENT_LEARNING", "GRID_SEARCH" ], "type": "string", "enumDescriptions": [ "Defaults to `REINFORCEMENT_LEARNING`.", "The Reinforcement Learning Algorithm for Multi-trial Neural Architecture Search (NAS).", "The Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS)." ] }, "metric": { "$ref": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecMetricSpec", "description": "Metric specs for the NAS job. Validation for this field is done at `multi_trial_algorithm_spec` field." }, "searchTrialSpec": { "description": "Required. Spec for search trials.", "$ref": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec" } }, "description": "The spec of multi-trial Neural Architecture Search (NAS)." }, "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInput": { "properties": { "metricSpec": { "description": "Required. Spec for tool parameter key value match metric.", "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchSpec" }, "instances": { "description": "Required. Repeated tool parameter key value match instances.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInstance" } } }, "description": "Input for tool parameter key value match metric.", "id": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInput", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDataset": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDataset", "type": "object", "description": "Input dataset spec.", "properties": { "vertexDataset": { "description": "Resource name of the Vertex AI managed dataset.", "type": "string" }, "timestampField": { "description": "The timestamp field. Usually for serving data.", "type": "string" }, "gcsSource": { "description": "Google Cloud Storage data source.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringGcsSource" }, "bigquerySource": { "description": "BigQuery data source.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringBigQuerySource" } } }, "GoogleCloudAiplatformV1beta1GenieSource": { "id": "GoogleCloudAiplatformV1beta1GenieSource", "type": "object", "description": "Contains information about the source of the models generated from Generative AI Studio.", "properties": { "baseModelUri": { "description": "Required. The public base model URI.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1FluencyInstance": { "description": "Spec for fluency instance.", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1FluencyInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingInput": { "description": "Instance and metric spec for RubricBasedInstructionFollowing metric.", "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingInstance", "description": "Required. Instance for RubricBasedInstructionFollowing metric." }, "metricSpec": { "description": "Required. Spec for RubricBasedInstructionFollowing metric.", "$ref": "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingSpec" } }, "id": "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingInput", "type": "object" }, "GoogleCloudAiplatformV1beta1PublisherModelCallToActionViewRestApi": { "description": "Rest API docs.", "properties": { "title": { "description": "Required. The title of the view rest API.", "type": "string" }, "documentations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelDocumentation" }, "description": "Required." } }, "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionViewRestApi", "type": "object" }, "GoogleCloudAiplatformV1beta1Schema": { "id": "GoogleCloudAiplatformV1beta1Schema", "type": "object", "properties": { "properties": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "description": "Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object." }, "additionalProperties": { "description": "Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.", "type": "any" }, "maximum": { "format": "double", "description": "Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.", "type": "number" }, "maxItems": { "type": "string", "description": "Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.", "format": "int64" }, "required": { "description": "Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.", "type": "array", "items": { "type": "string" } }, "minLength": { "type": "string", "format": "int64", "description": "Optional. If type is `STRING`, `min_length` specifies the minimum length of the string." }, "title": { "description": "Optional. Title for the schema.", "type": "string" }, "format": { "description": "Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.", "type": "string" }, "type": { "type": "string", "enumDescriptions": [ "Not specified, should not be used.", "OpenAPI string type", "OpenAPI number type", "OpenAPI integer type", "OpenAPI boolean type", "OpenAPI array type", "OpenAPI object type", "Null type" ], "enum": [ "TYPE_UNSPECIFIED", "STRING", "NUMBER", "INTEGER", "BOOLEAN", "ARRAY", "OBJECT", "NULL" ], "description": "Optional. Data type of the schema field." }, "enum": { "description": "Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:[\"EAST\", \"NORTH\", \"SOUTH\", \"WEST\"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:[\"101\", \"201\", \"301\"]}`", "type": "array", "items": { "type": "string" } }, "minProperties": { "type": "string", "description": "Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.", "format": "int64" }, "example": { "description": "Optional. Example of an instance of this schema.", "type": "any" }, "defs": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "description": "Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema." }, "propertyOrdering": { "type": "array", "items": { "type": "string" }, "description": "Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties." }, "pattern": { "description": "Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.", "type": "string" }, "nullable": { "description": "Optional. Indicates if the value of this field can be null.", "type": "boolean" }, "description": { "description": "Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.", "type": "string" }, "minimum": { "type": "number", "format": "double", "description": "Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value." }, "minItems": { "description": "Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.", "format": "int64", "type": "string" }, "items": { "description": "Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.", "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "maxProperties": { "type": "string", "description": "Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.", "format": "int64" }, "ref": { "description": "Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named \"Pet\": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the \"pet\" property is a reference to the schema node named \"Pet\". See details in https://json-schema.org/understanding-json-schema/structuring", "type": "string" }, "default": { "description": "Optional. Default value to use if the field is not specified.", "type": "any" }, "maxLength": { "type": "string", "description": "Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.", "format": "int64" }, "anyOf": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "description": "Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`." } }, "description": "Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object)." }, "GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolRequest": { "id": "GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolRequest", "type": "object", "description": "Request message for CreateDeploymentResourcePool method.", "properties": { "deploymentResourcePool": { "$ref": "GoogleCloudAiplatformV1beta1DeploymentResourcePool", "description": "Required. The DeploymentResourcePool to create." }, "deploymentResourcePoolId": { "description": "Required. The ID to use for the DeploymentResourcePool, which will become the final component of the DeploymentResourcePool's resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessResult": { "description": "Spec for question answering helpfulness result.", "properties": { "confidence": { "type": "number", "readOnly": true, "description": "Output only. Confidence for question answering helpfulness score.", "format": "float" }, "score": { "description": "Output only. Question Answering Helpfulness score.", "format": "float", "type": "number", "readOnly": true }, "explanation": { "description": "Output only. Explanation for question answering helpfulness score.", "readOnly": true, "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessResult", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryRecallResults": { "description": "Results for TrajectoryRecall metric.", "properties": { "trajectoryRecallMetricValues": { "description": "Output only. TrajectoryRecall metric values.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryRecallMetricValue" }, "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1TrajectoryRecallResults", "type": "object" }, "GoogleCloudAiplatformV1beta1GroundingChunkImage": { "id": "GoogleCloudAiplatformV1beta1GroundingChunkImage", "type": "object", "description": "An `Image` chunk is a piece of evidence that comes from an image search result. It contains the URI of the image search result and the URI of the image. This is used to provide the user with a link to the source of the information.", "properties": { "sourceUri": { "description": "The URI of the image search result page.", "type": "string" }, "title": { "description": "The title of the image search result page.", "type": "string" }, "imageUri": { "description": "The URI of the image.", "type": "string" }, "domain": { "description": "The domain of the image search result page.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SafetyResult": { "properties": { "score": { "format": "float", "description": "Output only. Safety score.", "readOnly": true, "type": "number" }, "confidence": { "type": "number", "readOnly": true, "description": "Output only. Confidence for safety score.", "format": "float" }, "explanation": { "readOnly": true, "type": "string", "description": "Output only. Explanation for safety score." } }, "description": "Spec for safety result.", "id": "GoogleCloudAiplatformV1beta1SafetyResult", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateEndpointLongRunningRequest": { "description": "Request message for EndpointService.UpdateEndpointLongRunning.", "properties": { "endpoint": { "$ref": "GoogleCloudAiplatformV1beta1Endpoint", "description": "Required. The Endpoint which replaces the resource on the server. Currently we only support updating the `client_connection_config` field, all the other fields' update will be blocked." } }, "id": "GoogleCloudAiplatformV1beta1UpdateEndpointLongRunningRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1EventMetadata": { "id": "GoogleCloudAiplatformV1beta1EventMetadata", "type": "object", "description": "Metadata relating to a LLM response event.", "properties": { "longRunningToolIds": { "type": "array", "items": { "type": "string" }, "description": "Optional. Set of ids of the long running function calls. Agent client will know from this field about which function call is long running. Only valid for function call event." }, "interrupted": { "description": "Optional. Flag indicating that LLM was interrupted when generating the content. Usually it's due to user interruption during a bidi streaming.", "type": "boolean" }, "partial": { "description": "Optional. Indicates whether the text content is part of a unfinished text stream. Only used for streaming mode and when the content is plain text.", "type": "boolean" }, "turnComplete": { "description": "Optional. Indicates whether the response from the model is complete. Only used for streaming mode.", "type": "boolean" }, "branch": { "description": "Optional. The branch of the event. The format is like agent_1.agent_2.agent_3, where agent_1 is the parent of agent_2, and agent_2 is the parent of agent_3. Branch is used when multiple child agents shouldn't see their siblings' conversation history.", "type": "string" }, "outputTranscription": { "description": "Optional. Audio transcription of model output.", "$ref": "GoogleCloudAiplatformV1beta1Transcription" }, "groundingMetadata": { "description": "Optional. Metadata returned to client when grounding is enabled.", "$ref": "GoogleCloudAiplatformV1beta1GroundingMetadata" }, "inputTranscription": { "$ref": "GoogleCloudAiplatformV1beta1Transcription", "description": "Optional. Audio transcription of user input." }, "customMetadata": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "The custom metadata of the LlmResponse." } } }, "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigSimilaritySearchConfig": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigSimilaritySearchConfig", "type": "object", "properties": { "embeddingModel": { "description": "Required. The model used to generate embeddings to lookup similar memories. Format: `projects/{project}/locations/{location}/publishers/google/models/{model}`.", "type": "string" } }, "description": "Configuration for how to perform similarity search on memories." }, "GoogleCloudAiplatformV1beta1GcsSource": { "description": "The Google Cloud Storage location for the input content.", "properties": { "uris": { "description": "Required. Google Cloud Storage URI(-s) to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/wildcards.", "type": "array", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1beta1GcsSource", "type": "object" }, "GoogleCloudAiplatformV1beta1SecretRef": { "properties": { "secret": { "description": "Required. The name of the secret in Cloud Secret Manager. Format: {secret_name}.", "type": "string" }, "version": { "description": "The Cloud Secret Manager secret version. Can be 'latest' for the latest version, an integer for a specific version, or a version alias.", "type": "string" } }, "description": "Reference to a secret stored in the Cloud Secret Manager that will provide the value for this environment variable.", "id": "GoogleCloudAiplatformV1beta1SecretRef", "type": "object" }, "GoogleCloudAiplatformV1beta1ShieldedVmConfig": { "properties": { "enableSecureBoot": { "description": "Defines whether the instance has [Secure Boot](https://cloud.google.com/compute/shielded-vm/docs/shielded-vm#secure-boot) enabled. Secure Boot helps ensure that the system only runs authentic software by verifying the digital signature of all boot components, and halting the boot process if signature verification fails.", "type": "boolean" } }, "description": "A set of Shielded Instance options. See [Images using supported Shielded VM features](https://cloud.google.com/compute/docs/instances/modifying-shielded-vm).", "id": "GoogleCloudAiplatformV1beta1ShieldedVmConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1PointwiseMetricInstance": { "id": "GoogleCloudAiplatformV1beta1PointwiseMetricInstance", "type": "object", "description": "Pointwise metric instance. Usually one instance corresponds to one row in an evaluation dataset.", "properties": { "contentMapInstance": { "$ref": "GoogleCloudAiplatformV1beta1ContentMap", "description": "Key-value contents for the mutlimodality input, including text, image, video, audio, and pdf, etc. The key is placeholder in metric prompt template, and the value is the multimodal content." }, "jsonInstance": { "description": "Instance specified as a json string. String key-value pairs are expected in the json_instance to render PointwiseMetricSpec.instance_prompt_template.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionClassificationPredictionResult": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionClassificationPredictionResult", "type": "object", "description": "Prediction output format for Image and Text Classification.", "properties": { "displayNames": { "description": "The display names of the AnnotationSpecs that had been identified, order matches the IDs.", "type": "array", "items": { "type": "string" } }, "confidences": { "type": "array", "items": { "format": "float", "type": "number" }, "description": "The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids." }, "ids": { "type": "array", "items": { "type": "string", "format": "int64" }, "description": "The resource IDs of the AnnotationSpecs that had been identified." } } }, "GoogleCloudAiplatformV1beta1ExamplesExampleGcsSource": { "properties": { "dataFormat": { "enum": [ "DATA_FORMAT_UNSPECIFIED", "JSONL" ], "description": "The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported.", "type": "string", "enumDescriptions": [ "Format unspecified, used when unset.", "Examples are stored in JSONL files." ] }, "gcsSource": { "description": "The Cloud Storage location for the input instances.", "$ref": "GoogleCloudAiplatformV1beta1GcsSource" } }, "description": "The Cloud Storage input instances.", "id": "GoogleCloudAiplatformV1beta1ExamplesExampleGcsSource", "type": "object" }, "GoogleCloudAiplatformV1beta1DirectRawPredictRequest": { "id": "GoogleCloudAiplatformV1beta1DirectRawPredictRequest", "type": "object", "description": "Request message for PredictionService.DirectRawPredict.", "properties": { "methodName": { "description": "Fully qualified name of the API method being invoked to perform predictions. Format: `/namespace.Service/Method/` Example: `/tensorflow.serving.PredictionService/Predict`", "type": "string" }, "input": { "description": "The prediction input.", "format": "byte", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition": { "description": "Monitoring alert triggered condition.", "properties": { "threshold": { "description": "A condition that compares a stats value against a threshold. Alert will be triggered if value above the threshold.", "format": "double", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition", "type": "object" }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateWarmPoolConfig": { "properties": { "targetInstanceCount": { "type": "integer", "format": "int32", "description": "Optional. The target number of pre-warmed instances to maintain." } }, "description": "Configuration for a warm pool of sandbox instances.", "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateWarmPoolConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationRunMetricComputationBasedMetricSpec": { "id": "GoogleCloudAiplatformV1beta1EvaluationRunMetricComputationBasedMetricSpec", "type": "object", "description": "Specification for a computation based metric.", "properties": { "type": { "description": "Required. The type of the computation based metric.", "enum": [ "COMPUTATION_BASED_METRIC_TYPE_UNSPECIFIED", "EXACT_MATCH", "BLEU", "ROUGE" ], "type": "string", "enumDescriptions": [ "Unspecified computation based metric type.", "Exact match metric.", "BLEU metric.", "ROUGE metric." ] }, "parameters": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. A map of parameters for the metric, e.g. {\"rouge_type\": \"rougeL\"}." } } }, "GoogleCloudAiplatformV1beta1TensorboardRun": { "id": "GoogleCloudAiplatformV1beta1TensorboardRun", "type": "object", "properties": { "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when this TensorboardRun was created.", "readOnly": true, "type": "string" }, "description": { "description": "Description of this TensorboardRun.", "type": "string" }, "etag": { "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "displayName": { "description": "Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.", "type": "string" }, "name": { "readOnly": true, "type": "string", "description": "Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`" }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this TensorboardRun was last updated." }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." } }, "description": "TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc" }, "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfig": { "description": "Traffic distribution configuration.", "properties": { "trafficSplitAlwaysLatest": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfigTrafficSplitAlwaysLatest", "description": "Optional. Traffic distribution configuration, where all traffic is sent to the latest Runtime Revision." }, "trafficSplitManual": { "description": "Optional. Manual traffic distribution configuration, where the user specifies the Runtime Revision IDs and the percentage of traffic to send to each.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfigTrafficSplitManual" } }, "id": "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1GroundingMetadata": { "id": "GoogleCloudAiplatformV1beta1GroundingMetadata", "type": "object", "properties": { "groundingChunks": { "description": "A list of supporting references retrieved from the grounding source. This field is populated when the grounding source is Google Search, Vertex AI Search, or Google Maps.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingChunk" } }, "retrievalQueries": { "type": "array", "items": { "type": "string" }, "description": "Optional. The queries that were executed by the retrieval tools. This field is populated only when the grounding source is a retrieval tool, such as Vertex AI Search." }, "sourceFlaggingUris": { "description": "Optional. Output only. A list of URIs that can be used to flag a place or review for inappropriate content. This field is populated only when the grounding source is Google Maps.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingMetadataSourceFlaggingUri" }, "readOnly": true }, "googleMapsWidgetContextToken": { "readOnly": true, "type": "string", "description": "Optional. Output only. A token that can be used to render a Google Maps widget with the contextual data. This field is populated only when the grounding source is Google Maps." }, "groundingSupports": { "description": "Optional. A list of grounding supports that connect the generated content to the grounding chunks. This field is populated when the grounding source is Google Search or Vertex AI Search.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingSupport" } }, "imageSearchQueries": { "type": "array", "items": { "type": "string" }, "description": "Optional. The image search queries that were used to generate the content. This field is populated only when the grounding source is Google Search with the Image Search search_type enabled." }, "retrievalMetadata": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1RetrievalMetadata", "description": "Optional. Output only. Metadata related to the retrieval grounding source." }, "webSearchQueries": { "description": "Optional. The web search queries that were used to generate the content. This field is populated only when the grounding source is Google Search.", "type": "array", "items": { "type": "string" } }, "searchEntryPoint": { "$ref": "GoogleCloudAiplatformV1beta1SearchEntryPoint", "description": "Optional. A web search entry point that can be used to display search results. This field is populated only when the grounding source is Google Search." } }, "description": "Information about the sources that support the content of a response. When grounding is enabled, the model returns citations for claims in the response. This object contains the retrieved sources." }, "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleGeneratedMemory": { "properties": { "fact": { "description": "Required. Represents the fact to generate a memory from.", "type": "string" }, "topics": { "description": "Optional. Represents the list of topics that the memory should be associated with. For example, use `custom_memory_topic_label = \"jargon\"` if the extracted memory is an example of memory extraction for the custom topic `jargon`.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryTopicId" } } }, "description": "A memory generated by the operation.", "id": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleGeneratedMemory", "type": "object" }, "GoogleCloudAiplatformV1beta1RecommendSpecRequest": { "description": "Request message for ModelService.RecommendSpec.", "properties": { "checkUserQuota": { "description": "Optional. If true, check user quota for the recommended regions. Returns all the machine spec in regions they are available, and also the user quota state for each machine type in each region.", "type": "boolean" }, "gcsUri": { "description": "Required. The Google Cloud Storage URI of the custom model, storing weights and config files (which can be used to infer the base model).", "type": "string" }, "checkMachineAvailability": { "description": "Optional. If true, check machine availability for the recommended regions. Only return the machine spec in regions where the machine is available.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1RecommendSpecRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1RagVectorDbConfigVertexFeatureStore": { "id": "GoogleCloudAiplatformV1beta1RagVectorDbConfigVertexFeatureStore", "type": "object", "description": "The config for the Vertex Feature Store.", "properties": { "featureViewResourceName": { "description": "The resource name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ExportFeatureValuesOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1ExportFeatureValuesOperationMetadata", "type": "object", "description": "Details of operations that exports Features values.", "properties": { "genericMetadata": { "description": "Operation metadata for Featurestore export Feature values.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1beta1WorkerPoolSpec": { "properties": { "lustreMounts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LustreMount" }, "description": "Optional. List of Lustre mounts." }, "machineSpec": { "$ref": "GoogleCloudAiplatformV1beta1MachineSpec", "description": "Optional. Immutable. The specification of a single machine." }, "diskSpec": { "$ref": "GoogleCloudAiplatformV1beta1DiskSpec", "description": "Disk spec." }, "replicaCount": { "type": "string", "format": "int64", "description": "Optional. The number of worker replicas to use for this worker pool." }, "containerSpec": { "$ref": "GoogleCloudAiplatformV1beta1ContainerSpec", "description": "The custom container task." }, "pythonPackageSpec": { "description": "The Python packaged task.", "$ref": "GoogleCloudAiplatformV1beta1PythonPackageSpec" }, "nfsMounts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NfsMount" }, "description": "Optional. List of NFS mount spec." } }, "description": "Represents the spec of a worker pool in a job.", "id": "GoogleCloudAiplatformV1beta1WorkerPoolSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInput": { "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInput", "type": "object", "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInstance", "description": "Required. Question answering relevance instance." }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceSpec", "description": "Required. Spec for question answering relevance score metric." } }, "description": "Input for question answering relevance metric." }, "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecIntValueCondition": { "properties": { "values": { "description": "Required. Matches values of the parent parameter of 'INTEGER' type. All values must lie in `integer_value_spec` of parent parameter.", "type": "array", "items": { "format": "int64", "type": "string" } } }, "description": "Represents the spec to match integer values from parent parameter.", "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecIntValueCondition", "type": "object" }, "GoogleCloudAiplatformV1beta1SetPublisherModelConfigRequest": { "properties": { "publisherModelConfig": { "description": "Required. The publisher model config.", "$ref": "GoogleCloudAiplatformV1beta1PublisherModelConfig" } }, "description": "Request message for EndpointService.SetPublisherModelConfig.", "id": "GoogleCloudAiplatformV1beta1SetPublisherModelConfigRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadata", "type": "object", "properties": { "timeSeriesIdentifierColumn": { "description": "The column name of the time series identifier column that identifies the time series.", "type": "string" }, "timeColumn": { "description": "The column name of the time column that identifies time order in the time series.", "type": "string" }, "inputConfig": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataInputConfig" } }, "description": "The metadata of Datasets that contain time series data." }, "GoogleCloudAiplatformV1beta1ListEvaluationMetricsResponse": { "id": "GoogleCloudAiplatformV1beta1ListEvaluationMetricsResponse", "type": "object", "properties": { "evaluationMetrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationMetric" }, "description": "List of EvaluationMetrics in the requested page." }, "nextPageToken": { "description": "A token to retrieve the next page of results.", "type": "string" } }, "description": "Response message for EvaluationMetricService.ListEvaluationMetrics." }, "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseHeader": { "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseHeader", "type": "object", "properties": { "entityType": { "description": "The resource name of the EntityType from the ReadFeatureValuesRequest. Value format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`.", "type": "string" }, "featureDescriptors": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseFeatureDescriptor" }, "description": "List of Feature metadata corresponding to each piece of ReadFeatureValuesResponse.EntityView.data." } }, "description": "Response header with metadata for the requested ReadFeatureValuesRequest.entity_type and Features." }, "GoogleCloudAiplatformV1beta1StudySpecDecayCurveAutomatedStoppingSpec": { "id": "GoogleCloudAiplatformV1beta1StudySpecDecayCurveAutomatedStoppingSpec", "type": "object", "properties": { "useElapsedDuration": { "description": "True if Measurement.elapsed_duration is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.step_count will be used as the x-axis.", "type": "boolean" } }, "description": "The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far." }, "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTarget": { "properties": { "vertexModel": { "description": "Model in Vertex AI Model Registry.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTargetVertexModelSource" } }, "description": "The monitoring target refers to the entity that is subject to analysis. e.g. Vertex AI Model version.", "id": "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTarget", "type": "object" }, "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotation": { "properties": { "queryType": { "type": "string", "enumDescriptions": [ "Unspecified query type for model error analysis.", "Query similar samples across all classes in the dataset.", "Query similar samples from the same class of the input sample.", "Query dissimilar samples from the same class of the input sample." ], "enum": [ "QUERY_TYPE_UNSPECIFIED", "ALL_SIMILAR", "SAME_CLASS_SIMILAR", "SAME_CLASS_DISSIMILAR" ], "description": "The query type used for finding the attributed items." }, "attributedItems": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotationAttributedItem" }, "description": "Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type." }, "outlierThreshold": { "type": "number", "format": "double", "description": "The threshold used to determine if this annotation is an outlier or not." }, "outlierScore": { "type": "number", "description": "The outlier score of this annotated item. Usually defined as the min of all distances from attributed items.", "format": "double" } }, "description": "Model error analysis for each annotation.", "id": "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotation", "type": "object" }, "GoogleCloudAiplatformV1beta1UploadRagFileRequest": { "properties": { "ragFile": { "$ref": "GoogleCloudAiplatformV1beta1RagFile", "description": "Required. The RagFile to upload." }, "uploadRagFileConfig": { "description": "Required. The config for the RagFiles to be uploaded into the RagCorpus. VertexRagDataService.UploadRagFile.", "$ref": "GoogleCloudAiplatformV1beta1UploadRagFileConfig" } }, "description": "Request message for VertexRagDataService.UploadRagFile.", "id": "GoogleCloudAiplatformV1beta1UploadRagFileRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1TaskStatusDetailsChange": { "properties": { "newTaskStatus": { "description": "Required. The complete state of the task's status *after* the change.", "$ref": "GoogleCloudAiplatformV1beta1TaskStatusDetails" } }, "description": "Represents a change to the task's status details.", "id": "GoogleCloudAiplatformV1beta1TaskStatusDetailsChange", "type": "object" }, "GoogleCloudAiplatformV1beta1AvroSource": { "description": "The storage details for Avro input content.", "properties": { "gcsSource": { "description": "Required. Google Cloud Storage location.", "$ref": "GoogleCloudAiplatformV1beta1GcsSource" } }, "id": "GoogleCloudAiplatformV1beta1AvroSource", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfig": { "properties": { "trainingPredictionSkewDetectionConfig": { "description": "The config for skew between training data and prediction data.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig" }, "explanationConfig": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfig", "description": "The config for integrating with Vertex Explainable AI." }, "trainingDataset": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingDataset", "description": "Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified." }, "predictionDriftDetectionConfig": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig", "description": "The config for drift of prediction data." } }, "description": "The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.", "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1MemoryFilter": { "id": "GoogleCloudAiplatformV1beta1MemoryFilter", "type": "object", "description": "Filter to apply when retrieving memories.", "properties": { "key": { "description": "Represents the key of the filter. For example, \"author\" would apply to `metadata` entries with the key \"author\".", "type": "string" }, "op": { "type": "string", "enumDescriptions": [ "Represents an unspecified operator. Defaults to EQUAL.", "Equal to.", "Greater than.", "Less than." ], "enum": [ "OPERATOR_UNSPECIFIED", "EQUAL", "GREATER_THAN", "LESS_THAN" ], "description": "Represents the operator to apply to the filter. If not set, then EQUAL will be used." }, "value": { "$ref": "GoogleCloudAiplatformV1beta1MemoryMetadataValue", "description": "Represents the value to compare to." }, "negate": { "description": "Indicates whether the filter will be negated.", "type": "boolean" } } }, "GoogleApiHttpBody": { "properties": { "contentType": { "description": "The HTTP Content-Type header value specifying the content type of the body.", "type": "string" }, "data": { "type": "string", "description": "The HTTP request/response body as raw binary.", "format": "byte" }, "extensions": { "type": "array", "items": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." } }, "description": "Application specific response metadata. Must be set in the first response for streaming APIs." } }, "description": "Message that represents an arbitrary HTTP body. It should only be used for payload formats that can't be represented as JSON, such as raw binary or an HTML page. This message can be used both in streaming and non-streaming API methods in the request as well as the response. It can be used as a top-level request field, which is convenient if one wants to extract parameters from either the URL or HTTP template into the request fields and also want access to the raw HTTP body. Example: message GetResourceRequest { // A unique request id. string request_id = 1; // The raw HTTP body is bound to this field. google.api.HttpBody http_body = 2; } service ResourceService { rpc GetResource(GetResourceRequest) returns (google.api.HttpBody); rpc UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); } Example with streaming methods: service CaldavService { rpc GetCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); rpc UpdateCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); } Use of this type only changes how the request and response bodies are handled, all other features will continue to work unchanged.", "id": "GoogleApiHttpBody", "type": "object" }, "GoogleCloudAiplatformV1beta1Execution": { "properties": { "displayName": { "description": "User provided display name of the Execution. May be up to 128 Unicode characters.", "type": "string" }, "schemaVersion": { "description": "The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", "type": "string" }, "state": { "type": "string", "enumDescriptions": [ "Unspecified Execution state", "The Execution is new", "The Execution is running", "The Execution has finished running", "The Execution has failed", "The Execution completed through Cache hit.", "The Execution was cancelled." ], "description": "The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.", "enum": [ "STATE_UNSPECIFIED", "NEW", "RUNNING", "COMPLETE", "FAILED", "CACHED", "CANCELLED" ] }, "etag": { "description": "An eTag used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "description": { "description": "Description of the Execution", "type": "string" }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when this Execution was created.", "readOnly": true, "type": "string" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded)." }, "schemaTitle": { "description": "The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.", "type": "string" }, "metadata": { "description": "Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this Execution was last updated.", "format": "google-datetime" }, "name": { "description": "Output only. The resource name of the Execution.", "type": "string", "readOnly": true } }, "description": "Instance of a general execution.", "id": "GoogleCloudAiplatformV1beta1Execution", "type": "object" }, "GoogleCloudAiplatformV1beta1ExactMatchInput": { "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1ExactMatchSpec", "description": "Required. Spec for exact match metric." }, "instances": { "description": "Required. Repeated exact match instances.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ExactMatchInstance" } } }, "description": "Input for exact match metric.", "id": "GoogleCloudAiplatformV1beta1ExactMatchInput", "type": "object" }, "GoogleCloudAiplatformV1beta1SuggestTrialsMetadata": { "id": "GoogleCloudAiplatformV1beta1SuggestTrialsMetadata", "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for suggesting Trials." }, "clientId": { "description": "The identifier of the client that is requesting the suggestion. If multiple SuggestTrialsRequests have the same `client_id`, the service will return the identical suggested Trial if the Trial is pending, and provide a new Trial if the last suggested Trial was completed.", "type": "string" } }, "description": "Details of operations that perform Trials suggestion." }, "GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData": { "description": "Instance data used to populate placeholders in a metric prompt template.", "properties": { "contents": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceDataContents", "description": "List of Gemini content data." }, "text": { "description": "Text data.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData", "type": "object" }, "GoogleCloudAiplatformV1beta1ListTrialsResponse": { "description": "Response message for VizierService.ListTrials.", "properties": { "trials": { "description": "The Trials associated with the Study.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Trial" } }, "nextPageToken": { "description": "Pass this token as the `page_token` field of the request for a subsequent call. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListTrialsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation", "type": "object", "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.", "properties": { "columnName": { "type": "string" }, "timeFormat": { "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation": { "properties": { "columnName": { "type": "string" } }, "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding.", "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTabularClassificationPredictionResult": { "description": "Prediction output format for Tabular Classification.", "properties": { "classes": { "type": "array", "items": { "type": "string" }, "description": "The name of the classes being classified, contains all possible values of the target column." }, "scores": { "description": "The model's confidence in each class being correct, higher value means higher confidence. The N-th score corresponds to the N-th class in classes.", "type": "array", "items": { "type": "number", "format": "float" } } }, "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTabularClassificationPredictionResult", "type": "object" }, "GoogleCloudAiplatformV1beta1ActivateOnlineEvaluatorRequest": { "description": "Request message for ActivateOnlineEvaluator.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1ActivateOnlineEvaluatorRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateSpecialistPoolOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1UpdateSpecialistPoolOperationMetadata", "type": "object", "properties": { "specialistPool": { "description": "Output only. The name of the SpecialistPool to which the specialists are being added. Format: `projects/{project_id}/locations/{location_id}/specialistPools/{specialist_pool}`", "readOnly": true, "type": "string" }, "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Runtime operation metadata for SpecialistPoolService.UpdateSpecialistPool." }, "GoogleCloudAiplatformV1beta1RagMetadataSchemaDetails": { "properties": { "type": { "type": "string", "enumDescriptions": [ "Unspecified type.", "Integer type.", "Float type.", "String type.", "Supported formats: %Y-%m-%dT%H:%M:%E*S%E*z (absl::RFC3339_full) %Y-%m-%dT%H:%M:%E*S %Y-%m-%dT%H:%M%E*z %Y-%m-%dT%H:%M %Y-%m-%dT%H%E*z %Y-%m-%dT%H %Y-%m-%d%E*z %Y-%m-%d %Y-%m %Y", "Boolean type.", "List type. - Each element in the list must be of the exact same data schema; otherwise, they are invalid arguments. - Elements cannot be another list (no list of list)." ], "enum": [ "DATA_TYPE_UNSPECIFIED", "INTEGER", "FLOAT", "STRING", "DATETIME", "BOOLEAN", "LIST" ], "description": "Type of the metadata." }, "listConfig": { "description": "Config for List data type.", "$ref": "GoogleCloudAiplatformV1beta1RagMetadataSchemaDetailsListConfig" }, "searchStrategy": { "$ref": "GoogleCloudAiplatformV1beta1RagMetadataSchemaDetailsSearchStrategy", "description": "The search strategy for the metadata value of the `key`." }, "granularity": { "type": "string", "enumDescriptions": [ "Unspecified granularity.", "RagFile-level granularity." ], "description": "The granularity associated with this RagMetadataSchema.", "enum": [ "GRANULARITY_UNSPECIFIED", "GRANULARITY_FILE_LEVEL" ] } }, "description": "Data schema details indicates the data type and the data struct corresponding to the key of user specified metadata.", "id": "GoogleCloudAiplatformV1beta1RagMetadataSchemaDetails", "type": "object" }, "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig": { "id": "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig", "type": "object", "properties": { "enablePrivateServiceConnect": { "description": "Required. If true, expose the IndexEndpoint via private service connect.", "type": "boolean" }, "pscAutomationConfigs": { "description": "Optional. List of projects and networks where the PSC endpoints will be created. This field is used by Online Inference(Prediction) only.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PSCAutomationConfig" } }, "enableSecurePrivateServiceConnect": { "description": "Optional. If set to true, enable secure private service connect with IAM authorization. Otherwise, private service connect will be done without authorization. Note latency will be slightly increased if authorization is enabled.", "type": "boolean" }, "projectAllowlist": { "type": "array", "items": { "type": "string" }, "description": "A list of Projects from which the forwarding rule will target the service attachment." }, "serviceAttachment": { "type": "string", "readOnly": true, "description": "Output only. The name of the generated service attachment resource. This is only populated if the endpoint is deployed with PrivateServiceConnect." } }, "description": "Represents configuration for private service connect." }, "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfig": { "id": "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfig", "type": "object", "description": "The Evalution configuration used for the evaluation run.", "properties": { "metrics": { "description": "Required. The metrics to be calculated in the evaluation run.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunMetric" } }, "rubricConfigs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRubricConfig" }, "description": "Optional. The rubric configs for the evaluation run. They are used to generate rubrics which can be used by rubric-based metrics. Multiple rubric configs can be specified for rubric generation but only one rubric config can be used for a rubric-based metric. If more than one rubric config is provided, the evaluation metric must specify a rubric group key. Note that if a generation spec is specified on both a rubric config and an evaluation metric, the rubrics generated for the metric will be used for evaluation." }, "datasetCustomMetrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DatasetCustomMetric" }, "description": "Optional. Specifications for custom dataset-level aggregations." }, "autoraterConfig": { "description": "Optional. The autorater config for the evaluation run.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigAutoraterConfig" }, "promptTemplate": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigPromptTemplate", "description": "The prompt template used for inference. The values for variables in the prompt template are defined in EvaluationItem.EvaluationPrompt.PromptTemplateData.values." }, "outputConfig": { "description": "Optional. The output config for the evaluation run.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigOutputConfig" }, "lossAnalysisConfig": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LossAnalysisConfig" }, "description": "Optional. Specifications for loss analysis. Each config can be specified for one metric." } } }, "GoogleCloudAiplatformV1beta1FeatureSelectionConfig": { "properties": { "featureConfigs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureSelectionConfigFeatureConfig" }, "description": "Optional. A list of features to be monitored and each feature's drift threshold." } }, "description": "Feature selection configuration for the FeatureMonitor.", "id": "GoogleCloudAiplatformV1beta1FeatureSelectionConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation", "type": "object", "properties": { "invalidValuesAllowed": { "description": "If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data.", "type": "boolean" }, "columnName": { "type": "string" }, "timeFormat": { "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)", "type": "string" } }, "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the * timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecasting": { "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model.", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputs" }, "metadata": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingMetadata", "description": "The metadata information." } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecasting", "type": "object" }, "GoogleCloudAiplatformV1beta1Tensorboard": { "id": "GoogleCloudAiplatformV1beta1Tensorboard", "type": "object", "properties": { "runCount": { "format": "int32", "description": "Output only. The number of Runs stored in this Tensorboard.", "readOnly": true, "type": "integer" }, "etag": { "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "description": { "description": "Description of this Tensorboard.", "type": "string" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this Tensorboard was created." }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this Tensorboard was last updated.", "readOnly": true, "type": "string" }, "isDefault": { "description": "Used to indicate if the TensorBoard instance is the default one. Each project & region can have at most one default TensorBoard instance. Creation of a default TensorBoard instance and updating an existing TensorBoard instance to be default will mark all other TensorBoard instances (if any) as non default.", "type": "boolean" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key." }, "blobStoragePathPrefix": { "description": "Output only. Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.", "readOnly": true, "type": "string" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "name": { "type": "string", "readOnly": true, "description": "Output only. Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`" }, "displayName": { "description": "Required. User provided name of this Tensorboard.", "type": "string" } }, "description": "Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a Google Cloud project. If needed users can also create extra Tensorboards in their projects." }, "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataInputConfig": { "id": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataInputConfig", "type": "object", "properties": { "gcsSource": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataGcsSource" }, "bigquerySource": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataBigQuerySource" } }, "description": "The tables Dataset's data source. The Dataset doesn't store the data directly, but only pointer(s) to its data." }, "GoogleCloudAiplatformV1beta1GoogleDriveSourceResourceId": { "id": "GoogleCloudAiplatformV1beta1GoogleDriveSourceResourceId", "type": "object", "properties": { "resourceType": { "description": "Required. The type of the Google Drive resource.", "enum": [ "RESOURCE_TYPE_UNSPECIFIED", "RESOURCE_TYPE_FILE", "RESOURCE_TYPE_FOLDER" ], "type": "string", "enumDescriptions": [ "Unspecified resource type.", "File resource type.", "Folder resource type." ] }, "resourceId": { "description": "Required. The ID of the Google Drive resource.", "type": "string" } }, "description": "The type and ID of the Google Drive resource." }, "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataFeatureValueDomain": { "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataFeatureValueDomain", "type": "object", "properties": { "minValue": { "type": "number", "description": "The minimum permissible value for this feature.", "format": "float" }, "originalStddev": { "description": "If this input feature has been normalized to a standard deviation of 1.0, the original_stddev specifies the standard deviation of the domain prior to normalization.", "format": "float", "type": "number" }, "maxValue": { "type": "number", "description": "The maximum permissible value for this feature.", "format": "float" }, "originalMean": { "type": "number", "format": "float", "description": "If this input feature has been normalized to a mean value of 0, the original_mean specifies the mean value of the domain prior to normalization." } }, "description": "Domain details of the input feature value. Provides numeric information about the feature, such as its range (min, max). If the feature has been pre-processed, for example with z-scoring, then it provides information about how to recover the original feature. For example, if the input feature is an image and it has been pre-processed to obtain 0-mean and stddev = 1 values, then original_mean, and original_stddev refer to the mean and stddev of the original feature (e.g. image tensor) from which input feature (with mean = 0 and stddev = 1) was obtained." }, "GoogleCloudAiplatformV1beta1RolloutOptions": { "properties": { "maxSurgeReplicas": { "format": "int32", "description": "Absolute count of allowed additional replicas.", "type": "integer" }, "maxUnavailableReplicas": { "description": "Absolute count of replicas allowed to be unavailable.", "format": "int32", "type": "integer" }, "maxUnavailablePercentage": { "type": "integer", "description": "Percentage of replicas allowed to be unavailable. For autoscaling deployments, this refers to the target replica count.", "format": "int32" }, "maxSurgePercentage": { "description": "Percentage of allowed additional replicas. For autoscaling deployments, this refers to the target replica count.", "format": "int32", "type": "integer" }, "previousDeployedModel": { "description": "ID of the DeployedModel that this deployment should replace.", "type": "string" }, "revisionNumber": { "description": "Output only. Read-only. Revision number determines the relative priority of DeployedModels in the same rollout. The DeployedModel with the largest revision number specifies the intended state of the deployment.", "format": "int32", "type": "integer", "readOnly": true } }, "description": "Configuration for rolling deployments.", "id": "GoogleCloudAiplatformV1beta1RolloutOptions", "type": "object" }, "GoogleCloudAiplatformV1beta1RougeInput": { "id": "GoogleCloudAiplatformV1beta1RougeInput", "type": "object", "description": "Input for rouge metric.", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1RougeSpec", "description": "Required. Spec for rouge score metric." }, "instances": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RougeInstance" }, "description": "Required. Repeated rouge instances." } } }, "GoogleCloudAiplatformV1beta1ExternalApi": { "description": "Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec.", "properties": { "simpleSearchParams": { "$ref": "GoogleCloudAiplatformV1beta1ExternalApiSimpleSearchParams", "description": "Parameters for the simple search API." }, "endpoint": { "description": "The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search", "type": "string" }, "apiSpec": { "description": "The API spec that the external API implements.", "enum": [ "API_SPEC_UNSPECIFIED", "SIMPLE_SEARCH", "ELASTIC_SEARCH" ], "type": "string", "enumDescriptions": [ "Unspecified API spec. This value should not be used.", "Simple search API spec.", "Elastic search API spec." ] }, "apiAuth": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1ApiAuth", "description": "The authentication config to access the API. Deprecated. Please use auth_config instead." }, "authConfig": { "$ref": "GoogleCloudAiplatformV1beta1AuthConfig", "description": "The authentication config to access the API." }, "elasticSearchParams": { "$ref": "GoogleCloudAiplatformV1beta1ExternalApiElasticSearchParams", "description": "Parameters for the elastic search API." } }, "id": "GoogleCloudAiplatformV1beta1ExternalApi", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingDataset": { "description": "Training Dataset information.", "properties": { "targetField": { "description": "The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.", "type": "string" }, "gcsSource": { "description": "The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.", "$ref": "GoogleCloudAiplatformV1beta1GcsSource" }, "bigquerySource": { "$ref": "GoogleCloudAiplatformV1beta1BigQuerySource", "description": "The BigQuery table of the unmanaged Dataset used to train this Model." }, "loggingSamplingStrategy": { "$ref": "GoogleCloudAiplatformV1beta1SamplingStrategy", "description": "Strategy to sample data from Training Dataset. If not set, we process the whole dataset." }, "dataset": { "description": "The resource name of the Dataset used to train this Model.", "type": "string" }, "dataFormat": { "description": "Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: \"tf-record\" The source file is a TFRecord file. \"csv\" The source file is a CSV file. \"jsonl\" The source file is a JSONL file.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingDataset", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesResponse": { "id": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesResponse", "type": "object", "description": "Response message for FeaturestoreService.BatchReadFeatureValues.", "properties": {} }, "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectTimeRangeAndFeature": { "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectTimeRangeAndFeature", "type": "object", "description": "Response message if the request uses the SelectTimeRangeAndFeature option.", "properties": { "impactedFeatureCount": { "type": "string", "format": "int64", "description": "The count of the features or columns impacted. This is the same as the feature count in the request." }, "onlineStorageModifiedEntityCount": { "description": "The count of modified entities in the online storage. Each entity ID corresponds to one entity. Within each entity, only the features specified in the request are deleted.", "format": "int64", "type": "string" }, "offlineStorageModifiedEntityRowCount": { "type": "string", "format": "int64", "description": "The count of modified entity rows in the offline storage. Each row corresponds to the combination of an entity ID and a timestamp. One entity ID can have multiple rows in the offline storage. Within each row, only the features specified in the request are deleted." } } }, "GoogleCloudAiplatformV1beta1ImportDataConfig": { "description": "Describes the location from where we import data into a Dataset, together with the labels that will be applied to the DataItems and the Annotations.", "properties": { "gcsSource": { "$ref": "GoogleCloudAiplatformV1beta1GcsSource", "description": "The Google Cloud Storage location for the input content." }, "dataItemLabels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Labels that will be applied to newly imported DataItems. If an identical DataItem as one being imported already exists in the Dataset, then these labels will be appended to these of the already existing one, and if labels with identical key is imported before, the old label value will be overwritten. If two DataItems are identical in the same import data operation, the labels will be combined and if key collision happens in this case, one of the values will be picked randomly. Two DataItems are considered identical if their content bytes are identical (e.g. image bytes or pdf bytes). These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file." }, "annotationLabels": { "description": "Labels that will be applied to newly imported Annotations. If two Annotations are identical, one of them will be deduped. Two Annotations are considered identical if their payload, payload_schema_uri and all of their labels are the same. These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file.", "type": "object", "additionalProperties": { "type": "string" } }, "importSchemaUri": { "description": "Required. Points to a YAML file stored on Google Cloud Storage describing the import format. Validation will be done against the schema. The schema is defined as an [OpenAPI 3.0.2 Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ImportDataConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecAgentConfigSourceAdkConfig": { "properties": { "jsonConfig": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Required. The value of the ADK config in JSON format." } }, "description": "Configuration for the Agent Development Kit (ADK).", "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecAgentConfigSourceAdkConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningTask": { "description": "A TrainingJob that tunes Hypererparameters of a custom code Model.", "properties": { "inputs": { "description": "The input parameters of this HyperparameterTuningTask.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec" }, "metadata": { "description": "The metadata information.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningTask", "type": "object" }, "GoogleCloudAiplatformV1beta1RagChunkPageSpan": { "properties": { "firstPage": { "type": "integer", "format": "int32", "description": "Page where chunk starts in the document. Inclusive. 1-indexed." }, "lastPage": { "format": "int32", "description": "Page where chunk ends in the document. Inclusive. 1-indexed.", "type": "integer" } }, "description": "Represents where the chunk starts and ends in the document.", "id": "GoogleCloudAiplatformV1beta1RagChunkPageSpan", "type": "object" }, "GoogleCloudAiplatformV1beta1FindNeighborsRequest": { "description": "The request message for MatchService.FindNeighbors.", "properties": { "deployedIndexId": { "description": "The ID of the DeployedIndex that will serve the request. This request is sent to a specific IndexEndpoint, as per the IndexEndpoint.network. That IndexEndpoint also has IndexEndpoint.deployed_indexes, and each such index has a DeployedIndex.id field. The value of the field below must equal one of the DeployedIndex.id fields of the IndexEndpoint that is being called for this request.", "type": "string" }, "returnFullDatapoint": { "description": "If set to true, the full datapoints (including all vector values and restricts) of the nearest neighbors are returned. Note that returning full datapoint will significantly increase the latency and cost of the query.", "type": "boolean" }, "queries": { "description": "The list of queries.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsRequestQuery" } } }, "id": "GoogleCloudAiplatformV1beta1FindNeighborsRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ExportModelOperationMetadataOutputInfo": { "description": "Further describes the output of the ExportModel. Supplements ExportModelRequest.OutputConfig.", "properties": { "artifactOutputUri": { "description": "Output only. If the Model artifact is being exported to Google Cloud Storage this is the full path of the directory created, into which the Model files are being written to.", "type": "string", "readOnly": true }, "imageOutputUri": { "readOnly": true, "type": "string", "description": "Output only. If the Model image is being exported to Google Container Registry or Artifact Registry this is the full path of the image created." } }, "id": "GoogleCloudAiplatformV1beta1ExportModelOperationMetadataOutputInfo", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotation": { "description": "Annotation details specific to image segmentation.", "properties": { "polygonAnnotation": { "$ref": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolygonAnnotation", "description": "Polygon annotation." }, "maskAnnotation": { "description": "Mask based segmentation annotation. Only one mask annotation can exist for one image.", "$ref": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationMaskAnnotation" }, "polylineAnnotation": { "description": "Polyline annotation.", "$ref": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolylineAnnotation" } }, "id": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotation", "type": "object" }, "GoogleCloudAiplatformV1beta1IntegratedGradientsAttribution": { "description": "An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365", "properties": { "smoothGradConfig": { "$ref": "GoogleCloudAiplatformV1beta1SmoothGradConfig", "description": "Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf" }, "blurBaselineConfig": { "description": "Config for IG with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383", "$ref": "GoogleCloudAiplatformV1beta1BlurBaselineConfig" }, "stepCount": { "type": "integer", "description": "Required. The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is within the desired error range. Valid range of its value is [1, 100], inclusively.", "format": "int32" } }, "id": "GoogleCloudAiplatformV1beta1IntegratedGradientsAttribution", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluateInstancesResponse": { "properties": { "fulfillmentResult": { "$ref": "GoogleCloudAiplatformV1beta1FulfillmentResult", "description": "Result for fulfillment metric." }, "toolParameterKeyMatchResults": { "description": "Results for tool parameter key match metric.", "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchResults" }, "trajectoryRecallResults": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryRecallResults", "description": "Results for trajectory recall metric." }, "exactMatchResults": { "description": "Auto metric evaluation results. Results for exact match metric.", "$ref": "GoogleCloudAiplatformV1beta1ExactMatchResults" }, "safetyResult": { "$ref": "GoogleCloudAiplatformV1beta1SafetyResult", "description": "Result for safety metric." }, "questionAnsweringHelpfulnessResult": { "description": "Result for question answering helpfulness metric.", "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessResult" }, "toolNameMatchResults": { "description": "Results for tool name match metric.", "$ref": "GoogleCloudAiplatformV1beta1ToolNameMatchResults" }, "trajectoryAnyOrderMatchResults": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchResults", "description": "Result for trajectory any order match metric." }, "summarizationHelpfulnessResult": { "$ref": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessResult", "description": "Result for summarization helpfulness metric." }, "summarizationQualityResult": { "$ref": "GoogleCloudAiplatformV1beta1SummarizationQualityResult", "description": "Summarization only metrics. Result for summarization quality metric." }, "cometResult": { "description": "Translation metrics. Result for Comet metric.", "$ref": "GoogleCloudAiplatformV1beta1CometResult" }, "metricResults": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MetricResult" }, "description": "Metric results for each instance. The order of the metric results is guaranteed to be the same as the order of the instances in the request." }, "summarizationVerbosityResult": { "$ref": "GoogleCloudAiplatformV1beta1SummarizationVerbosityResult", "description": "Result for summarization verbosity metric." }, "questionAnsweringQualityResult": { "description": "Question answering only metrics. Result for question answering quality metric.", "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityResult" }, "trajectoryPrecisionResults": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryPrecisionResults", "description": "Result for trajectory precision metric." }, "trajectorySingleToolUseResults": { "description": "Results for trajectory single tool use metric.", "$ref": "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseResults" }, "trajectoryExactMatchResults": { "description": "Result for trajectory exact match metric.", "$ref": "GoogleCloudAiplatformV1beta1TrajectoryExactMatchResults" }, "rougeResults": { "description": "Results for rouge metric.", "$ref": "GoogleCloudAiplatformV1beta1RougeResults" }, "toolCallValidResults": { "description": "Tool call metrics. Results for tool call valid metric.", "$ref": "GoogleCloudAiplatformV1beta1ToolCallValidResults" }, "groundednessResult": { "description": "Result for groundedness metric.", "$ref": "GoogleCloudAiplatformV1beta1GroundednessResult" }, "coherenceResult": { "description": "Result for coherence metric.", "$ref": "GoogleCloudAiplatformV1beta1CoherenceResult" }, "questionAnsweringCorrectnessResult": { "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessResult", "description": "Result for question answering correctness metric." }, "pointwiseMetricResult": { "description": "Generic metrics. Result for pointwise metric.", "$ref": "GoogleCloudAiplatformV1beta1PointwiseMetricResult" }, "questionAnsweringRelevanceResult": { "description": "Result for question answering relevance metric.", "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceResult" }, "pairwiseMetricResult": { "description": "Result for pairwise metric.", "$ref": "GoogleCloudAiplatformV1beta1PairwiseMetricResult" }, "rubricBasedInstructionFollowingResult": { "description": "Result for rubric based instruction following metric.", "$ref": "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingResult" }, "bleuResults": { "$ref": "GoogleCloudAiplatformV1beta1BleuResults", "description": "Results for bleu metric." }, "pairwiseQuestionAnsweringQualityResult": { "description": "Result for pairwise question answering quality metric.", "$ref": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityResult" }, "pairwiseSummarizationQualityResult": { "$ref": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityResult", "description": "Result for pairwise summarization quality metric." }, "fluencyResult": { "description": "LLM-based metric evaluation result. General text generation metrics, applicable to other categories. Result for fluency metric.", "$ref": "GoogleCloudAiplatformV1beta1FluencyResult" }, "toolParameterKvMatchResults": { "description": "Results for tool parameter key value match metric.", "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchResults" }, "trajectoryInOrderMatchResults": { "description": "Result for trajectory in order match metric.", "$ref": "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchResults" }, "metricxResult": { "$ref": "GoogleCloudAiplatformV1beta1MetricxResult", "description": "Result for Metricx metric." } }, "description": "Response message for EvaluationService.EvaluateInstances.", "id": "GoogleCloudAiplatformV1beta1EvaluateInstancesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchResults": { "properties": { "trajectoryInOrderMatchMetricValues": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchMetricValue" }, "readOnly": true, "description": "Output only. TrajectoryInOrderMatch metric values." } }, "description": "Results for TrajectoryInOrderMatch metric.", "id": "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchResults", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryExactMatchInput": { "description": "Instances and metric spec for TrajectoryExactMatch metric.", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryExactMatchSpec", "description": "Required. Spec for TrajectoryExactMatch metric." }, "instances": { "description": "Required. Repeated TrajectoryExactMatch instance.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryExactMatchInstance" } } }, "id": "GoogleCloudAiplatformV1beta1TrajectoryExactMatchInput", "type": "object" }, "GoogleCloudAiplatformV1beta1FindNeighborsResponseNearestNeighbors": { "description": "Nearest neighbors for one query.", "properties": { "neighbors": { "description": "All its neighbors.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsResponseNeighbor" } }, "id": { "description": "The ID of the query datapoint.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1FindNeighborsResponseNearestNeighbors", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigBruteForceConfig": { "properties": {}, "id": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigBruteForceConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1RagMetadata": { "description": "Metadata for RagFile provided by users.", "properties": { "name": { "description": "Identifier. Resource name of the RagMetadata. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}/ragMetadata/{rag_metadata}`", "type": "string" }, "userSpecifiedMetadata": { "$ref": "GoogleCloudAiplatformV1beta1UserSpecifiedMetadata", "description": "User provided metadata." } }, "id": "GoogleCloudAiplatformV1beta1RagMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1IndexEndpoint": { "id": "GoogleCloudAiplatformV1beta1IndexEndpoint", "type": "object", "properties": { "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Immutable. Customer-managed encryption key spec for an IndexEndpoint. If set, this IndexEndpoint and all sub-resources of this IndexEndpoint will be secured by this key." }, "publicEndpointDomainName": { "type": "string", "readOnly": true, "description": "Output only. If public_endpoint_enabled is true, this field will be populated with the domain name to use for this index endpoint." }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "description": { "description": "The description of the IndexEndpoint.", "type": "string" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this IndexEndpoint was created." }, "deployedIndexes": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DeployedIndex" }, "readOnly": true, "description": "Output only. The indexes deployed in this endpoint." }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize your IndexEndpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." }, "privateServiceConnectConfig": { "description": "Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive.", "$ref": "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig" }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this IndexEndpoint was last updated. This timestamp is not updated when the endpoint's DeployedIndexes are updated, e.g. due to updates of the original Indexes they are the deployments of.", "readOnly": true, "type": "string" }, "displayName": { "description": "Required. The display name of the IndexEndpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "enablePrivateServiceConnect": { "description": "Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.", "deprecated": true, "type": "boolean" }, "network": { "description": "Optional. The full name of the Google Compute Engine [network](https://cloud.google.com/compute/docs/networks-and-firewalls#networks) to which the IndexEndpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. network and private_service_connect_config are mutually exclusive. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in '12345', and {network} is network name.", "type": "string" }, "satisfiesPzs": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "publicEndpointEnabled": { "description": "Optional. If true, the deployed index will be accessible through public endpoint.", "type": "boolean" }, "name": { "type": "string", "readOnly": true, "description": "Output only. The resource name of the IndexEndpoint." } }, "description": "Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes." }, "GoogleCloudAiplatformV1beta1VertexAISearch": { "id": "GoogleCloudAiplatformV1beta1VertexAISearch", "type": "object", "properties": { "dataStoreSpecs": { "description": "Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1VertexAISearchDataStoreSpec" } }, "engine": { "description": "Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`", "type": "string" }, "maxResults": { "description": "Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.", "format": "int32", "type": "integer" }, "datastore": { "description": "Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`", "type": "string" }, "filter": { "description": "Optional. Filter strings to be passed to the search API.", "type": "string" } }, "description": "Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder" }, "GoogleCloudAiplatformV1beta1Probe": { "properties": { "exec": { "description": "ExecAction probes the health of a container by executing a command.", "$ref": "GoogleCloudAiplatformV1beta1ProbeExecAction" }, "httpGet": { "description": "HttpGetAction probes the health of a container by sending an HTTP GET request.", "$ref": "GoogleCloudAiplatformV1beta1ProbeHttpGetAction" }, "tcpSocket": { "description": "TcpSocketAction probes the health of a container by opening a TCP socket connection.", "$ref": "GoogleCloudAiplatformV1beta1ProbeTcpSocketAction" }, "timeoutSeconds": { "description": "Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to period_seconds. Maps to Kubernetes probe argument 'timeoutSeconds'.", "format": "int32", "type": "integer" }, "successThreshold": { "type": "integer", "description": "Number of consecutive successes before the probe is considered successful. Defaults to 1. Minimum value is 1. Maps to Kubernetes probe argument 'successThreshold'.", "format": "int32" }, "initialDelaySeconds": { "format": "int32", "description": "Number of seconds to wait before starting the probe. Defaults to 0. Minimum value is 0. Maps to Kubernetes probe argument 'initialDelaySeconds'.", "type": "integer" }, "failureThreshold": { "format": "int32", "description": "Number of consecutive failures before the probe is considered failed. Defaults to 3. Minimum value is 1. Maps to Kubernetes probe argument 'failureThreshold'.", "type": "integer" }, "grpc": { "description": "GrpcAction probes the health of a container by sending a gRPC request.", "$ref": "GoogleCloudAiplatformV1beta1ProbeGrpcAction" }, "periodSeconds": { "type": "integer", "format": "int32", "description": "How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeout_seconds. Maps to Kubernetes probe argument 'periodSeconds'." } }, "description": "Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.", "id": "GoogleCloudAiplatformV1beta1Probe", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchInput": { "properties": { "metricSpec": { "description": "Required. Spec for TrajectoryInOrderMatch metric.", "$ref": "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchSpec" }, "instances": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchInstance" }, "description": "Required. Repeated TrajectoryInOrderMatch instance." } }, "description": "Instances and metric spec for TrajectoryInOrderMatch metric.", "id": "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchInput", "type": "object" }, "GoogleCloudAiplatformV1beta1Extension": { "id": "GoogleCloudAiplatformV1beta1Extension", "type": "object", "properties": { "toolUseExamples": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ToolUseExample" }, "description": "Optional. Examples to illustrate the usage of the extension as a tool." }, "displayName": { "description": "Required. The display name of the Extension. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "name": { "description": "Identifier. The resource name of the Extension.", "type": "string" }, "extensionOperations": { "description": "Output only. Supported operations.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ExtensionOperation" }, "readOnly": true }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this Extension was most recently updated.", "format": "google-datetime" }, "runtimeConfig": { "$ref": "GoogleCloudAiplatformV1beta1RuntimeConfig", "description": "Optional. Runtime config controlling the runtime behavior of this Extension." }, "manifest": { "$ref": "GoogleCloudAiplatformV1beta1ExtensionManifest", "description": "Required. Manifest of the Extension." }, "privateServiceConnectConfig": { "$ref": "GoogleCloudAiplatformV1beta1ExtensionPrivateServiceConnectConfig", "description": "Optional. The PrivateServiceConnect config for the extension. If specified, the service endpoints associated with the Extension should be [registered with private network access in the provided Service Directory](https://cloud.google.com/service-directory/docs/configuring-private-network-access). If the service contains more than one endpoint with a network, the service will arbitrarilty choose one of the endpoints to use for extension execution." }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when this Extension was created.", "readOnly": true, "type": "string" }, "description": { "description": "Optional. The description of the Extension.", "type": "string" }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" } }, "description": "Extensions are tools for large language models to access external data, run computations, etc." }, "GoogleCloudAiplatformV1beta1Part": { "properties": { "codeExecutionResult": { "description": "Optional. The result of executing the ExecutableCode.", "$ref": "GoogleCloudAiplatformV1beta1CodeExecutionResult" }, "thoughtSignature": { "format": "byte", "description": "Optional. An opaque signature for the thought so it can be reused in subsequent requests.", "type": "string" }, "fileData": { "description": "Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.", "$ref": "GoogleCloudAiplatformV1beta1FileData" }, "functionCall": { "description": "Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.", "$ref": "GoogleCloudAiplatformV1beta1FunctionCall" }, "functionResponse": { "$ref": "GoogleCloudAiplatformV1beta1FunctionResponse", "description": "Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted." }, "inlineData": { "$ref": "GoogleCloudAiplatformV1beta1Blob", "description": "Optional. The inline data content of the part. This can be used to include images, audio, or video in a request." }, "executableCode": { "$ref": "GoogleCloudAiplatformV1beta1ExecutableCode", "description": "Optional. Code generated by the model that is intended to be executed." }, "videoMetadata": { "description": "Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.", "$ref": "GoogleCloudAiplatformV1beta1VideoMetadata" }, "text": { "description": "Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.", "type": "string" }, "thought": { "description": "Optional. Indicates whether the `part` represents the model's thought process or reasoning.", "type": "boolean" }, "mediaResolution": { "$ref": "GoogleCloudAiplatformV1beta1PartMediaResolution", "description": "per part media resolution. Media resolution for the input media." } }, "description": "A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.", "id": "GoogleCloudAiplatformV1beta1Part", "type": "object" }, "GoogleCloudAiplatformV1beta1PscInterfaceConfig": { "description": "Configuration for PSC-I.", "properties": { "networkAttachment": { "description": "Optional. The name of the Compute Engine [network attachment](https://cloud.google.com/vpc/docs/about-network-attachments) to attach to the resource within the region and user project. To specify this field, you must have already [created a network attachment] (https://cloud.google.com/vpc/docs/create-manage-network-attachments#create-network-attachments). This field is only used for resources using PSC-I.", "type": "string" }, "dnsPeeringConfigs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DnsPeeringConfig" }, "description": "Optional. DNS peering configurations. When specified, Vertex AI will attempt to configure DNS peering zones in the tenant project VPC to resolve the specified domains using the target network's Cloud DNS. The user must grant the dns.peer role to the Vertex AI Service Agent on the target project." } }, "id": "GoogleCloudAiplatformV1beta1PscInterfaceConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1MergeVersionAliasesRequest": { "id": "GoogleCloudAiplatformV1beta1MergeVersionAliasesRequest", "type": "object", "description": "Request message for ModelService.MergeVersionAliases.", "properties": { "versionAliases": { "type": "array", "items": { "type": "string" }, "description": "Required. The set of version aliases to merge. The alias should be at most 128 characters, and match `a-z{0,126}[a-z-0-9]`. Add the `-` prefix to an alias means removing that alias from the version. `-` is NOT counted in the 128 characters. Example: `-golden` means removing the `golden` alias from the version. There is NO ordering in aliases, which means 1) The aliases returned from GetModel API might not have the exactly same order from this MergeVersionAliases API. 2) Adding and deleting the same alias in the request is not recommended, and the 2 operations will be cancelled out." } } }, "GoogleCloudAiplatformV1beta1TrajectoryPrecisionInstance": { "id": "GoogleCloudAiplatformV1beta1TrajectoryPrecisionInstance", "type": "object", "properties": { "referenceTrajectory": { "$ref": "GoogleCloudAiplatformV1beta1Trajectory", "description": "Required. Spec for reference tool call trajectory." }, "predictedTrajectory": { "$ref": "GoogleCloudAiplatformV1beta1Trajectory", "description": "Required. Spec for predicted tool call trajectory." } }, "description": "Spec for TrajectoryPrecision instance." }, "GoogleCloudAiplatformV1beta1DeleteOperationMetadata": { "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Details of operations that perform deletes of any entities.", "id": "GoogleCloudAiplatformV1beta1DeleteOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1RubricContentProperty": { "description": "Defines criteria based on a specific property.", "properties": { "description": { "description": "Description of the property being evaluated. Example: \"The model's response is grammatically correct.\"", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1RubricContentProperty", "type": "object" }, "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityViewData": { "description": "Container to hold value(s), successive in time, for one Feature from the request.", "properties": { "value": { "description": "Feature value if a single value is requested.", "$ref": "GoogleCloudAiplatformV1beta1FeatureValue" }, "values": { "description": "Feature values list if values, successive in time, are requested. If the requested number of values is greater than the number of existing Feature values, nonexistent values are omitted instead of being returned as empty.", "$ref": "GoogleCloudAiplatformV1beta1FeatureValueList" } }, "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityViewData", "type": "object" }, "GoogleCloudAiplatformV1beta1ListIndexEndpointsResponse": { "properties": { "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListIndexEndpointsRequest.page_token to obtain that page.", "type": "string" }, "indexEndpoints": { "description": "List of IndexEndpoints in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1IndexEndpoint" } } }, "description": "Response message for IndexEndpointService.ListIndexEndpoints.", "id": "GoogleCloudAiplatformV1beta1ListIndexEndpointsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1BigQueryRequestSet": { "id": "GoogleCloudAiplatformV1beta1BigQueryRequestSet", "type": "object", "properties": { "promptColumn": { "description": "Optional. The name of the column that contains the requests to evaluate. This will be in evaluation_item.EvalPrompt format.", "type": "string" }, "rubricsColumn": { "description": "Optional. The name of the column that contains the rubrics. This is in evaluation_rubric.RubricGroup format.", "type": "string" }, "candidateResponseColumns": { "description": "Optional. Map of candidate name to candidate response column name. The column will be in evaluation_item.CandidateResponse format.", "type": "object", "additionalProperties": { "type": "string" } }, "uri": { "description": "Required. The URI of a BigQuery table. e.g. bq://projectId.bqDatasetId.bqTableId", "type": "string" }, "samplingConfig": { "$ref": "GoogleCloudAiplatformV1beta1BigQueryRequestSetSamplingConfig", "description": "Optional. The sampling config for the bigquery resource." } }, "description": "The request set for the evaluation run." }, "GoogleCloudAiplatformV1beta1RestoreDatasetVersionOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1RestoreDatasetVersionOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Runtime operation information for DatasetService.RestoreDatasetVersion." }, "GoogleCloudAiplatformV1beta1FeatureGroupBigQuery": { "properties": { "bigQuerySource": { "$ref": "GoogleCloudAiplatformV1beta1BigQuerySource", "description": "Required. Immutable. The BigQuery source URI that points to either a BigQuery Table or View." }, "timeSeries": { "description": "Optional. If the source is a time-series source, this can be set to control how downstream sources (ex: FeatureView ) will treat time-series sources. If not set, will treat the source as a time-series source with `feature_timestamp` as timestamp column and no scan boundary.", "$ref": "GoogleCloudAiplatformV1beta1FeatureGroupBigQueryTimeSeries" }, "dense": { "description": "Optional. If set, all feature values will be fetched from a single row per unique entityId including nulls. If not set, will collapse all rows for each unique entityId into a singe row with any non-null values if present, if no non-null values are present will sync null. ex: If source has schema `(entity_id, feature_timestamp, f0, f1)` and the following rows: `(e1, 2020-01-01T10:00:00.123Z, 10, 15)` `(e1, 2020-02-01T10:00:00.123Z, 20, null)` If dense is set, `(e1, 20, null)` is synced to online stores. If dense is not set, `(e1, 20, 15)` is synced to online stores.", "type": "boolean" }, "entityIdColumns": { "description": "Optional. Columns to construct entity_id / row keys. If not provided defaults to `entity_id`.", "type": "array", "items": { "type": "string" } }, "staticDataSource": { "description": "Optional. Set if the data source is not a time-series.", "type": "boolean" } }, "description": "Input source type for BigQuery Tables and Views.", "id": "GoogleCloudAiplatformV1beta1FeatureGroupBigQuery", "type": "object" }, "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigBigQuerySourceConfig": { "id": "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigBigQuerySourceConfig", "type": "object", "properties": { "datapointFieldMapping": { "description": "Required. Mapping of datapoint fields to BigQuery column names.", "$ref": "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMapping" }, "tablePath": { "description": "Required. The path to the BigQuery table containing the index data, in the format of `bq://..`.", "type": "string" } }, "description": "Configuration for importing data from a BigQuery table." }, "GoogleCloudAiplatformV1beta1ExactMatchInstance": { "id": "GoogleCloudAiplatformV1beta1ExactMatchInstance", "type": "object", "description": "Spec for exact match instance.", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "reference": { "description": "Required. Ground truth used to compare against the prediction.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ExplanationSpec": { "description": "Specification of Model explanation.", "properties": { "parameters": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationParameters", "description": "Required. Parameters that configure explaining of the Model's predictions." }, "metadata": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadata", "description": "Optional. Metadata describing the Model's input and output for explanation." } }, "id": "GoogleCloudAiplatformV1beta1ExplanationSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ListHyperparameterTuningJobsResponse": { "id": "GoogleCloudAiplatformV1beta1ListHyperparameterTuningJobsResponse", "type": "object", "properties": { "hyperparameterTuningJobs": { "description": "List of HyperparameterTuningJobs in the requested page. HyperparameterTuningJob.trials of the jobs will be not be returned.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1HyperparameterTuningJob" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListHyperparameterTuningJobsRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for JobService.ListHyperparameterTuningJobs" }, "GoogleCloudAiplatformV1beta1ResourcesConsumed": { "description": "Statistics information about resource consumption.", "properties": { "replicaHours": { "description": "Output only. The number of replica hours used. Note that many replicas may run in parallel, and additionally any given work may be queued for some time. Therefore this value is not strictly related to wall time.", "format": "double", "type": "number", "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1ResourcesConsumed", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureNoiseSigma": { "description": "Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.", "properties": { "noiseSigma": { "description": "Noise sigma per feature. No noise is added to features that are not set.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureNoiseSigmaNoiseSigmaForFeature" } } }, "id": "GoogleCloudAiplatformV1beta1FeatureNoiseSigma", "type": "object" }, "GoogleCloudAiplatformV1beta1BoolArray": { "properties": { "values": { "description": "A list of bool values.", "type": "array", "items": { "type": "boolean" } } }, "description": "A list of boolean values.", "id": "GoogleCloudAiplatformV1beta1BoolArray", "type": "object" }, "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInstance": { "properties": { "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" }, "context": { "description": "Required. Text to answer the question.", "type": "string" }, "prediction": { "description": "Required. Output of the candidate model.", "type": "string" }, "baselinePrediction": { "description": "Required. Output of the baseline model.", "type": "string" }, "instruction": { "description": "Required. Question Answering prompt for LLM.", "type": "string" } }, "description": "Spec for pairwise question answering quality instance.", "id": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1ReadTensorboardSizeResponse": { "properties": { "storageSizeByte": { "description": "Payload storage size for the TensorBoard", "format": "int64", "type": "string" } }, "description": "Response message for TensorboardService.ReadTensorboardSize.", "id": "GoogleCloudAiplatformV1beta1ReadTensorboardSizeResponse", "type": "object" }, "CloudAiLargeModelsVisionPromptInputs": { "id": "CloudAiLargeModelsVisionPromptInputs", "type": "object", "description": "\"Direct\" prompting for Experimental Video Generation. These will be sent directly to the LDM without being rewritten.", "properties": { "transcript": { "description": "Spoken transcript of the video for characters.", "type": "string" }, "promptChunks": { "description": "2s, 256 tokens per chunk, 4 total chunks. Required.", "type": "array", "items": { "type": "string" } }, "negativeAudioPrompt": { "description": "Negative description of audio content in the video.", "type": "string" }, "negativePrompt": { "description": "Single negative prompt for what not to generate.", "type": "string" }, "audioPrompt": { "description": "Description of audio content in the video, without speech.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ToolComputerUse": { "id": "GoogleCloudAiplatformV1beta1ToolComputerUse", "type": "object", "properties": { "environment": { "type": "string", "enumDescriptions": [ "Defaults to browser.", "Operates in a web browser." ], "description": "Required. The environment being operated.", "enum": [ "ENVIRONMENT_UNSPECIFIED", "ENVIRONMENT_BROWSER" ] }, "excludedPredefinedFunctions": { "type": "array", "items": { "type": "string" }, "description": "Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions." } }, "description": "Tool to support computer use." }, "GoogleCloudAiplatformV1beta1DatasetStats": { "properties": { "totalBillableCharacterCount": { "description": "Output only. Number of billable characters in the tuning dataset.", "format": "int64", "type": "string", "readOnly": true }, "tuningDatasetExampleCount": { "type": "string", "readOnly": true, "description": "Output only. Number of examples in the tuning dataset.", "format": "int64" }, "tuningStepCount": { "format": "int64", "description": "Output only. Number of tuning steps for this Tuning Job.", "readOnly": true, "type": "string" }, "userInputTokenDistribution": { "description": "Output only. Dataset distributions for the user input tokens.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1DatasetDistribution" }, "userMessagePerExampleDistribution": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1DatasetDistribution", "description": "Output only. Dataset distributions for the messages per example." }, "userDatasetExamples": { "description": "Output only. Sample user messages in the training dataset uri.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "totalTuningCharacterCount": { "format": "int64", "description": "Output only. Number of tuning characters in the tuning dataset.", "readOnly": true, "type": "string" }, "userOutputTokenDistribution": { "description": "Output only. Dataset distributions for the user output tokens.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1DatasetDistribution" }, "droppedExampleIndices": { "description": "Output only. A partial sample of the indices (starting from 1) of the dropped examples.", "type": "array", "items": { "format": "int64", "type": "string" }, "readOnly": true }, "droppedExampleReasons": { "description": "Output only. For each index in `dropped_example_indices`, the user-facing reason why the example was dropped.", "readOnly": true, "type": "array", "items": { "type": "string" } } }, "description": "Statistics computed over a tuning dataset.", "id": "GoogleCloudAiplatformV1beta1DatasetStats", "type": "object" }, "GoogleCloudAiplatformV1beta1PurgeExecutionsRequest": { "properties": { "filter": { "description": "Required. A required filter matching the Executions to be purged. E.g., `update_time \u003c= 2020-11-19T11:30:00-04:00`.", "type": "string" }, "force": { "description": "Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Execution names that would be deleted.", "type": "boolean" } }, "description": "Request message for MetadataService.PurgeExecutions.", "id": "GoogleCloudAiplatformV1beta1PurgeExecutionsRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluateInstancesRequest": { "id": "GoogleCloudAiplatformV1beta1EvaluateInstancesRequest", "type": "object", "properties": { "summarizationVerbosityInput": { "$ref": "GoogleCloudAiplatformV1beta1SummarizationVerbosityInput", "description": "Input for summarization verbosity metric." }, "fulfillmentInput": { "$ref": "GoogleCloudAiplatformV1beta1FulfillmentInput", "description": "Input for fulfillment metric." }, "pointwiseMetricInput": { "description": "Input for pointwise metric.", "$ref": "GoogleCloudAiplatformV1beta1PointwiseMetricInput" }, "fluencyInput": { "description": "LLM-based metric instance. General text generation metrics, applicable to other categories. Input for fluency metric.", "$ref": "GoogleCloudAiplatformV1beta1FluencyInput" }, "trajectorySingleToolUseInput": { "description": "Input for trajectory single tool use metric.", "$ref": "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseInput" }, "summarizationHelpfulnessInput": { "description": "Input for summarization helpfulness metric.", "$ref": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInput" }, "questionAnsweringRelevanceInput": { "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInput", "description": "Input for question answering relevance metric." }, "questionAnsweringQualityInput": { "description": "Input for question answering quality metric.", "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInput" }, "toolParameterKeyMatchInput": { "description": "Input for tool parameter key match metric.", "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInput" }, "coherenceInput": { "$ref": "GoogleCloudAiplatformV1beta1CoherenceInput", "description": "Input for coherence metric." }, "toolParameterKvMatchInput": { "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInput", "description": "Input for tool parameter key value match metric." }, "pairwiseMetricInput": { "description": "Input for pairwise metric.", "$ref": "GoogleCloudAiplatformV1beta1PairwiseMetricInput" }, "trajectoryPrecisionInput": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryPrecisionInput", "description": "Input for trajectory precision metric." }, "exactMatchInput": { "$ref": "GoogleCloudAiplatformV1beta1ExactMatchInput", "description": "Auto metric instances. Instances and metric spec for exact match metric." }, "rougeInput": { "description": "Instances and metric spec for rouge metric.", "$ref": "GoogleCloudAiplatformV1beta1RougeInput" }, "questionAnsweringCorrectnessInput": { "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInput", "description": "Input for question answering correctness metric." }, "trajectoryExactMatchInput": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryExactMatchInput", "description": "Input for trajectory exact match metric." }, "summarizationQualityInput": { "description": "Input for summarization quality metric.", "$ref": "GoogleCloudAiplatformV1beta1SummarizationQualityInput" }, "pairwiseSummarizationQualityInput": { "description": "Input for pairwise summarization quality metric.", "$ref": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInput" }, "bleuInput": { "description": "Instances and metric spec for bleu metric.", "$ref": "GoogleCloudAiplatformV1beta1BleuInput" }, "pairwiseQuestionAnsweringQualityInput": { "$ref": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInput", "description": "Input for pairwise question answering quality metric." }, "metricSources": { "description": "Optional. The metrics (either inline or registered) used for evaluation. Currently, we only support evaluating a single metric. If multiple metrics are provided, only the first one will be evaluated.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MetricSource" } }, "questionAnsweringHelpfulnessInput": { "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInput", "description": "Input for question answering helpfulness metric." }, "toolCallValidInput": { "description": "Tool call metric instances. Input for tool call valid metric.", "$ref": "GoogleCloudAiplatformV1beta1ToolCallValidInput" }, "trajectoryAnyOrderMatchInput": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchInput", "description": "Input for trajectory match any order metric." }, "toolNameMatchInput": { "description": "Input for tool name match metric.", "$ref": "GoogleCloudAiplatformV1beta1ToolNameMatchInput" }, "trajectoryRecallInput": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryRecallInput", "description": "Input for trajectory recall metric." }, "instance": { "description": "The instance to be evaluated.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstance" }, "metricxInput": { "$ref": "GoogleCloudAiplatformV1beta1MetricxInput", "description": "Input for Metricx metric." }, "groundednessInput": { "description": "Input for groundedness metric.", "$ref": "GoogleCloudAiplatformV1beta1GroundednessInput" }, "rubricBasedInstructionFollowingInput": { "$ref": "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingInput", "description": "Rubric Based Instruction Following metric." }, "metrics": { "description": "The metrics used for evaluation. Currently, we only support evaluating a single metric. If multiple metrics are provided, only the first one will be evaluated.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Metric" } }, "trajectoryInOrderMatchInput": { "description": "Input for trajectory in order match metric.", "$ref": "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchInput" }, "location": { "description": "Required. The resource name of the Location to evaluate the instances. Format: `projects/{project}/locations/{location}`", "type": "string" }, "cometInput": { "$ref": "GoogleCloudAiplatformV1beta1CometInput", "description": "Translation metrics. Input for Comet metric." }, "safetyInput": { "description": "Input for safety metric.", "$ref": "GoogleCloudAiplatformV1beta1SafetyInput" }, "autoraterConfig": { "description": "Optional. Autorater config used for evaluation.", "$ref": "GoogleCloudAiplatformV1beta1AutoraterConfig" } }, "description": "Request message for EvaluationService.EvaluateInstances." }, "GoogleCloudAiplatformV1beta1NearestNeighborQueryEmbedding": { "id": "GoogleCloudAiplatformV1beta1NearestNeighborQueryEmbedding", "type": "object", "description": "The embedding vector.", "properties": { "value": { "description": "Optional. Individual value in the embedding.", "type": "array", "items": { "type": "number", "format": "float" } } } }, "GoogleCloudAiplatformV1beta1EmbedContentRequestEmbedContentConfig": { "properties": { "taskType": { "enum": [ "UNSPECIFIED", "RETRIEVAL_QUERY", "RETRIEVAL_DOCUMENT", "SEMANTIC_SIMILARITY", "CLASSIFICATION", "CLUSTERING", "QUESTION_ANSWERING", "FACT_VERIFICATION", "CODE_RETRIEVAL_QUERY" ], "description": "Optional. The task type of the embedding. Only applicable to text-only embedding models.", "type": "string", "enumDescriptions": [ "Unset value, which will default to one of the other enum values.", "Specifies the given text is a query in a search/retrieval setting.", "Specifies the given text is a document from the corpus being searched.", "Specifies the given text will be used for STS.", "Specifies that the given text will be classified.", "Specifies that the embeddings will be used for clustering.", "Specifies that the embeddings will be used for question answering.", "Specifies that the embeddings will be used for fact verification.", "Specifies that the embeddings will be used for code retrieval." ] }, "title": { "description": "Optional. The title for the text. Only applicable to text-only embedding models.", "type": "string" }, "autoTruncate": { "description": "Optional. Whether to silently truncate the input content if it's longer than the maximum sequence length. Only applicable to text-only embedding models.", "type": "boolean" }, "documentOcr": { "description": "Optional. Whether to enable OCR for document content.", "type": "boolean" }, "audioTrackExtraction": { "description": "Optional. Whether to extract audio from video content.", "type": "boolean" }, "outputDimensionality": { "type": "integer", "description": "Optional. Reduced dimension for the output embedding. If set, excessive values in the output embedding are truncated from the end.", "format": "int32" } }, "description": "Configurations for the EmbedContent API.", "id": "GoogleCloudAiplatformV1beta1EmbedContentRequestEmbedContentConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageClassificationPredictionInstance": { "description": "Prediction input format for Image Classification.", "properties": { "content": { "description": "The image bytes or Cloud Storage URI to make the prediction on.", "type": "string" }, "mimeType": { "description": "The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageClassificationPredictionInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchInstance": { "id": "GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchInstance", "type": "object", "properties": { "referenceTrajectory": { "description": "Required. Spec for reference tool call trajectory.", "$ref": "GoogleCloudAiplatformV1beta1Trajectory" }, "predictedTrajectory": { "description": "Required. Spec for predicted tool call trajectory.", "$ref": "GoogleCloudAiplatformV1beta1Trajectory" } }, "description": "Spec for TrajectoryInOrderMatch instance." }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecAppBuilderData": { "properties": { "codeRepositoryState": { "description": "Serialized state of the code repository. This string will typically contain a JSON representation of the UI's CodeRepositoryService state (files, folders, content, and any metadata). The UI is responsible for serialization and deserialization.", "type": "string" }, "linkedResources": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecAppBuilderDataLinkedResource" }, "description": "Linked resources attached to the application by the user." }, "framework": { "description": "Optional. Framework used to build the application.", "enum": [ "FRAMEWORK_UNSPECIFIED", "REACT", "ANGULAR" ], "type": "string", "enumDescriptions": [ "Unspecified framework.", "React framework.", "Angular framework." ] } }, "description": "Defines data for an application builder.", "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecAppBuilderData", "type": "object" }, "GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList": { "properties": { "artifacts": { "description": "Output only. A list of artifact metadata.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Artifact" }, "readOnly": true } }, "description": "A list of artifact metadata.", "id": "GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricBasedMetricSpec": { "id": "GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricBasedMetricSpec", "type": "object", "properties": { "metricPromptTemplate": { "description": "Optional. Template for the prompt used by the judge model to evaluate against rubrics.", "type": "string" }, "judgeAutoraterConfig": { "description": "Optional. Optional configuration for the judge LLM (Autorater). The definition of AutoraterConfig needs to be provided.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigAutoraterConfig" }, "inlineRubrics": { "description": "Use rubrics provided directly in the spec.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricBasedMetricSpecRepeatedRubrics" }, "rubricGenerationSpec": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricGenerationSpec", "description": "Dynamically generate rubrics for evaluation using this specification." }, "rubricGroupKey": { "description": "Use a pre-defined group of rubrics associated with the input content. This refers to a key in the `rubric_groups` map of `RubricEnhancedContents`.", "type": "string" } }, "description": "Specification for a metric that is based on rubrics." }, "GoogleCloudAiplatformV1beta1DatasetDistribution": { "properties": { "mean": { "type": "number", "readOnly": true, "description": "Output only. The arithmetic mean of the values in the population.", "format": "double" }, "median": { "readOnly": true, "type": "number", "format": "double", "description": "Output only. The median of the values in the population." }, "p5": { "description": "Output only. The 5th percentile of the values in the population.", "format": "double", "type": "number", "readOnly": true }, "sum": { "format": "double", "description": "Output only. Sum of a given population of values.", "readOnly": true, "type": "number" }, "max": { "description": "Output only. The maximum of the population values.", "format": "double", "type": "number", "readOnly": true }, "p95": { "readOnly": true, "type": "number", "format": "double", "description": "Output only. The 95th percentile of the values in the population." }, "buckets": { "description": "Output only. Defines the histogram bucket.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DatasetDistributionDistributionBucket" } }, "min": { "format": "double", "description": "Output only. The minimum of the population values.", "readOnly": true, "type": "number" } }, "description": "Distribution computed over a tuning dataset.", "id": "GoogleCloudAiplatformV1beta1DatasetDistribution", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaVisualInspectionClassificationLabelSavedQueryMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaVisualInspectionClassificationLabelSavedQueryMetadata", "type": "object", "properties": { "multiLabel": { "description": "Whether or not the classification label is multi_label.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestVertexSessionSource": { "id": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestVertexSessionSource", "type": "object", "properties": { "session": { "description": "Required. The resource name of the Session to generate memories for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "type": "string" }, "endTime": { "type": "string", "format": "google-datetime", "description": "Optional. End time (exclusive) of the time range. If not set, the end time is unbounded." }, "startTime": { "type": "string", "description": "Optional. Time range to define which session events should be used to generate memories. Start time (inclusive) of the time range. If not set, the start time is unbounded.", "format": "google-datetime" } }, "description": "Defines an Agent Engine Session from which to generate the memories. If `scope` is not provided, the scope will be extracted from the Session (i.e. {\"user_id\": sesison.user_id})." }, "GoogleCloudAiplatformV1beta1TrajectoryExactMatchResults": { "id": "GoogleCloudAiplatformV1beta1TrajectoryExactMatchResults", "type": "object", "properties": { "trajectoryExactMatchMetricValues": { "description": "Output only. TrajectoryExactMatch metric values.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryExactMatchMetricValue" }, "readOnly": true } }, "description": "Results for TrajectoryExactMatch metric." }, "GoogleCloudAiplatformV1beta1ToolNameMatchResults": { "id": "GoogleCloudAiplatformV1beta1ToolNameMatchResults", "type": "object", "description": "Results for tool name match metric.", "properties": { "toolNameMatchMetricValues": { "description": "Output only. Tool name match metric values.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ToolNameMatchMetricValue" }, "readOnly": true } } }, "GoogleCloudAiplatformV1beta1Claim": { "description": "Claim that is extracted from the input text and facts that support it.", "properties": { "startIndex": { "format": "int32", "description": "Index in the input text where the claim starts (inclusive).", "type": "integer" }, "factIndexes": { "type": "array", "items": { "type": "integer", "format": "int32" }, "description": "Indexes of the facts supporting this claim." }, "score": { "type": "number", "format": "float", "description": "Confidence score of this corroboration." }, "endIndex": { "format": "int32", "description": "Index in the input text where the claim ends (exclusive).", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1Claim", "type": "object" }, "GoogleCloudAiplatformV1beta1RagManagedDbConfigServerless": { "id": "GoogleCloudAiplatformV1beta1RagManagedDbConfigServerless", "type": "object", "description": "Message to configure the serverless mode offered by RAG Engine.", "properties": {} }, "GoogleCloudAiplatformV1beta1PythonPackageSpec": { "description": "The spec of a Python packaged code.", "properties": { "packageUris": { "description": "Required. The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.", "type": "array", "items": { "type": "string" } }, "executorImageUri": { "description": "Required. The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of [pre-built containers for training](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). You must use an image from this list.", "type": "string" }, "env": { "description": "Environment variables to be passed to the python module. Maximum limit is 100.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EnvVar" } }, "args": { "description": "Command line arguments to be passed to the Python task.", "type": "array", "items": { "type": "string" } }, "pythonModule": { "description": "Required. The Python module name to run after installing the packages.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1PythonPackageSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema": { "description": "Schema field definition.", "properties": { "dataType": { "description": "Supported data types are: `float` `integer` `boolean` `string` `categorical`", "type": "string" }, "name": { "description": "Field name.", "type": "string" }, "repeated": { "description": "Describes if the schema field is an array of given data type.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchInput": { "description": "Instances and metric spec for TrajectoryAnyOrderMatch metric.", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchSpec", "description": "Required. Spec for TrajectoryAnyOrderMatch metric." }, "instances": { "description": "Required. Repeated TrajectoryAnyOrderMatch instance.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchInstance" } } }, "id": "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchInput", "type": "object" }, "GoogleCloudAiplatformV1beta1FindNeighborsResponseNeighbor": { "description": "A neighbor of the query vector.", "properties": { "distance": { "description": "The distance between the neighbor and the dense embedding query.", "format": "double", "type": "number" }, "datapoint": { "$ref": "GoogleCloudAiplatformV1beta1IndexDatapoint", "description": "The datapoint of the neighbor. Note that full datapoints are returned only when \"return_full_datapoint\" is set to true. Otherwise, only the \"datapoint_id\" and \"crowding_tag\" fields are populated." }, "sparseDistance": { "format": "double", "description": "The distance between the neighbor and the query sparse_embedding.", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1FindNeighborsResponseNeighbor", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentData": { "type": "object", "deprecated": true, "id": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentData", "properties": { "toolsText": { "type": "string", "deprecated": true, "description": "A JSON string containing a list of tools available to an agent with info such as name, description, parameters and required parameters." }, "tools": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataTools", "description": "List of tools." }, "turns": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataConversationTurn" }, "description": "Optional. The chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -\u003e Agent Response)." }, "events": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataEvents", "description": "A list of events." }, "agentConfig": { "description": "Optional. Deprecated: Use `agent_eval_data` instead. Agent configuration.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentConfig" }, "agents": { "description": "Optional. The static Agent Configuration. This map defines the graph structure of the agent system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent (tools, instructions, sub-agents).", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentConfig" } }, "developerInstruction": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData", "description": "Optional. Deprecated: Use `agents.developer_instruction` or `turns.events.active_instruction` instead. A field containing instructions from the developer for the agent." } }, "description": "Deprecated: Use `agent_eval_data` instead. Contains data specific to agent evaluations." }, "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMapping": { "description": "Mapping of datapoint fields to column names for columnar data sources.", "properties": { "numericRestricts": { "description": "Optional. List of restricts for numeric values.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMappingNumericRestrict" } }, "embeddingColumn": { "description": "Required. The column with the vector embeddings for each data point.", "type": "string" }, "metadataColumns": { "description": "Optional. List of columns containing metadata to be included in the index.", "type": "array", "items": { "type": "string" } }, "restricts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMappingRestrict" }, "description": "Optional. List of restricts for string values." }, "idColumn": { "description": "Required. The column with unique identifiers for each data point.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMapping", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelVersionCheckpoint": { "description": "Describes the machine learning model version checkpoint.", "properties": { "checkpointId": { "description": "The ID of the checkpoint.", "type": "string" }, "step": { "format": "int64", "description": "The step of the checkpoint.", "type": "string" }, "epoch": { "format": "int64", "description": "The epoch of the checkpoint.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ModelVersionCheckpoint", "deprecated": true, "type": "object" }, "GoogleCloudAiplatformV1beta1MetricMetadataScoreRange": { "id": "GoogleCloudAiplatformV1beta1MetricMetadataScoreRange", "type": "object", "description": "The range of possible scores for this metric, used for plotting.", "properties": { "max": { "format": "double", "description": "Required. The maximum value of the score range (inclusive).", "type": "number" }, "step": { "description": "Optional. The distance between discrete steps in the range. If unset, the range is assumed to be continuous.", "format": "double", "type": "number" }, "description": { "description": "Optional. The description of the score explaining the directionality etc.", "type": "string" }, "min": { "description": "Required. The minimum value of the score range (inclusive).", "format": "double", "type": "number" } } }, "GoogleCloudAiplatformV1beta1Chunk": { "id": "GoogleCloudAiplatformV1beta1Chunk", "type": "object", "description": "Container for bytes-encoded data such as video frame, audio sample, or a complete binary/text data.", "properties": { "mimeType": { "description": "Required. Mime type of the chunk data. See https://www.iana.org/assignments/media-types/media-types.xhtml for the full list.", "type": "string" }, "data": { "type": "string", "format": "byte", "description": "Required. The data in the chunk." }, "metadata": { "description": "Optional. Metadata that is associated with the data in the payload.", "$ref": "GoogleCloudAiplatformV1beta1Metadata" } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTracking": { "description": "A TrainingJob that trains and uploads an AutoML Video ObjectTracking Model.", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTracking", "type": "object" }, "GoogleCloudAiplatformV1beta1AutoraterConfig": { "description": "The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset.", "properties": { "flipEnabled": { "description": "Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias.", "type": "boolean" }, "generationConfig": { "description": "Optional. Configuration options for model generation and outputs.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig" }, "autoraterModel": { "description": "Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string" }, "samplingCount": { "description": "Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.", "format": "int32", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1AutoraterConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolParameterKVMatchSpec": { "properties": { "useStrictStringMatch": { "description": "Optional. Whether to use STRICT string match on parameter values.", "type": "boolean" } }, "description": "Spec for tool parameter key value match metric.", "id": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1EntityIdSelector": { "properties": { "csvSource": { "$ref": "GoogleCloudAiplatformV1beta1CsvSource", "description": "Source of Csv" }, "entityIdField": { "description": "Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id.", "type": "string" } }, "description": "Selector for entityId. Getting ids from the given source.", "id": "GoogleCloudAiplatformV1beta1EntityIdSelector", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateFeatureGroupOperationMetadata": { "properties": { "genericMetadata": { "description": "Operation metadata for FeatureGroup.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Details of operations that perform update FeatureGroup.", "id": "GoogleCloudAiplatformV1beta1UpdateFeatureGroupOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation", "type": "object", "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.", "properties": { "columnName": { "type": "string" }, "timeFormat": { "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)", "type": "string" } } }, "GoogleTypeExpr": { "id": "GoogleTypeExpr", "type": "object", "properties": { "expression": { "description": "Textual representation of an expression in Common Expression Language syntax.", "type": "string" }, "description": { "description": "Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.", "type": "string" }, "title": { "description": "Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.", "type": "string" }, "location": { "description": "Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.", "type": "string" } }, "description": "Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: \"Summary size limit\" description: \"Determines if a summary is less than 100 chars\" expression: \"document.summary.size() \u003c 100\" Example (Equality): title: \"Requestor is owner\" description: \"Determines if requestor is the document owner\" expression: \"document.owner == request.auth.claims.email\" Example (Logic): title: \"Public documents\" description: \"Determine whether the document should be publicly visible\" expression: \"document.type != 'private' && document.type != 'internal'\" Example (Data Manipulation): title: \"Notification string\" description: \"Create a notification string with a timestamp.\" expression: \"'New message received at ' + string(document.create_time)\" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information." }, "GoogleCloudAiplatformV1beta1ImportModelEvaluationRequest": { "properties": { "modelEvaluation": { "description": "Required. Model evaluation resource to be imported.", "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluation" } }, "description": "Request message for ModelService.ImportModelEvaluation", "id": "GoogleCloudAiplatformV1beta1ImportModelEvaluationRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1RagManagedDbConfigUnprovisioned": { "description": "Disables the RAG Engine service and deletes all your data held within this service. This will halt the billing of the service. NOTE: Once deleted the data cannot be recovered. To start using RAG Engine again, you will need to update the tier by calling the UpdateRagEngineConfig API.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1RagManagedDbConfigUnprovisioned", "type": "object" }, "GoogleCloudAiplatformV1beta1PredefinedSplit": { "id": "GoogleCloudAiplatformV1beta1PredefinedSplit", "type": "object", "description": "Assigns input data to training, validation, and test sets based on the value of a provided key. Supported only for tabular Datasets.", "properties": { "key": { "description": "Required. The key is a name of one of the Dataset's data columns. The value of the key (either the label's value or value in the column) must be one of {`training`, `validation`, `test`}, and it defines to which set the given piece of data is assigned. If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1PurgeExecutionsMetadata": { "properties": { "genericMetadata": { "description": "Operation metadata for purging Executions.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Details of operations that perform MetadataService.PurgeExecutions.", "id": "GoogleCloudAiplatformV1beta1PurgeExecutionsMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1GeminiPreferenceExampleCompletion": { "id": "GoogleCloudAiplatformV1beta1GeminiPreferenceExampleCompletion", "type": "object", "description": "Completion and its preference score.", "properties": { "score": { "description": "The score for the given completion.", "format": "float", "type": "number" }, "completion": { "description": "Single turn completion for the given prompt.", "$ref": "GoogleCloudAiplatformV1beta1Content" } } }, "GoogleCloudAiplatformV1beta1ToolUseExampleExtensionOperation": { "properties": { "extension": { "description": "Resource name of the extension.", "type": "string" }, "operationId": { "description": "Required. Operation ID of the extension.", "type": "string" } }, "description": "Identifies one operation of the extension.", "id": "GoogleCloudAiplatformV1beta1ToolUseExampleExtensionOperation", "type": "object" }, "GoogleCloudAiplatformV1beta1ContentMapContents": { "description": "Repeated Content type.", "properties": { "contents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "description": "Optional. Repeated contents." } }, "id": "GoogleCloudAiplatformV1beta1ContentMapContents", "type": "object" }, "GoogleCloudAiplatformV1beta1PurgeArtifactsRequest": { "properties": { "filter": { "description": "Required. A required filter matching the Artifacts to be purged. E.g., `update_time \u003c= 2020-11-19T11:30:00-04:00`.", "type": "string" }, "force": { "description": "Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Artifact names that would be deleted.", "type": "boolean" } }, "description": "Request message for MetadataService.PurgeArtifacts.", "id": "GoogleCloudAiplatformV1beta1PurgeArtifactsRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoObjectTrackingPredictionParams": { "description": "Prediction model parameters for Video Object Tracking.", "properties": { "confidenceThreshold": { "format": "float", "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", "type": "number" }, "maxPredictions": { "type": "integer", "format": "int32", "description": "The model only returns up to that many top, by confidence score, predictions per frame of the video. If this number is very high, the Model may return fewer predictions per frame. Default value is 50." }, "minBoundingBoxSize": { "description": "Only bounding boxes with shortest edge at least that long as a relative value of video frame size are returned. Default value is 0.0.", "format": "float", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoObjectTrackingPredictionParams", "type": "object" }, "GoogleCloudAiplatformV1beta1CustomJobSpec": { "description": "Represents the spec of a CustomJob.", "properties": { "experiment": { "description": "Optional. The Experiment associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}`", "type": "string" }, "models": { "type": "array", "items": { "type": "string" }, "description": "Optional. The name of the Model resources for which to generate a mapping to artifact URIs. Applicable only to some of the Google-provided custom jobs. Format: `projects/{project}/locations/{location}/models/{model}` In order to retrieve a specific version of the model, also provide the version ID or version alias. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` If no version ID or alias is specified, the \"default\" version will be returned. The \"default\" version alias is created for the first version of the model, and can be moved to other versions later on. There will be exactly one default version." }, "tensorboard": { "description": "Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "type": "string" }, "enableWebAccess": { "description": "Optional. Whether you want Vertex AI to enable [interactive shell access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).", "type": "boolean" }, "pscInterfaceConfig": { "$ref": "GoogleCloudAiplatformV1beta1PscInterfaceConfig", "description": "Optional. Configuration for PSC-I for CustomJob." }, "experimentRun": { "description": "Optional. The Experiment Run associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}`", "type": "string" }, "workerPoolSpecs": { "description": "Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1WorkerPoolSpec" } }, "enableDashboardAccess": { "description": "Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to `true`, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).", "type": "boolean" }, "serviceAccount": { "description": "Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) for the CustomJob's project is used.", "type": "string" }, "network": { "description": "Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the job is not peered with any network.", "type": "string" }, "scheduling": { "$ref": "GoogleCloudAiplatformV1beta1Scheduling", "description": "Scheduling options for a CustomJob." }, "persistentResourceId": { "description": "Optional. The ID of the PersistentResource in the same Project and Location which to run If this is specified, the job will be run on existing machines held by the PersistentResource instead of on-demand short-live machines. The network and CMEK configs on the job should be consistent with those on the PersistentResource, otherwise, the job will be rejected.", "type": "string" }, "reservedIpRanges": { "type": "array", "items": { "type": "string" }, "description": "Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range']." }, "baseOutputDirectory": { "description": "The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = `/model/` * AIP_CHECKPOINT_DIR = `/checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `/logs/` For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = `//model/` * AIP_CHECKPOINT_DIR = `//checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `//logs/`", "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" }, "protectedArtifactLocationId": { "description": "The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1CustomJobSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation", "type": "object", "properties": { "columnName": { "type": "string" } }, "description": "Training pipeline will infer the proper transformation based on the statistic of dataset." }, "GoogleCloudAiplatformV1beta1EvaluateDatasetRequest": { "description": "Request message for EvaluationService.EvaluateDataset.", "properties": { "dataset": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationDataset", "description": "Required. The dataset used for evaluation." }, "metrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Metric" }, "description": "Required. The metrics used for evaluation." }, "location": { "description": "Required. The resource name of the Location to evaluate the dataset. Format: `projects/{project}/locations/{location}`", "type": "string" }, "autoraterConfig": { "description": "Optional. Autorater config used for evaluation. Currently only publisher Gemini models are supported. Format: `projects/{PROJECT}/locations/{LOCATION}/publishers/google/models/{MODEL}.`", "$ref": "GoogleCloudAiplatformV1beta1AutoraterConfig" }, "outputConfig": { "description": "Required. Config for evaluation output.", "$ref": "GoogleCloudAiplatformV1beta1OutputConfig" } }, "id": "GoogleCloudAiplatformV1beta1EvaluateDatasetRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata", "type": "object", "properties": { "costMilliNodeHours": { "type": "string", "format": "int64", "description": "The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours." }, "successfulStopReason": { "type": "string", "enumDescriptions": [ "Should not be set.", "The inputs.budgetMilliNodeHours had been reached.", "Further training of the Model ceased to increase its quality, since it already has converged." ], "description": "For successful job completions, this is the reason why the job has finished.", "enum": [ "SUCCESSFUL_STOP_REASON_UNSPECIFIED", "BUDGET_REACHED", "MODEL_CONVERGED" ] } } }, "GoogleCloudAiplatformV1beta1EventActions": { "id": "GoogleCloudAiplatformV1beta1EventActions", "type": "object", "properties": { "skipSummarization": { "description": "Optional. If true, it won't call model to summarize function response. Only used for function_response event.", "type": "boolean" }, "artifactDelta": { "description": "Optional. Indicates that the event is updating an artifact. key is the filename, value is the version.", "type": "object", "additionalProperties": { "type": "integer", "format": "int32" } }, "escalate": { "description": "Optional. The agent is escalating to a higher level agent.", "type": "boolean" }, "transferAgent": { "description": "Optional. If set, the event transfers to the specified agent.", "type": "string" }, "stateDelta": { "description": "Optional. Indicates that the event is updating the state with the given delta.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "requestedAuthConfigs": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. Will only be set by a tool response indicating tool request euc. Struct key is the function call id since one function call response (from model) could correspond to multiple function calls. Struct value is the required auth config, which can be another struct." } }, "description": "Actions are parts of events that are executed by the agent." }, "GoogleCloudAiplatformV1beta1AssessDataRequestTuningResourceUsageAssessmentConfig": { "properties": { "modelName": { "description": "Required. The name of the model used for tuning.", "type": "string" } }, "description": "Configuration for the tuning resource usage assessment.", "id": "GoogleCloudAiplatformV1beta1AssessDataRequestTuningResourceUsageAssessmentConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityResult": { "properties": { "pairwiseChoice": { "readOnly": true, "type": "string", "enumDescriptions": [ "Unspecified prediction choice.", "Baseline prediction wins", "Candidate prediction wins", "Winner cannot be determined" ], "enum": [ "PAIRWISE_CHOICE_UNSPECIFIED", "BASELINE", "CANDIDATE", "TIE" ], "description": "Output only. Pairwise summarization prediction choice." }, "confidence": { "type": "number", "readOnly": true, "description": "Output only. Confidence for summarization quality score.", "format": "float" }, "explanation": { "type": "string", "readOnly": true, "description": "Output only. Explanation for summarization quality score." } }, "description": "Spec for pairwise summarization quality result.", "id": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityResult", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateOnlineEvaluatorOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Common part of operation metadata." } }, "description": "Metadata for the CreateOnlineEvaluator operation.", "id": "GoogleCloudAiplatformV1beta1CreateOnlineEvaluatorOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ListModelMonitoringJobsResponse": { "properties": { "nextPageToken": { "description": "The standard List next-page token.", "type": "string" }, "modelMonitoringJobs": { "description": "A list of ModelMonitoringJobs that matches the specified filter in the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJob" } } }, "description": "Response message for ModelMonitoringService.ListModelMonitoringJobs.", "id": "GoogleCloudAiplatformV1beta1ListModelMonitoringJobsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SpeculativeDecodingSpecDraftModelSpeculation": { "id": "GoogleCloudAiplatformV1beta1SpeculativeDecodingSpecDraftModelSpeculation", "type": "object", "description": "Draft model speculation works by using the smaller model to generate candidate tokens for speculative decoding.", "properties": { "draftModel": { "description": "Required. The resource name of the draft model.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1PipelineTaskDetailPipelineTaskStatus": { "properties": { "state": { "readOnly": true, "type": "string", "enumDescriptions": [ "Unspecified.", "Specifies pending state for the task.", "Specifies task is being executed.", "Specifies task completed successfully.", "Specifies Task cancel is in pending state.", "Specifies task is being cancelled.", "Specifies task was cancelled.", "Specifies task failed.", "Specifies task was skipped due to cache hit.", "Specifies that the task was not triggered because the task's trigger policy is not satisfied. The trigger policy is specified in the `condition` field of PipelineJob.pipeline_spec." ], "enum": [ "STATE_UNSPECIFIED", "PENDING", "RUNNING", "SUCCEEDED", "CANCEL_PENDING", "CANCELLING", "CANCELLED", "FAILED", "SKIPPED", "NOT_TRIGGERED" ], "description": "Output only. The state of the task." }, "updateTime": { "description": "Output only. Update time of this status.", "format": "google-datetime", "type": "string", "readOnly": true }, "error": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried." } }, "description": "A single record of the task status.", "id": "GoogleCloudAiplatformV1beta1PipelineTaskDetailPipelineTaskStatus", "type": "object" }, "GoogleCloudAiplatformV1beta1UndeployIndexRequest": { "id": "GoogleCloudAiplatformV1beta1UndeployIndexRequest", "type": "object", "description": "Request message for IndexEndpointService.UndeployIndex.", "properties": { "deployedIndexId": { "description": "Required. The ID of the DeployedIndex to be undeployed from the IndexEndpoint.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1PreferenceOptimizationHyperParameters": { "id": "GoogleCloudAiplatformV1beta1PreferenceOptimizationHyperParameters", "type": "object", "properties": { "epochCount": { "type": "string", "description": "Optional. Number of complete passes the model makes over the entire training dataset during training.", "format": "int64" }, "adapterSize": { "enum": [ "ADAPTER_SIZE_UNSPECIFIED", "ADAPTER_SIZE_ONE", "ADAPTER_SIZE_TWO", "ADAPTER_SIZE_FOUR", "ADAPTER_SIZE_EIGHT", "ADAPTER_SIZE_SIXTEEN", "ADAPTER_SIZE_THIRTY_TWO" ], "description": "Optional. Adapter size for preference optimization.", "type": "string", "enumDescriptions": [ "Adapter size is unspecified.", "Adapter size 1.", "Adapter size 2.", "Adapter size 4.", "Adapter size 8.", "Adapter size 16.", "Adapter size 32." ] }, "beta": { "type": "number", "format": "double", "description": "Optional. Weight for KL Divergence regularization." }, "learningRateMultiplier": { "format": "double", "description": "Optional. Multiplier for adjusting the default learning rate.", "type": "number" } }, "description": "Hyperparameters for Preference Optimization." }, "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopicCustomMemoryTopic": { "id": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopicCustomMemoryTopic", "type": "object", "properties": { "label": { "description": "Required. Represents the label of the topic.", "type": "string" }, "description": { "description": "Required. Represents the description of the memory topic. This should explain what information should be extracted for this topic.", "type": "string" } }, "description": "A custom memory topic defined by the developer." }, "GoogleCloudAiplatformV1beta1EvaluationRunDataSource": { "id": "GoogleCloudAiplatformV1beta1EvaluationRunDataSource", "type": "object", "properties": { "evaluationSet": { "description": "The EvaluationSet resource name. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`", "type": "string" }, "bigqueryRequestSet": { "description": "Evaluation data in bigquery.", "$ref": "GoogleCloudAiplatformV1beta1BigQueryRequestSet" } }, "description": "The data source for the evaluation run." }, "GoogleCloudAiplatformV1beta1TunedModelRef": { "properties": { "tuningJob": { "description": "Support migration from tuning job list page, from gemini-1.0-pro-002 to 1.5 and above.", "type": "string" }, "tunedModel": { "description": "Support migration from model registry.", "type": "string" }, "pipelineJob": { "description": "Support migration from tuning job list page, from bison model to gemini model.", "type": "string" } }, "description": "TunedModel Reference for legacy model migration.", "id": "GoogleCloudAiplatformV1beta1TunedModelRef", "type": "object" }, "GoogleCloudAiplatformV1beta1OutputConfig": { "description": "Config for evaluation output.", "properties": { "gcsDestination": { "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", "description": "Cloud storage destination for evaluation output." } }, "id": "GoogleCloudAiplatformV1beta1OutputConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelEvaluationBiasConfig": { "id": "GoogleCloudAiplatformV1beta1ModelEvaluationBiasConfig", "type": "object", "properties": { "biasSlices": { "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpec", "description": "Specification for how the data should be sliced for bias. It contains a list of slices, with limitation of two slices. The first slice of data will be the slice_a. The second slice in the list (slice_b) will be compared against the first slice. If only a single slice is provided, then slice_a will be compared against \"not slice_a\". Below are examples with feature \"education\" with value \"low\", \"medium\", \"high\" in the dataset: Example 1: bias_slices = [{'education': 'low'}] A single slice provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'medium' or 'high'. Example 2: bias_slices = [{'education': 'low'}, {'education': 'high'}] Two slices provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'high'." }, "labels": { "description": "Positive labels selection on the target field.", "type": "array", "items": { "type": "string" } } }, "description": "Configuration for bias detection." }, "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateMetatdata": { "id": "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateMetatdata", "type": "object", "description": "This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for suggesting Trials." }, "study": { "description": "The name of the Study that the Trial belongs to.", "type": "string" }, "trial": { "description": "The Trial name.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInput": { "description": "Input for question answering quality metric.", "properties": { "metricSpec": { "description": "Required. Spec for question answering quality score metric.", "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualitySpec" }, "instance": { "description": "Required. Question answering quality instance.", "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInstance" } }, "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInput", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpec": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpec", "type": "object", "properties": { "containerSpec": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecContainerSpec", "description": "Deploy from a container image with a defined entrypoint and commands." }, "packageSpec": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecPackageSpec", "description": "Optional. User provided package spec of the ReasoningEngine. Ignored when users directly specify a deployment image through `deployment_spec.first_party_image_override`, but keeping the field_behavior to avoid introducing breaking changes. The `deployment_source` field should not be set if `package_spec` is specified." }, "identityType": { "description": "Optional. The identity type to use for the Reasoning Engine. If not specified, the `service_account` field will be used if set, otherwise the default Vertex AI Reasoning Engine Service Agent in the project will be used.", "enum": [ "IDENTITY_TYPE_UNSPECIFIED", "SERVICE_ACCOUNT", "AGENT_IDENTITY" ], "type": "string", "enumDescriptions": [ "Default value. Use a custom service account if the `service_account` field is set, otherwise use the default Vertex AI Reasoning Engine Service Agent in the project. Same behavior as SERVICE_ACCOUNT.", "Use a custom service account if the `service_account` field is set, otherwise use the default Vertex AI Reasoning Engine Service Agent in the project.", "Use Agent Identity. The `service_account` field must not be set." ] }, "deploymentSpec": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpec", "description": "Optional. The specification of a Reasoning Engine deployment." }, "classMethods": { "description": "Optional. Declarations for object class methods in OpenAPI specification format.", "type": "array", "items": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "agentFramework": { "description": "Optional. The OSS agent framework used to develop the agent. Currently supported values: \"google-adk\", \"langchain\", \"langgraph\", \"ag2\", \"llama-index\", \"custom\".", "type": "string" }, "effectiveIdentity": { "readOnly": true, "type": "string", "description": "Output only. The identity to use for the Reasoning Engine. It can contain one of the following values: * service-{project}@gcp-sa-aiplatform-re.googleapis.com (for SERVICE_AGENT identity type) * {name}@{project}.gserviceaccount.com (for SERVICE_ACCOUNT identity type) * agents.global.{org}.system.id.goog/resources/aiplatform/projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine} (for AGENT_IDENTITY identity type)" }, "serviceAccount": { "description": "Optional. The service account that the Reasoning Engine artifact runs as. It should have \"roles/storage.objectViewer\" for reading the user project's Cloud Storage and \"roles/aiplatform.user\" for using Vertex extensions. If not specified, the Vertex AI Reasoning Engine Service Agent in the project will be used.", "type": "string" }, "agentCard": { "description": "Optional. The A2A Agent Card for the agent (if available). It follows the specification at https://a2a-protocol.org/latest/specification/#5-agent-discovery-the-agent-card.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "sourceCodeSpec": { "description": "Deploy from source code files with a defined entrypoint.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpec" } }, "description": "ReasoningEngine configurations" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs": { "properties": { "modelType": { "enum": [ "MODEL_TYPE_UNSPECIFIED", "CLOUD_HIGH_ACCURACY_1", "CLOUD_LOW_ACCURACY_1", "MOBILE_TF_LOW_LATENCY_1" ], "type": "string", "enumDescriptions": [ "Should not be set.", "A model to be used via prediction calls to uCAIP API. Expected to have a higher latency, but should also have a higher prediction quality than other models.", "A model to be used via prediction calls to uCAIP API. Expected to have a lower latency but relatively lower prediction quality.", "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow model and used on a mobile or edge device afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models." ] }, "budgetMilliNodeHours": { "type": "string", "format": "int64", "description": "The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. Or actual_wall_clock_hours = train_budget_milli_node_hours / (number_of_nodes_involved * 1000) For modelType `cloud-high-accuracy-1`(default), the budget must be between 20,000 and 2,000,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time (1000 milli * 24 hours * 8 nodes)." }, "baseModelId": { "description": "The ID of the `base` model. If it is specified, the new model will be trained based on the `base` model. Otherwise, the new model will be trained from scratch. The `base` model must be in the same Project and Location as the new Model to train, and have the same modelType.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs", "type": "object" }, "GoogleCloudAiplatformV1beta1TrialParameter": { "description": "A message representing a parameter to be tuned.", "properties": { "parameterId": { "description": "Output only. The ID of the parameter. The parameter should be defined in StudySpec's Parameters.", "type": "string", "readOnly": true }, "value": { "description": "Output only. The value of the parameter. `number_value` will be set if a parameter defined in StudySpec is in type 'INTEGER', 'DOUBLE' or 'DISCRETE'. `string_value` will be set if a parameter defined in StudySpec is in type 'CATEGORICAL'.", "readOnly": true, "type": "any" } }, "id": "GoogleCloudAiplatformV1beta1TrialParameter", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResult": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResult", "type": "object", "properties": { "timeSegmentEnd": { "type": "string", "format": "google-duration", "description": "The end, inclusive, of the video's time segment in which the object instance has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end." }, "frames": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame" }, "description": "All of the frames of the video in which a single object instance has been detected. The bounding boxes in the frames identify the same object." }, "timeSegmentStart": { "type": "string", "format": "google-duration", "description": "The beginning, inclusive, of the video's time segment in which the object instance has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end." }, "confidence": { "format": "float", "description": "The Model's confidence in correction of this prediction, higher value means higher confidence.", "type": "number" }, "id": { "description": "The resource ID of the AnnotationSpec that had been identified.", "type": "string" }, "displayName": { "description": "The display name of the AnnotationSpec that had been identified.", "type": "string" } }, "description": "Prediction output format for Video Object Tracking." }, "GoogleCloudAiplatformV1beta1ReadFeatureValuesRequest": { "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesRequest", "type": "object", "properties": { "featureSelector": { "description": "Required. Selector choosing Features of the target EntityType.", "$ref": "GoogleCloudAiplatformV1beta1FeatureSelector" }, "entityId": { "description": "Required. ID for a specific entity. For example, for a machine learning model predicting user clicks on a website, an entity ID could be `user_123`.", "type": "string" } }, "description": "Request message for FeaturestoreOnlineServingService.ReadFeatureValues." }, "GoogleCloudAiplatformV1beta1ListMemoriesResponse": { "id": "GoogleCloudAiplatformV1beta1ListMemoriesResponse", "type": "object", "description": "Response message for MemoryBankService.ListMemories.", "properties": { "memories": { "description": "List of Memories in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Memory" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListMemoriesRequest.page_token to obtain that page.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1StructuredMemoryConfigSchemaConfig": { "id": "GoogleCloudAiplatformV1beta1StructuredMemoryConfigSchemaConfig", "type": "object", "properties": { "memoryType": { "type": "string", "enumDescriptions": [ "Represents an unspecified memory type. This value should not be used.", "Indicates belonging to a collection of natural language memories.", "Indicates belonging to a structured profile." ], "description": "Optional. Represents the type of the structured memories associated with the schema. If not set, then `STRUCTURED_PROFILE` will be used.", "enum": [ "MEMORY_TYPE_UNSPECIFIED", "NATURAL_LANGUAGE_COLLECTION", "STRUCTURED_PROFILE" ] }, "id": { "description": "Required. Represents the ID of the schema. Must be 1-63 characters, start with a lowercase letter, and consist of lowercase letters, numbers, and hyphens.", "type": "string" }, "schema": { "description": "Required. Represents the OpenAPI schema of the structured memories. The schema `type` cannot be `ARRAY` when `memory_type` is `STRUCTURED_PROFILE`.", "$ref": "GoogleCloudAiplatformV1beta1Schema" } }, "description": "Schema configuration for structured memories." }, "GoogleCloudAiplatformV1beta1MetricxInput": { "id": "GoogleCloudAiplatformV1beta1MetricxInput", "type": "object", "description": "Input for MetricX metric.", "properties": { "instance": { "description": "Required. Metricx instance.", "$ref": "GoogleCloudAiplatformV1beta1MetricxInstance" }, "metricSpec": { "description": "Required. Spec for Metricx metric.", "$ref": "GoogleCloudAiplatformV1beta1MetricxSpec" } } }, "GoogleCloudAiplatformV1beta1BleuMetricValue": { "id": "GoogleCloudAiplatformV1beta1BleuMetricValue", "type": "object", "description": "Bleu metric value for an instance.", "properties": { "score": { "type": "number", "readOnly": true, "description": "Output only. Bleu score.", "format": "float" } } }, "GoogleCloudAiplatformV1beta1FeatureGroup": { "description": "Vertex AI Feature Group.", "properties": { "bigQuery": { "$ref": "GoogleCloudAiplatformV1beta1FeatureGroupBigQuery", "description": "Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source. The BigQuery source table or view must have at least one entity ID column and a column named `feature_timestamp`." }, "serviceAgentType": { "type": "string", "enumDescriptions": [ "By default, the project-level Vertex AI Service Agent is enabled.", "Specifies the project-level Vertex AI Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).", "Enable a FeatureGroup service account to be created by Vertex AI and output in the field `service_account_email`. This service account will be used to read from the source BigQuery table during jobs under a FeatureGroup." ], "description": "Optional. Service agent type used during jobs under a FeatureGroup. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureGroup within a project, a separate service account should be provisioned by setting this field to `SERVICE_AGENT_TYPE_FEATURE_GROUP`. This will generate a separate service account to access the BigQuery source table.", "enum": [ "SERVICE_AGENT_TYPE_UNSPECIFIED", "SERVICE_AGENT_TYPE_PROJECT", "SERVICE_AGENT_TYPE_FEATURE_GROUP" ] }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this FeatureGroup was created.", "format": "google-datetime" }, "description": { "description": "Optional. Description of the FeatureGroup.", "type": "string" }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "serviceAccountEmail": { "description": "Output only. A Service Account unique to this FeatureGroup. The role bigquery.dataViewer should be granted to this service account to allow Vertex AI Feature Store to access source data while running jobs under this FeatureGroup.", "type": "string", "readOnly": true }, "name": { "description": "Identifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`", "type": "string" }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this FeatureGroup was last updated.", "readOnly": true, "type": "string" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." } }, "id": "GoogleCloudAiplatformV1beta1FeatureGroup", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelExplanation": { "id": "GoogleCloudAiplatformV1beta1ModelExplanation", "type": "object", "properties": { "meanAttributions": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Attribution" }, "description": "Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. Attribution.output_index can be used to identify which output this attribution is explaining. The baselineOutputValue, instanceOutputValue and featureAttributions fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. Attribution.approximation_error is not populated." } }, "description": "Aggregated explanation metrics for a Model over a set of instances." }, "GoogleCloudAiplatformV1beta1FeatureSelector": { "properties": { "idMatcher": { "description": "Required. Matches Features based on ID.", "$ref": "GoogleCloudAiplatformV1beta1IdMatcher" } }, "description": "Selector for Features of an EntityType.", "id": "GoogleCloudAiplatformV1beta1FeatureSelector", "type": "object" }, "GoogleCloudAiplatformV1beta1TensorboardTimeSeries": { "description": "TensorboardTimeSeries maps to times series produced in training runs", "properties": { "displayName": { "description": "Required. User provided name of this TensorboardTimeSeries. This value should be unique among all TensorboardTimeSeries resources belonging to the same TensorboardRun resource (parent resource).", "type": "string" }, "pluginName": { "description": "Immutable. Name of the plugin this time series pertain to. Such as Scalar, Tensor, Blob", "type": "string" }, "description": { "description": "Description of this TensorboardTimeSeries.", "type": "string" }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this TensorboardTimeSeries was created.", "format": "google-datetime" }, "valueType": { "type": "string", "enumDescriptions": [ "The value type is unspecified.", "Used for TensorboardTimeSeries that is a list of scalars. E.g. accuracy of a model over epochs/time.", "Used for TensorboardTimeSeries that is a list of tensors. E.g. histograms of weights of layer in a model over epoch/time.", "Used for TensorboardTimeSeries that is a list of blob sequences. E.g. set of sample images with labels over epochs/time." ], "enum": [ "VALUE_TYPE_UNSPECIFIED", "SCALAR", "TENSOR", "BLOB_SEQUENCE" ], "description": "Required. Immutable. Type of TensorboardTimeSeries value." }, "etag": { "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "pluginData": { "type": "string", "description": "Data of the current plugin, with the size limited to 65KB.", "format": "byte" }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this TensorboardTimeSeries was last updated.", "readOnly": true, "type": "string" }, "name": { "description": "Output only. Name of the TensorboardTimeSeries.", "type": "string", "readOnly": true }, "metadata": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeriesMetadata", "description": "Output only. Scalar, Tensor, or Blob metadata for this TensorboardTimeSeries." } }, "id": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries", "type": "object" }, "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox": { "properties": { "y2": { "format": "int32", "description": "The Y coordinate of the bottom-right corner, in pixels.", "type": "integer" }, "y1": { "type": "integer", "format": "int32", "description": "The Y coordinate of the top-left corner, in pixels." }, "x2": { "type": "integer", "description": "The X coordinate of the bottom-right corner, in pixels.", "format": "int32" }, "x1": { "format": "int32", "description": "The X coordinate of the top-left corner, in pixels.", "type": "integer" } }, "description": "An integer bounding box of original pixels of the image for the detected labels.", "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs", "type": "object", "properties": { "disableEarlyStopping": { "description": "Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Object Detection might stop training before the entire training budget has been used.", "type": "boolean" }, "budgetMilliNodeHours": { "type": "string", "format": "int64", "description": "The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType `cloud`(default), the budget must be between 20,000 and 900,000 milli node hours, inclusive. The default value is 216,000 which represents one day in wall time, considering 9 nodes are used. For model types `mobile-tf-low-latency-1`, `mobile-tf-versatile-1`, `mobile-tf-high-accuracy-1` the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used." }, "modelType": { "type": "string", "enumDescriptions": [ "Should not be set.", "A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to have a higher latency, but should also have a higher prediction quality than other cloud models.", "A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to have a low latency, but may have lower prediction quality than other cloud models.", "A model best tailored to be used within Google Cloud, and which cannot be exported. Compared to the CLOUD_HIGH_ACCURACY_1 and CLOUD_LOW_LATENCY_1 models above, it is expected to have higher prediction quality and lower latency.", "A model that, in addition to being available within Google Cloud can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models.", "A model that, in addition to being available within Google Cloud can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards.", "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other mobile models.", "A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to best support predictions in streaming with lower latency and lower prediction quality than other cloud models.", "SpineNet for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", "YOLO for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally." ], "enum": [ "MODEL_TYPE_UNSPECIFIED", "CLOUD_HIGH_ACCURACY_1", "CLOUD_LOW_LATENCY_1", "CLOUD_1", "MOBILE_TF_LOW_LATENCY_1", "MOBILE_TF_VERSATILE_1", "MOBILE_TF_HIGH_ACCURACY_1", "CLOUD_STREAMING_1", "SPINENET", "YOLO" ] }, "tunableParameter": { "description": "Trainer type for Vision TrainRequest.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter" }, "uptrainBaseModelId": { "description": "The ID of `base` model for upTraining. If it is specified, the new model will be upTrained based on the `base` model for upTraining. Otherwise, the new model will be trained from scratch. The `base` model for upTraining must be in the same Project and Location as the new Model to train, and have the same modelType.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1CreatePersistentResourceOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreatePersistentResourceOperationMetadata", "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for PersistentResource." }, "progressMessage": { "description": "Progress Message for Create LRO", "type": "string" } }, "description": "Details of operations that perform create PersistentResource." }, "GoogleCloudAiplatformV1beta1CodeExecutionResult": { "id": "GoogleCloudAiplatformV1beta1CodeExecutionResult", "type": "object", "properties": { "output": { "description": "Optional. Contains stdout when code execution is successful, stderr or other description otherwise.", "type": "string" }, "outcome": { "description": "Required. Outcome of the code execution.", "enum": [ "OUTCOME_UNSPECIFIED", "OUTCOME_OK", "OUTCOME_FAILED", "OUTCOME_DEADLINE_EXCEEDED" ], "type": "string", "enumDescriptions": [ "Unspecified status. This value should not be used.", "Code execution completed successfully. `output` contains the stdout, if any.", "Code execution failed. `output` contains the stderr and stdout, if any.", "Code execution ran for too long, and was cancelled. There may or may not be a partial `output` present." ] } }, "description": "Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used." }, "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateMlEngineModelVersionConfig": { "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateMlEngineModelVersionConfig", "type": "object", "properties": { "modelDisplayName": { "description": "Required. Display name of the model in Vertex AI. System will pick a display name if unspecified.", "type": "string" }, "modelVersion": { "description": "Required. Full resource name of ml engine model version. Format: `projects/{project}/models/{model}/versions/{version}`.", "type": "string" }, "endpoint": { "description": "Required. The ml.googleapis.com endpoint that this model version should be migrated from. Example values: * ml.googleapis.com * us-centrall-ml.googleapis.com * europe-west4-ml.googleapis.com * asia-east1-ml.googleapis.com", "type": "string" } }, "description": "Config for migrating version in ml.googleapis.com to Vertex AI's Model." }, "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolylineAnnotation": { "description": "Represents a polyline in image.", "properties": { "vertexes": { "description": "The vertexes are connected one by one and the last vertex in not connected to the first one.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaVertex" } }, "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolylineAnnotation", "type": "object" }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplate": { "description": "The specification of a SandboxEnvironmentTemplate. A SandboxEnvironmentTemplate defines a template for creating SandboxEnvironments.", "properties": { "defaultContainerEnvironment": { "description": "The sandbox environment for default container workloads.", "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateDefaultContainerEnvironment" }, "warmPoolConfig": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateWarmPoolConfig", "description": "Optional. The configuration for the warm pool of this template." }, "updateTime": { "format": "google-datetime", "description": "Output only. The timestamp when this SandboxEnvironmentTemplate was most recently updated.", "readOnly": true, "type": "string" }, "name": { "description": "Identifier. The resource name of the SandboxEnvironmentTemplate. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentTemplates/{sandbox_environment_template}`", "type": "string" }, "customContainerEnvironment": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateCustomContainerEnvironment", "description": "The sandbox environment for custom container workloads." }, "createTime": { "description": "Output only. The timestamp when this SandboxEnvironmentTemplate was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "egressControlConfig": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateEgressControlConfig", "description": "Optional. The configuration for egress control of this template." }, "state": { "enum": [ "UNSPECIFIED", "PROVISIONING", "ACTIVE", "DEPROVISIONING", "DELETED", "FAILED" ], "description": "Output only. The state of the sandbox environment template.", "readOnly": true, "type": "string", "enumDescriptions": [ "The default value. This value is unused.", "Runtime resources are being allocated for the sandbox environment.", "Sandbox runtime is ready for serving.", "Sandbox runtime is halted, performing tear down tasks.", "Sandbox has terminated with underlying runtime failure.", "Sandbox has failed to provision." ] }, "displayName": { "description": "Required. The display name of the SandboxEnvironmentTemplate.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplate", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfigTrafficSplitAlwaysLatest": { "description": "Traffic distribution configuration, where all traffic is sent to the latest Runtime Revision.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfigTrafficSplitAlwaysLatest", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigAutoraterConfig": { "id": "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigAutoraterConfig", "type": "object", "properties": { "generationConfig": { "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig", "description": "Optional. Configuration options for model generation and outputs." }, "autoraterModel": { "description": "Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string" }, "sampleCount": { "type": "integer", "description": "Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.", "format": "int32" } }, "description": "The autorater config used for the evaluation run." }, "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataBigQuerySource": { "properties": { "uri": { "description": "The URI of a BigQuery table. e.g. bq://projectId.bqDatasetId.bqTableId", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataBigQuerySource", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigTtlConfig": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigTtlConfig", "type": "object", "description": "Configuration for automatically setting the TTL (\"time-to-live\") of the memories in the Memory Bank.", "properties": { "granularTtlConfig": { "description": "Optional. The granular TTL configuration of the memories in the Memory Bank.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigTtlConfigGranularTtlConfig" }, "memoryRevisionDefaultTtl": { "type": "string", "format": "google-duration", "description": "Optional. The default TTL duration of the memory revisions in the Memory Bank. This applies to all operations that create a memory revision. If not set, a default TTL of 365 days will be used." }, "defaultTtl": { "type": "string", "format": "google-duration", "description": "Optional. The default TTL duration of the memories in the Memory Bank. This applies to all operations that create or update a memory." } } }, "GoogleCloudAiplatformV1beta1Event": { "description": "An edge describing the relationship between an Artifact and an Execution in a lineage graph.", "properties": { "artifact": { "description": "Required. The relative resource name of the Artifact in the Event.", "type": "string" }, "execution": { "description": "Output only. The relative resource name of the Execution in the Event.", "readOnly": true, "type": "string" }, "type": { "description": "Required. The type of the Event.", "enum": [ "TYPE_UNSPECIFIED", "INPUT", "OUTPUT" ], "type": "string", "enumDescriptions": [ "Unspecified whether input or output of the Execution.", "An input of the Execution.", "An output of the Execution." ] }, "labels": { "description": "The labels with user-defined metadata to annotate Events. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Event (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", "type": "object", "additionalProperties": { "type": "string" } }, "eventTime": { "format": "google-datetime", "description": "Output only. Time the Event occurred.", "readOnly": true, "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1Event", "type": "object" }, "GoogleCloudAiplatformV1beta1CancelBatchPredictionJobRequest": { "description": "Request message for JobService.CancelBatchPredictionJob.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1CancelBatchPredictionJobRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1Schedule": { "properties": { "endTime": { "description": "Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count \u003e= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.", "format": "google-datetime", "type": "string" }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this Schedule was updated." }, "maxConcurrentActiveRunCount": { "format": "int64", "description": "Optional. Specifies the maximum number of active runs that can be executed concurrently for this Schedule. This limits the number of runs that can be in a non-terminal state at the same time. Currently, this field is only supported for requests of type CreatePipelineJobRequest.", "type": "string" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this Schedule was created." }, "allowQueueing": { "description": "Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.", "type": "boolean" }, "startedRunCount": { "type": "string", "readOnly": true, "description": "Output only. The number of runs started by this schedule.", "format": "int64" }, "maxRunCount": { "type": "string", "format": "int64", "description": "Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count \u003e= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified." }, "createModelMonitoringJobRequest": { "$ref": "GoogleCloudAiplatformV1beta1CreateModelMonitoringJobRequest", "description": "Request for ModelMonitoringService.CreateModelMonitoringJob." }, "catchUp": { "description": "Output only. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false.", "type": "boolean", "readOnly": true }, "name": { "description": "Immutable. The resource name of the Schedule.", "type": "string" }, "lastResumeTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this Schedule was last resumed. Unset if never resumed from pause." }, "cron": { "description": "Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: \"CRON_TZ=${IANA_TIME_ZONE}\" or \"TZ=${IANA_TIME_ZONE}\". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, \"CRON_TZ=America/New_York 1 * * * *\", or \"TZ=America/New_York 1 * * * *\".", "type": "string" }, "createNotebookExecutionJobRequest": { "$ref": "GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobRequest", "description": "Request for NotebookService.CreateNotebookExecutionJob." }, "nextRunTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule." }, "lastScheduledRunResponse": { "description": "Output only. Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ScheduleRunResponse" }, "lastPauseTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this Schedule was last paused. Unset if never paused.", "format": "google-datetime" }, "startTime": { "format": "google-datetime", "description": "Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.", "type": "string" }, "state": { "description": "Output only. The state of this Schedule.", "enum": [ "STATE_UNSPECIFIED", "ACTIVE", "PAUSED", "COMPLETED" ], "type": "string", "enumDescriptions": [ "Unspecified.", "The Schedule is active. Runs are being scheduled on the user-specified timespec.", "The schedule is paused. No new runs will be created until the schedule is resumed. Already started runs will be allowed to complete.", "The Schedule is completed. No new runs will be scheduled. Already started runs will be allowed to complete. Schedules in completed state cannot be paused or resumed." ], "readOnly": true }, "maxConcurrentRunCount": { "format": "int64", "description": "Required. Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).", "type": "string" }, "displayName": { "description": "Required. User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "createPipelineJobRequest": { "description": "Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).", "$ref": "GoogleCloudAiplatformV1beta1CreatePipelineJobRequest" } }, "description": "An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.", "id": "GoogleCloudAiplatformV1beta1Schedule", "type": "object" }, "GoogleCloudAiplatformV1beta1CorpusStatus": { "id": "GoogleCloudAiplatformV1beta1CorpusStatus", "type": "object", "properties": { "errorStatus": { "description": "Output only. Only when the `state` field is ERROR.", "readOnly": true, "type": "string" }, "state": { "enum": [ "UNKNOWN", "INITIALIZED", "ACTIVE", "ERROR" ], "description": "Output only. RagCorpus life state.", "readOnly": true, "type": "string", "enumDescriptions": [ "This state is not supposed to happen.", "RagCorpus resource entry is initialized, but hasn't done validation.", "RagCorpus is provisioned successfully and is ready to serve.", "RagCorpus is in a problematic situation. See `error_message` field for details." ] } }, "description": "RagCorpus status." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity": { "description": "A duration of time expressed in time granularity units.", "properties": { "quantity": { "type": "string", "format": "int64", "description": "The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1." }, "unit": { "description": "The time granularity unit of this time period. The supported units are: * \"minute\" * \"hour\" * \"day\" * \"week\" * \"month\" * \"year\"", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity", "type": "object" }, "GoogleCloudAiplatformV1beta1GroundednessResult": { "description": "Spec for groundedness result.", "properties": { "score": { "format": "float", "description": "Output only. Groundedness score.", "readOnly": true, "type": "number" }, "confidence": { "description": "Output only. Confidence for groundedness score.", "format": "float", "type": "number", "readOnly": true }, "explanation": { "readOnly": true, "type": "string", "description": "Output only. Explanation for groundedness score." } }, "id": "GoogleCloudAiplatformV1beta1GroundednessResult", "type": "object" }, "GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext": { "id": "GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext", "type": "object", "description": "Context retrieved from a data source to ground the model's response. This is used when a retrieval tool fetches information from a user-provided corpus or a public dataset.", "properties": { "ragChunk": { "$ref": "GoogleCloudAiplatformV1beta1RagChunk", "description": "Additional context for a Retrieval-Augmented Generation (RAG) retrieval result. This is populated only when the RAG retrieval tool is used." }, "uri": { "description": "The URI of the retrieved data source.", "type": "string" }, "documentName": { "description": "Output only. The full resource name of the referenced Vertex AI Search document. This is used to identify the specific document that was retrieved. The format is `projects/{project}/locations/{location}/collections/{collection}/dataStores/{data_store}/branches/{branch}/documents/{document}`.", "readOnly": true, "type": "string" }, "text": { "description": "The content of the retrieved data source.", "type": "string" }, "title": { "description": "The title of the retrieved data source.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfig": { "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfig", "type": "object", "description": "Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset.", "properties": { "dataset": { "description": "Required. Full resource name of data labeling Dataset. Format: `projects/{project}/datasets/{dataset}`.", "type": "string" }, "migrateDataLabelingAnnotatedDatasetConfigs": { "description": "Optional. Configs for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery. The specified AnnotatedDatasets have to belong to the datalabeling Dataset.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig" } }, "datasetDisplayName": { "description": "Optional. Display name of the Dataset in Vertex AI. System will pick a display name if unspecified.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ProbeHttpHeader": { "id": "GoogleCloudAiplatformV1beta1ProbeHttpHeader", "type": "object", "description": "HttpHeader describes a custom header to be used in HTTP probes", "properties": { "name": { "description": "The header field name. This will be canonicalized upon output, so case-variant names will be understood as the same header.", "type": "string" }, "value": { "description": "The header field value", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ToolNameMatchMetricValue": { "id": "GoogleCloudAiplatformV1beta1ToolNameMatchMetricValue", "type": "object", "properties": { "score": { "format": "float", "description": "Output only. Tool name match score.", "readOnly": true, "type": "number" } }, "description": "Tool name match metric value for an instance." }, "GoogleCloudAiplatformV1beta1CsvDestination": { "properties": { "gcsDestination": { "description": "Required. Google Cloud Storage location.", "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" } }, "description": "The storage details for CSV output content.", "id": "GoogleCloudAiplatformV1beta1CsvDestination", "type": "object" }, "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigThresholdConfig": { "id": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigThresholdConfig", "type": "object", "description": "The config for Featurestore Monitoring threshold.", "properties": { "value": { "type": "number", "format": "double", "description": "Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature." } } }, "GoogleCloudAiplatformV1beta1FeatureOnlineStoreDedicatedServingEndpoint": { "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreDedicatedServingEndpoint", "type": "object", "properties": { "publicEndpointDomainName": { "description": "Output only. This field will be populated with the domain name to use for this FeatureOnlineStore", "readOnly": true, "type": "string" }, "serviceAttachment": { "type": "string", "readOnly": true, "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled and after FeatureViewSync is created." }, "privateServiceConnectConfig": { "description": "Optional. Private service connect config. The private service connection is available only for Optimized storage type, not for embedding management now. If PrivateServiceConnectConfig.enable_private_service_connect set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint.", "$ref": "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig" } }, "description": "The dedicated serving endpoint for this FeatureOnlineStore. Only need to set when you choose Optimized storage type. Public endpoint is provisioned by default." }, "GoogleCloudAiplatformV1beta1DeployedIndexRef": { "id": "GoogleCloudAiplatformV1beta1DeployedIndexRef", "type": "object", "properties": { "indexEndpoint": { "description": "Immutable. A resource name of the IndexEndpoint.", "type": "string" }, "deployedIndexId": { "description": "Immutable. The ID of the DeployedIndex in the above IndexEndpoint.", "type": "string" }, "displayName": { "description": "Output only. The display name of the DeployedIndex.", "readOnly": true, "type": "string" } }, "description": "Points to a DeployedIndex." }, "GoogleCloudAiplatformV1beta1MemoryRevision": { "properties": { "name": { "description": "Identifier. Represents the resource name of the Memory Revision. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}/revisions/{memory_revision}`", "type": "string" }, "fact": { "description": "Output only. Represents the fact of the Memory Revision. This corresponds to the `fact` field of the parent Memory at the time of revision creation.", "type": "string", "readOnly": true }, "structuredData": { "description": "Output only. Represents the structured value of the memory at the time of revision creation.", "readOnly": true, "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "expireTime": { "format": "google-datetime", "description": "Output only. Represents the timestamp of when this resource is considered expired.", "readOnly": true, "type": "string" }, "labels": { "description": "Output only. Represents the labels of the Memory Revision. These labels are applied to the MemoryRevision when it is created based on `GenerateMemoriesRequest.revision_labels`.", "readOnly": true, "type": "object", "additionalProperties": { "type": "string" } }, "extractedMemories": { "description": "Output only. Represents the extracted memories from the source content before consolidation when the memory was updated via GenerateMemories. This information was used to modify an existing Memory via Consolidation.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1IntermediateExtractedMemory" } }, "createTime": { "description": "Output only. Represents the timestamp when this Memory Revision was created.", "format": "google-datetime", "type": "string", "readOnly": true } }, "description": "A revision of a Memory.", "id": "GoogleCloudAiplatformV1beta1MemoryRevision", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValueDistributionDataValue": { "description": "Summary statistics for a population of values.", "properties": { "distribution": { "description": "Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format.", "type": "any" }, "distributionDeviation": { "type": "number", "description": "Distribution distance deviation from the current dataset's statistics to baseline dataset's statistics. * For categorical feature, the distribution distance is calculated by L-inifinity norm or Jensen–Shannon divergence. * For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.", "format": "double" } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValueDistributionDataValue", "type": "object" }, "GoogleCloudAiplatformV1beta1Trial": { "properties": { "state": { "readOnly": true, "type": "string", "enumDescriptions": [ "The Trial state is unspecified.", "Indicates that a specific Trial has been requested, but it has not yet been suggested by the service.", "Indicates that the Trial has been suggested.", "Indicates that the Trial should stop according to the service.", "Indicates that the Trial is completed successfully.", "Indicates that the Trial should not be attempted again. The service will set a Trial to INFEASIBLE when it's done but missing the final_measurement." ], "enum": [ "STATE_UNSPECIFIED", "REQUESTED", "ACTIVE", "STOPPING", "SUCCEEDED", "INFEASIBLE" ], "description": "Output only. The detailed state of the Trial." }, "startTime": { "description": "Output only. Time when the Trial was started.", "format": "google-datetime", "type": "string", "readOnly": true }, "measurements": { "description": "Output only. A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_duration). These are used for early stopping computations.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Measurement" }, "readOnly": true }, "id": { "type": "string", "readOnly": true, "description": "Output only. The identifier of the Trial assigned by the service." }, "customJob": { "readOnly": true, "type": "string", "description": "Output only. The CustomJob name linked to the Trial. It's set for a HyperparameterTuningJob's Trial." }, "name": { "description": "Output only. Resource name of the Trial assigned by the service.", "type": "string", "readOnly": true }, "webAccessUris": { "description": "Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.", "type": "object", "additionalProperties": { "type": "string" }, "readOnly": true }, "parameters": { "description": "Output only. The parameters of the Trial.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrialParameter" }, "readOnly": true }, "finalMeasurement": { "description": "Output only. The final measurement containing the objective value.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1Measurement" }, "endTime": { "description": "Output only. Time when the Trial's status changed to `SUCCEEDED` or `INFEASIBLE`.", "format": "google-datetime", "type": "string", "readOnly": true }, "clientId": { "description": "Output only. The identifier of the client that originally requested this Trial. Each client is identified by a unique client_id. When a client asks for a suggestion, Vertex AI Vizier will assign it a Trial. The client should evaluate the Trial, complete it, and report back to Vertex AI Vizier. If suggestion is asked again by same client_id before the Trial is completed, the same Trial will be returned. Multiple clients with different client_ids can ask for suggestions simultaneously, each of them will get their own Trial.", "readOnly": true, "type": "string" }, "infeasibleReason": { "description": "Output only. A human readable string describing why the Trial is infeasible. This is set only if Trial state is `INFEASIBLE`.", "type": "string", "readOnly": true } }, "description": "A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.", "id": "GoogleCloudAiplatformV1beta1Trial", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateMemoriesRequest": { "id": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequest", "type": "object", "description": "Request message for MemoryBankService.GenerateMemories. Maximum size is 8 MB.", "properties": { "revisionExpireTime": { "type": "string", "format": "google-datetime", "description": "Optional. Timestamp of when the revision is considered expired. If not set, the memory revision will be kept until manually deleted." }, "revisionTtl": { "description": "Optional. The TTL for the revision. The expiration time is computed: now + TTL.", "format": "google-duration", "type": "string" }, "scope": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The scope of the memories that should be generated. Memories will be consolidated across memories with the same scope. Must be provided unless the scope is defined in the source content. If `scope` is provided, it will override the scope defined in the source content. Scope values cannot contain the wildcard character '*'." }, "metadata": { "description": "Optional. User-provided metadata for the generated memories. This is not generated by Memory Bank.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1MemoryMetadataValue" } }, "vertexSessionSource": { "description": "Defines a Vertex Session as the source content from which to generate memories.", "$ref": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestVertexSessionSource" }, "disableConsolidation": { "description": "Optional. If true, generated memories will not be consolidated with existing memories; all generated memories will be added as new memories regardless of whether they are duplicates of or contradictory to existing memories. By default, memory consolidation is enabled.", "type": "boolean" }, "allowedTopics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryTopicId" }, "description": "Optional. Restricts memory generation to a subset of memory topics." }, "directMemoriesSource": { "description": "Defines a direct source of memories that should be uploaded to Memory Bank. This is similar to `CreateMemory`, but it allows for consolidation between these new memories and existing memories for the same scope.", "$ref": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectMemoriesSource" }, "directContentsSource": { "description": "Defines a direct source of content as the source content from which to generate memories.", "$ref": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectContentsSource" }, "disableMemoryRevisions": { "description": "Optional. If true, no revisions will be created for this request.", "type": "boolean" }, "revisionLabels": { "description": "Optional. Labels to be applied to the generated memory revisions. For example, you can use this to label a revision with its data source.", "type": "object", "additionalProperties": { "type": "string" } }, "metadataMergeStrategy": { "type": "string", "enumDescriptions": [ "Unspecified metadata merge strategy. If unspecified, the default behavior is to overwrite existing metadata (`OVERWRITE`).", "Replace the metadata of the updated memories with the new metadata.", "Append new metadata to the existing metadata. If there are duplicate keys, the existing values will be overwritten.", "Restrict consolidation to memories that have exactly the same metadata as the request. If a memory doesn't have the same metadata, it is not eligible for consolidation." ], "enum": [ "METADATA_MERGE_STRATEGY_UNSPECIFIED", "OVERWRITE", "MERGE", "REQUIRE_EXACT_MATCH" ], "description": "Optional. The strategy to use when applying metadata to existing memories." } } }, "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfig": { "description": "The runtime config of a PipelineJob.", "properties": { "inputArtifacts": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigInputArtifact" }, "description": "The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact." }, "failurePolicy": { "description": "Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.", "enum": [ "PIPELINE_FAILURE_POLICY_UNSPECIFIED", "PIPELINE_FAILURE_POLICY_FAIL_SLOW", "PIPELINE_FAILURE_POLICY_FAIL_FAST" ], "type": "string", "enumDescriptions": [ "Default value, and follows fail slow behavior.", "Indicates that the pipeline should continue to run until all possible tasks have been scheduled and completed.", "Indicates that the pipeline should stop scheduling new tasks after a task has failed." ] }, "defaultRuntime": { "$ref": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigDefaultRuntime", "description": "Optional. The default runtime for the PipelineJob. If not set, Standard Vertex Custom Job(https://cloud.google.com/vertex-ai/docs/training/overview) is used as the runtime. If set, all pipeline tasks will run on the default runtime unless a task is a GCPC custom job component (https://cloud.google.com/vertex-ai/docs/pipelines/customjob-component) based task. If the task is based on a GCPC custom job component, it runs solely according to the component's configuration." }, "gcsOutputDirectory": { "description": "Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.", "type": "string" }, "parameters": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1Value" }, "deprecated": true, "description": "Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower." }, "parameterValues": { "type": "object", "additionalProperties": { "type": "any" }, "description": "The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL." } }, "id": "GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestFullExport": { "description": "Describes exporting all historical Feature values of all entities of the EntityType between [start_time, end_time].", "properties": { "endTime": { "format": "google-datetime", "description": "Exports Feature values as of this timestamp. If not set, retrieve values as of now. Timestamp, if present, must not have higher than millisecond precision.", "type": "string" }, "startTime": { "type": "string", "description": "Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision.", "format": "google-datetime" } }, "id": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestFullExport", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaVisualInspectionMaskSavedQueryMetadata": { "properties": {}, "id": "GoogleCloudAiplatformV1beta1SchemaVisualInspectionMaskSavedQueryMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelArmorConfig": { "id": "GoogleCloudAiplatformV1beta1ModelArmorConfig", "type": "object", "description": "Configuration for Model Armor. Model Armor is a Google Cloud service that provides safety and security filtering for prompts and responses. It helps protect your AI applications from risks such as harmful content, sensitive data leakage, and prompt injection attacks.", "properties": { "promptTemplateName": { "description": "Optional. The resource name of the Model Armor template to use for prompt screening. A Model Armor template is a set of customized filters and thresholds that define how Model Armor screens content. If specified, Model Armor will use this template to check the user's prompt for safety and security risks before it is sent to the model. The name must be in the format `projects/{project}/locations/{location}/templates/{template}`.", "type": "string" }, "responseTemplateName": { "description": "Optional. The resource name of the Model Armor template to use for response screening. A Model Armor template is a set of customized filters and thresholds that define how Model Armor screens content. If specified, Model Armor will use this template to check the model's response for safety and security risks before it is returned to the user. The name must be in the format `projects/{project}/locations/{location}/templates/{template}`.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1StudySpecMedianAutomatedStoppingSpec": { "description": "The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement.", "properties": { "useElapsedDuration": { "description": "True if median automated stopping rule applies on Measurement.elapsed_duration. It means that elapsed_duration field of latest measurement of current Trial is used to compute median objective value for each completed Trials.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1StudySpecMedianAutomatedStoppingSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetail": { "description": "Represent the execution details of the job.", "properties": { "targetDatasets": { "description": "Processed target datasets.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetailProcessedDataset" } }, "baselineDatasets": { "description": "Processed baseline datasets.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetailProcessedDataset" } }, "objectiveStatus": { "type": "object", "additionalProperties": { "$ref": "GoogleRpcStatus" }, "description": "Status of data processing for each monitoring objective. Key is the objective." }, "error": { "description": "Additional job error status.", "$ref": "GoogleRpcStatus" } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetail", "type": "object" }, "GoogleCloudAiplatformV1beta1DatasetDistributionDistributionBucket": { "description": "Dataset bucket used to create a histogram for the distribution given a population of values.", "properties": { "right": { "readOnly": true, "type": "number", "format": "double", "description": "Output only. Right bound of the bucket." }, "left": { "type": "number", "readOnly": true, "description": "Output only. Left bound of the bucket.", "format": "double" }, "count": { "description": "Output only. Number of values in the bucket.", "format": "int64", "type": "string", "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1DatasetDistributionDistributionBucket", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsRequest": { "description": "Request message for ModelMonitoringService.SearchModelMonitoringStats.", "properties": { "statsFilter": { "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilter", "description": "Filter for search different stats." }, "pageToken": { "description": "A page token received from a previous ModelMonitoringService.SearchModelMonitoringStats call.", "type": "string" }, "timeInterval": { "$ref": "GoogleTypeInterval", "description": "The time interval for which results should be returned." }, "pageSize": { "type": "integer", "description": "The standard list page size.", "format": "int32" } }, "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1RagVectorDbConfig": { "properties": { "apiAuth": { "$ref": "GoogleCloudAiplatformV1beta1ApiAuth", "description": "Authentication config for the chosen Vector DB." }, "vertexFeatureStore": { "description": "The config for the Vertex Feature Store.", "$ref": "GoogleCloudAiplatformV1beta1RagVectorDbConfigVertexFeatureStore" }, "ragManagedDb": { "$ref": "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDb", "description": "The config for the RAG-managed Vector DB." }, "vertexVectorSearch": { "description": "The config for the Vertex Vector Search.", "$ref": "GoogleCloudAiplatformV1beta1RagVectorDbConfigVertexVectorSearch" }, "ragManagedVertexVectorSearch": { "$ref": "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedVertexVectorSearch", "description": "The config for the RAG-managed Vertex Vector Search 2.0." }, "pinecone": { "$ref": "GoogleCloudAiplatformV1beta1RagVectorDbConfigPinecone", "description": "The config for the Pinecone." }, "weaviate": { "$ref": "GoogleCloudAiplatformV1beta1RagVectorDbConfigWeaviate", "description": "The config for the Weaviate." }, "ragEmbeddingModelConfig": { "$ref": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfig", "description": "Optional. Immutable. The embedding model config of the Vector DB." } }, "description": "Config for the Vector DB to use for RAG.", "id": "GoogleCloudAiplatformV1beta1RagVectorDbConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformation", "type": "object", "properties": { "numeric": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation" }, "categorical": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation" }, "timestamp": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation" }, "text": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation" }, "auto": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation" } } }, "GoogleCloudAiplatformV1beta1TrajectoryRecallMetricValue": { "id": "GoogleCloudAiplatformV1beta1TrajectoryRecallMetricValue", "type": "object", "description": "TrajectoryRecall metric value for an instance.", "properties": { "score": { "description": "Output only. TrajectoryRecall score.", "format": "float", "type": "number", "readOnly": true } } }, "GoogleCloudAiplatformV1beta1MemoryProfile": { "id": "GoogleCloudAiplatformV1beta1MemoryProfile", "type": "object", "description": "A memory profile.", "properties": { "schemaId": { "description": "Represents the ID of the schema. This ID corresponds to the `schema_id` defined inside the SchemaConfig, under StructuredMemoryCustomizationConfig.", "type": "string" }, "profile": { "description": "Represents the profile data.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "GoogleCloudAiplatformV1beta1GenerationConfigModelConfig": { "description": "Config for model selection.", "properties": { "featureSelectionPreference": { "description": "Required. Feature selection preference.", "enum": [ "FEATURE_SELECTION_PREFERENCE_UNSPECIFIED", "PRIORITIZE_QUALITY", "BALANCED", "PRIORITIZE_COST" ], "type": "string", "enumDescriptions": [ "Unspecified feature selection preference.", "Prefer higher quality over lower cost.", "Balanced feature selection preference.", "Prefer lower cost over higher quality." ] } }, "id": "GoogleCloudAiplatformV1beta1GenerationConfigModelConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1DeploymentResourcePool": { "id": "GoogleCloudAiplatformV1beta1DeploymentResourcePool", "type": "object", "description": "A description of resources that can be shared by multiple DeployedModels, whose underlying specification consists of a DedicatedResources.", "properties": { "satisfiesPzi": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" }, "serviceAccount": { "description": "The service account that the DeploymentResourcePool's container(s) run as. Specify the email address of the service account. If this service account is not specified, the container(s) run as a service account that doesn't have access to the resource project. Users deploying the Models to this DeploymentResourcePool must have the `iam.serviceAccounts.actAs` permission on this service account.", "type": "string" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this DeploymentResourcePool was created." }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key spec for a DeploymentResourcePool. If set, this DeploymentResourcePool will be secured by this key. Endpoints and the DeploymentResourcePool they deploy in need to have the same EncryptionSpec." }, "satisfiesPzs": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "dedicatedResources": { "description": "Required. The underlying DedicatedResources that the DeploymentResourcePool uses.", "$ref": "GoogleCloudAiplatformV1beta1DedicatedResources" }, "disableContainerLogging": { "description": "If the DeploymentResourcePool is deployed with custom-trained Models or AutoML Tabular Models, the container(s) of the DeploymentResourcePool will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.", "type": "boolean" }, "name": { "description": "Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ResumeModelDeploymentMonitoringJobRequest": { "id": "GoogleCloudAiplatformV1beta1ResumeModelDeploymentMonitoringJobRequest", "type": "object", "description": "Request message for JobService.ResumeModelDeploymentMonitoringJob.", "properties": {} }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecAgentConfigSource": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecAgentConfigSource", "type": "object", "description": "Specification for the deploying from agent config.", "properties": { "adkConfig": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecAgentConfigSourceAdkConfig", "description": "Required. The ADK configuration." }, "inlineSource": { "description": "Optional. Any additional files needed to interpret the config. If a `requirements.txt` file is present in the `inline_source`, the corresponding packages will be installed. If no `requirements.txt` file is present in `inline_source`, then the latest version of `google-adk` will be installed for interpreting the ADK config.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecInlineSource" } } }, "GoogleCloudAiplatformV1beta1RollbackMemoryRequest": { "properties": { "targetRevisionId": { "type": "string", "format": "int64", "description": "Required. The ID of the revision to rollback to." } }, "description": "Request message for MemoryBankService.RollbackMemory.", "id": "GoogleCloudAiplatformV1beta1RollbackMemoryRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1FunctionResponse": { "id": "GoogleCloudAiplatformV1beta1FunctionResponse", "type": "object", "properties": { "scheduling": { "type": "string", "enumDescriptions": [ "This value is unused.", "Only add the result to the conversation context, do not interrupt or trigger generation.", "Add the result to the conversation context, and prompt to generate output without interrupting ongoing generation.", "Add the result to the conversation context, interrupt ongoing generation and prompt to generate output." ], "description": "Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.", "enum": [ "SCHEDULING_UNSPECIFIED", "SILENT", "WHEN_IDLE", "INTERRUPT" ] }, "name": { "description": "Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.", "type": "string" }, "parts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FunctionResponsePart" }, "description": "Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types." }, "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Required. The function response in JSON object format. Use \"output\" key to specify function output and \"error\" key to specify error details (if any). If \"output\" and \"error\" keys are not specified, then whole \"response\" is treated as function output." }, "id": { "description": "Optional. The id of the function call this response is for. Populated by the client to match the corresponding function call `id`.", "type": "string" } }, "description": "The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction." }, "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextClassificationPredictionInstance": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextClassificationPredictionInstance", "type": "object", "description": "Prediction input format for Text Classification.", "properties": { "content": { "description": "The text snippet to make the predictions on.", "type": "string" }, "mimeType": { "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain", "type": "string" } } }, "GoogleIamV1GetPolicyOptions": { "id": "GoogleIamV1GetPolicyOptions", "type": "object", "description": "Encapsulates settings provided to GetIamPolicy.", "properties": { "requestedPolicyVersion": { "type": "integer", "format": "int32", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies)." } } }, "GoogleCloudAiplatformV1beta1RebootPersistentResourceOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1RebootPersistentResourceOperationMetadata", "type": "object", "description": "Details of operations that perform reboot PersistentResource.", "properties": { "progressMessage": { "description": "Progress Message for Reboot LRO", "type": "string" }, "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for PersistentResource." } } }, "GoogleCloudAiplatformV1beta1UndeployIndexResponse": { "description": "Response message for IndexEndpointService.UndeployIndex.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1UndeployIndexResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1TokensInfo": { "id": "GoogleCloudAiplatformV1beta1TokensInfo", "type": "object", "description": "Tokens info with a list of tokens and the corresponding list of token ids.", "properties": { "tokens": { "type": "array", "items": { "type": "string", "format": "byte" }, "description": "A list of tokens from the input." }, "tokenIds": { "type": "array", "items": { "format": "int64", "type": "string" }, "description": "A list of token ids from the input." }, "role": { "description": "Optional. Optional fields for the role from the corresponding Content.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessSpec": { "id": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessSpec", "type": "object", "properties": { "version": { "format": "int32", "description": "Optional. Which version to use for evaluation.", "type": "integer" }, "useReference": { "description": "Optional. Whether to use instance.reference to compute summarization helpfulness.", "type": "boolean" } }, "description": "Spec for summarization helpfulness score metric." }, "GoogleCloudAiplatformV1beta1ListMemoryRevisionsResponse": { "id": "GoogleCloudAiplatformV1beta1ListMemoryRevisionsResponse", "type": "object", "description": "Response message for MemoryBankService.ListMemoryRevisions.", "properties": { "memoryRevisions": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryRevision" }, "description": "The list of Memory Revisions in the request page." }, "nextPageToken": { "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1RuntimeConfigVertexAISearchRuntimeConfig": { "id": "GoogleCloudAiplatformV1beta1RuntimeConfigVertexAISearchRuntimeConfig", "type": "object", "properties": { "servingConfigName": { "description": "Optional. Vertex AI Search serving config name. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}/servingConfigs/{serving_config}`", "type": "string" }, "engineId": { "description": "Optional. Vertex AI Search engine ID. This is used to construct the search request. By setting this engine_id, API will construct the serving config using the default value to call search API for the user. The engine_id and serving_config_name cannot both be empty at the same time.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseMetricValue": { "id": "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseMetricValue", "type": "object", "properties": { "score": { "format": "float", "description": "Output only. TrajectorySingleToolUse score.", "readOnly": true, "type": "number" } }, "description": "TrajectorySingleToolUse metric value for an instance." }, "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateResponse": { "id": "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateResponse", "type": "object", "properties": { "shouldStop": { "description": "True if the Trial should stop.", "type": "boolean" } }, "description": "Response message for VizierService.CheckTrialEarlyStoppingState." }, "GoogleCloudAiplatformV1beta1UndeployModelResponse": { "id": "GoogleCloudAiplatformV1beta1UndeployModelResponse", "type": "object", "description": "Response message for EndpointService.UndeployModel.", "properties": {} }, "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessResult": { "description": "Spec for summarization helpfulness result.", "properties": { "explanation": { "description": "Output only. Explanation for summarization helpfulness score.", "type": "string", "readOnly": true }, "confidence": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Confidence for summarization helpfulness score." }, "score": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Summarization Helpfulness score." } }, "id": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessResult", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec": { "properties": { "maxTrialCount": { "format": "int32", "description": "The desired total number of Trials.", "type": "integer" }, "studySpec": { "description": "Study configuration of the HyperparameterTuningJob.", "$ref": "GoogleCloudAiplatformV1beta1StudySpec" }, "parallelTrialCount": { "description": "The desired number of Trials to run in parallel.", "format": "int32", "type": "integer" }, "maxFailedTrialCount": { "description": "The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.", "format": "int32", "type": "integer" }, "trialJobSpec": { "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec", "description": "The spec of a trial job. The same spec applies to the CustomJobs created in all the trials." } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringScheduleConfig": { "id": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringScheduleConfig", "type": "object", "properties": { "monitorInterval": { "description": "Required. The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered.", "format": "google-duration", "type": "string" }, "monitorWindow": { "type": "string", "format": "google-duration", "description": "The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics." } }, "description": "The config for scheduling monitoring job." }, "GoogleCloudAiplatformV1beta1GenerateLossClustersRequestEvaluationResultList": { "properties": { "evaluationResults": { "description": "Required. The list of evaluation results to analyze.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationResult" } } }, "description": "A wrapper to allow providing a list of items inline.", "id": "GoogleCloudAiplatformV1beta1GenerateLossClustersRequestEvaluationResultList", "type": "object" }, "GoogleCloudAiplatformV1beta1UpsertExamplesResponseUpsertResult": { "properties": { "example": { "description": "The example created/updated successfully.", "$ref": "GoogleCloudAiplatformV1beta1Example" }, "status": { "$ref": "GoogleRpcStatus", "description": "The error message of the example that was not created/updated successfully." } }, "description": "The result for creating/updating a single example.", "id": "GoogleCloudAiplatformV1beta1UpsertExamplesResponseUpsertResult", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateUserScenariosResponse": { "properties": { "userScenarios": { "description": "The generated user scenarios used to simulate multi-turn agent running results and agent evaluation.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1UserScenario" } } }, "description": "Response message for DataFoundryService.GenerateUserScenarios.", "id": "GoogleCloudAiplatformV1beta1GenerateUserScenariosResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1PipelineTaskDetail": { "properties": { "startTime": { "type": "string", "readOnly": true, "description": "Output only. Task start time.", "format": "google-datetime" }, "state": { "enum": [ "STATE_UNSPECIFIED", "PENDING", "RUNNING", "SUCCEEDED", "CANCEL_PENDING", "CANCELLING", "CANCELLED", "FAILED", "SKIPPED", "NOT_TRIGGERED" ], "description": "Output only. State of the task.", "readOnly": true, "type": "string", "enumDescriptions": [ "Unspecified.", "Specifies pending state for the task.", "Specifies task is being executed.", "Specifies task completed successfully.", "Specifies Task cancel is in pending state.", "Specifies task is being cancelled.", "Specifies task was cancelled.", "Specifies task failed.", "Specifies task was skipped due to cache hit.", "Specifies that the task was not triggered because the task's trigger policy is not satisfied. The trigger policy is specified in the `condition` field of PipelineJob.pipeline_spec." ] }, "outputs": { "readOnly": true, "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList" }, "description": "Output only. The runtime output artifacts of the task." }, "taskId": { "type": "string", "readOnly": true, "description": "Output only. The system generated ID of the task.", "format": "int64" }, "parentTaskId": { "format": "int64", "description": "Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.", "readOnly": true, "type": "string" }, "executorDetail": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetail", "description": "Output only. The detailed execution info." }, "taskName": { "description": "Output only. The user specified name of the task that is defined in pipeline_spec.", "type": "string", "readOnly": true }, "pipelineTaskStatus": { "description": "Output only. A list of task status. This field keeps a record of task status evolving over time.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskDetailPipelineTaskStatus" }, "readOnly": true }, "taskUniqueName": { "readOnly": true, "type": "string", "description": "Output only. The unique name of a task. This field is used by rerun pipeline job. Console UI and Vertex AI SDK will support triggering pipeline job reruns. The name is constructed by concatenating all the parent tasks name with the task name. For example, if a task named \"child_task\" has a parent task named \"parent_task_1\" and parent task 1 has a parent task named \"parent_task_2\", the task unique name will be \"parent_task_2.parent_task_1.child_task\"." }, "inputs": { "description": "Output only. The runtime input artifacts of the task.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList" }, "readOnly": true }, "error": { "description": "Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "execution": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1Execution", "description": "Output only. The execution metadata of the task." }, "endTime": { "type": "string", "readOnly": true, "description": "Output only. Task end time.", "format": "google-datetime" }, "createTime": { "format": "google-datetime", "description": "Output only. Task create time.", "readOnly": true, "type": "string" } }, "description": "The runtime detail of a task execution.", "id": "GoogleCloudAiplatformV1beta1PipelineTaskDetail", "type": "object" }, "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequestFeatureSpec": { "id": "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequestFeatureSpec", "type": "object", "properties": { "id": { "description": "Required. ID of the Feature to import values of. This Feature must exist in the target EntityType, or the request will fail.", "type": "string" }, "sourceField": { "description": "Source column to get the Feature values from. If not set, uses the column with the same name as the Feature ID.", "type": "string" } }, "description": "Defines the Feature value(s) to import." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomTask": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomTask", "type": "object", "properties": { "inputs": { "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec", "description": "The input parameters of this CustomTask." }, "metadata": { "description": "The metadata information.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomJobMetadata" } }, "description": "A TrainingJob that trains a custom code Model." }, "GoogleCloudAiplatformV1beta1SummarizationQualityInput": { "id": "GoogleCloudAiplatformV1beta1SummarizationQualityInput", "type": "object", "properties": { "instance": { "description": "Required. Summarization quality instance.", "$ref": "GoogleCloudAiplatformV1beta1SummarizationQualityInstance" }, "metricSpec": { "description": "Required. Spec for summarization quality score metric.", "$ref": "GoogleCloudAiplatformV1beta1SummarizationQualitySpec" } }, "description": "Input for summarization quality metric." }, "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfig": { "description": "Configuration for importing data from an external source.", "properties": { "bigQuerySourceConfig": { "description": "Configuration for importing data from a BigQuery table.", "$ref": "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigBigQuerySourceConfig" } }, "id": "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployDeployMetadata": { "properties": { "sampleRequest": { "description": "Optional. Sample request for deployed endpoint.", "type": "string" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. Labels for the deployment config. For managing deployment config like verifying, source of deployment config, etc." } }, "description": "Metadata information about the deployment for managing deployment config.", "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployDeployMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1NearestNeighborQueryStringFilter": { "description": "String filter is used to search a subset of the entities by using boolean rules on string columns. For example: if a query specifies string filter with 'name = color, allow_tokens = {red, blue}, deny_tokens = {purple}',' then that query will match entities that are red or blue, but if those points are also purple, then they will be excluded even if they are red/blue. Only string filter is supported for now, numeric filter will be supported in the near future.", "properties": { "allowTokens": { "description": "Optional. The allowed tokens.", "type": "array", "items": { "type": "string" } }, "name": { "description": "Required. Column names in BigQuery that used as filters.", "type": "string" }, "denyTokens": { "type": "array", "items": { "type": "string" }, "description": "Optional. The denied tokens." } }, "id": "GoogleCloudAiplatformV1beta1NearestNeighborQueryStringFilter", "type": "object" }, "GoogleCloudAiplatformV1beta1CoherenceResult": { "description": "Spec for coherence result.", "properties": { "explanation": { "type": "string", "readOnly": true, "description": "Output only. Explanation for coherence score." }, "confidence": { "format": "float", "description": "Output only. Confidence for coherence score.", "readOnly": true, "type": "number" }, "score": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Coherence score." } }, "id": "GoogleCloudAiplatformV1beta1CoherenceResult", "type": "object" }, "GoogleCloudAiplatformV1beta1AppendEventResponse": { "id": "GoogleCloudAiplatformV1beta1AppendEventResponse", "type": "object", "properties": {}, "description": "Response message for SessionService.AppendEvent." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation", "type": "object", "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Tokenize text to words. Convert each words to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean. * Tokenization is based on unicode script boundaries. * Missing values get their own lookup index and resulting embedding. * Stop-words receive no special treatment and are not removed.", "properties": { "columnName": { "type": "string" } } }, "GoogleCloudAiplatformV1beta1Trajectory": { "id": "GoogleCloudAiplatformV1beta1Trajectory", "type": "object", "description": "Spec for trajectory.", "properties": { "toolCalls": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ToolCall" }, "description": "Required. Tool calls in the trajectory." } } }, "GoogleCloudAiplatformV1beta1SyntheticField": { "properties": { "fieldName": { "description": "Optional. The name of the specific field, such as \"product_name\" or \"review_text\".", "type": "string" }, "content": { "description": "Required. The actual content or value for this field. This can be text, images, or other types of data.", "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "description": "Represents a single named field within a synthetic example, consisting of a name and the actual content.", "id": "GoogleCloudAiplatformV1beta1SyntheticField", "type": "object" }, "GoogleCloudAiplatformV1beta1AssessDataRequestBatchPredictionResourceUsageAssessmentConfig": { "description": "Configuration for the batch prediction resource usage assessment.", "properties": { "modelName": { "description": "Required. The name of the model used for batch prediction.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1AssessDataRequestBatchPredictionResourceUsageAssessmentConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1TuningJobMetadata": { "id": "GoogleCloudAiplatformV1beta1TuningJobMetadata", "type": "object", "properties": { "completedEpochCount": { "description": "Output only. The number of epochs that have been completed.", "format": "int64", "type": "string", "readOnly": true }, "completedStepCount": { "readOnly": true, "type": "string", "format": "int64", "description": "Output only. The number of steps that have been completed. Set for Multi-Step RL." } }, "description": "Tuning job metadata." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs", "type": "object", "properties": { "modelType": { "type": "string", "enumDescriptions": [ "Should not be set.", "A Model best tailored to be used within Google Cloud, and which cannot be exported. Default.", "A model type best tailored to be used within Google Cloud, which cannot be exported externally. Compared to the CLOUD model above, it is expected to have higher prediction accuracy.", "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models.", "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device with afterwards.", "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other mobile models.", "EfficientNet model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", "MaxViT model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", "ViT model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally.", "CoCa model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally." ], "enum": [ "MODEL_TYPE_UNSPECIFIED", "CLOUD", "CLOUD_1", "MOBILE_TF_LOW_LATENCY_1", "MOBILE_TF_VERSATILE_1", "MOBILE_TF_HIGH_ACCURACY_1", "EFFICIENTNET", "MAXVIT", "VIT", "COCA" ] }, "tunableParameter": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter", "description": "Trainer type for Vision TrainRequest." }, "budgetMilliNodeHours": { "description": "The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType `cloud`(default), the budget must be between 8,000 and 800,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time, considering 8 nodes are used. For model types `mobile-tf-low-latency-1`, `mobile-tf-versatile-1`, `mobile-tf-high-accuracy-1`, the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used.", "format": "int64", "type": "string" }, "disableEarlyStopping": { "description": "Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Classification might stop training before the entire training budget has been used.", "type": "boolean" }, "baseModelId": { "description": "The ID of the `base` model. If it is specified, the new model will be trained based on the `base` model. Otherwise, the new model will be trained from scratch. The `base` model must be in the same Project and Location as the new Model to train, and have the same modelType.", "type": "string" }, "uptrainBaseModelId": { "description": "The ID of `base` model for upTraining. If it is specified, the new model will be upTrained based on the `base` model for upTraining. Otherwise, the new model will be trained from scratch. The `base` model for upTraining must be in the same Project and Location as the new Model to train, and have the same modelType.", "type": "string" }, "multiLabel": { "description": "If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable). If true, a multi-label Model will be trained (i.e. assuming that for each image multiple annotations may be applicable).", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1CancelHyperparameterTuningJobRequest": { "description": "Request message for JobService.CancelHyperparameterTuningJob.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1CancelHyperparameterTuningJobRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1WriteFeatureValuesRequest": { "id": "GoogleCloudAiplatformV1beta1WriteFeatureValuesRequest", "type": "object", "description": "Request message for FeaturestoreOnlineServingService.WriteFeatureValues.", "properties": { "payloads": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1WriteFeatureValuesPayload" }, "description": "Required. The entities to be written. Up to 100,000 feature values can be written across all `payloads`." } } }, "GoogleCloudAiplatformV1beta1ExportFractionSplit": { "id": "GoogleCloudAiplatformV1beta1ExportFractionSplit", "type": "object", "properties": { "trainingFraction": { "format": "double", "description": "The fraction of the input data that is to be used to train the Model.", "type": "number" }, "validationFraction": { "type": "number", "description": "The fraction of the input data that is to be used to validate the Model.", "format": "double" }, "testFraction": { "format": "double", "description": "The fraction of the input data that is to be used to evaluate the Model.", "type": "number" } }, "description": "Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test." }, "GoogleCloudAiplatformV1beta1StudySpecMetricSpecSafetyMetricConfig": { "id": "GoogleCloudAiplatformV1beta1StudySpecMetricSpecSafetyMetricConfig", "type": "object", "description": "Used in safe optimization to specify threshold levels and risk tolerance.", "properties": { "desiredMinSafeTrialsFraction": { "description": "Desired minimum fraction of safe trials (over total number of trials) that should be targeted by the algorithm at any time during the study (best effort). This should be between 0.0 and 1.0 and a value of 0.0 means that there is no minimum and an algorithm proceeds without targeting any specific fraction. A value of 1.0 means that the algorithm attempts to only Suggest safe Trials.", "format": "double", "type": "number" }, "safetyThreshold": { "format": "double", "description": "Safety threshold (boundary value between safe and unsafe). NOTE that if you leave SafetyMetricConfig unset, a default value of 0 will be used.", "type": "number" } } }, "GoogleCloudAiplatformV1beta1LustreMount": { "description": "Represents a mount configuration for Lustre file system.", "properties": { "instanceIp": { "description": "Required. IP address of the Lustre instance.", "type": "string" }, "mountPoint": { "description": "Required. Destination mount path. The Lustre file system will be mounted for the user under /mnt/lustre/", "type": "string" }, "volumeHandle": { "description": "Required. The unique identifier of the Lustre volume.", "type": "string" }, "filesystem": { "description": "Required. The name of the Lustre filesystem.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1LustreMount", "type": "object" }, "GoogleCloudAiplatformV1beta1UserActionReference": { "properties": { "operation": { "description": "For API calls that return a long running operation. Resource name of the long running operation. Format: `projects/{project}/locations/{location}/operations/{operation}`", "type": "string" }, "method": { "description": "The method name of the API RPC call. For example, \"/google.cloud.aiplatform.{apiVersion}.DatasetService.CreateDataset\"", "type": "string" }, "dataLabelingJob": { "description": "For API calls that start a LabelingJob. Resource name of the LabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", "type": "string" } }, "description": "References an API call. It contains more information about long running operation and Jobs that are triggered by the API call.", "id": "GoogleCloudAiplatformV1beta1UserActionReference", "type": "object" }, "GoogleCloudAiplatformV1beta1AutomaticResources": { "id": "GoogleCloudAiplatformV1beta1AutomaticResources", "type": "object", "description": "A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines.", "properties": { "minReplicaCount": { "type": "integer", "description": "Immutable. The minimum number of replicas that will be always deployed on. If traffic against it increases, it may dynamically be deployed onto more replicas up to max_replica_count, and as traffic decreases, some of these extra replicas may be freed. If the requested value is too large, the deployment will error.", "format": "int32" }, "maxReplicaCount": { "type": "integer", "description": "Immutable. The maximum number of replicas that may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale to that many replicas is guaranteed (barring service outages). If traffic increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, a no upper bound for scaling under heavy traffic will be assume, though Vertex AI may be unable to scale beyond certain replica number.", "format": "int32" } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringTabularStats": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringTabularStats", "type": "object", "properties": { "statsName": { "description": "The stats name.", "type": "string" }, "objectiveType": { "description": "One of the supported monitoring objectives: `raw-feature-drift` `prediction-output-drift` `feature-attribution`", "type": "string" }, "dataPoints": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPoint" }, "description": "The data points of this time series. When listing time series, points are returned in reverse time order." } }, "description": "A collection of data points that describes the time-varying values of a tabular metric." }, "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessSpec": { "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessSpec", "type": "object", "properties": { "useReference": { "description": "Optional. Whether to use instance.reference to compute question answering helpfulness.", "type": "boolean" }, "version": { "description": "Optional. Which version to use for evaluation.", "format": "int32", "type": "integer" } }, "description": "Spec for question answering helpfulness metric." }, "GoogleCloudAiplatformV1beta1BatchDeleteRagMetadataRequest": { "id": "GoogleCloudAiplatformV1beta1BatchDeleteRagMetadataRequest", "type": "object", "properties": { "names": { "description": "Required. The RagMetadata to delete. A maximum of 500 rag metadata can be deleted in a batch.", "type": "array", "items": { "type": "string" } } }, "description": "Request message for VertexRagDataService.BatchDeleteRagMetadata." }, "GoogleCloudAiplatformV1beta1MigratableResourceAutomlDataset": { "id": "GoogleCloudAiplatformV1beta1MigratableResourceAutomlDataset", "type": "object", "properties": { "dataset": { "description": "Full resource name of automl Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`.", "type": "string" }, "datasetDisplayName": { "description": "The Dataset's display name in automl.googleapis.com.", "type": "string" } }, "description": "Represents one Dataset in automl.googleapis.com." }, "GoogleCloudAiplatformV1beta1TimeSeriesData": { "properties": { "tensorboardTimeSeriesId": { "description": "Required. The ID of the TensorboardTimeSeries, which will become the final component of the TensorboardTimeSeries' resource name", "type": "string" }, "valueType": { "description": "Required. Immutable. The value type of this time series. All the values in this time series data must match this value type.", "enum": [ "VALUE_TYPE_UNSPECIFIED", "SCALAR", "TENSOR", "BLOB_SEQUENCE" ], "type": "string", "enumDescriptions": [ "The value type is unspecified.", "Used for TensorboardTimeSeries that is a list of scalars. E.g. accuracy of a model over epochs/time.", "Used for TensorboardTimeSeries that is a list of tensors. E.g. histograms of weights of layer in a model over epoch/time.", "Used for TensorboardTimeSeries that is a list of blob sequences. E.g. set of sample images with labels over epochs/time." ] }, "values": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TimeSeriesDataPoint" }, "description": "Required. Data points in this time series." } }, "description": "All the data stored in a TensorboardTimeSeries.", "id": "GoogleCloudAiplatformV1beta1TimeSeriesData", "type": "object" }, "GoogleCloudAiplatformV1beta1SafetyRating": { "id": "GoogleCloudAiplatformV1beta1SafetyRating", "type": "object", "properties": { "overwrittenThreshold": { "enum": [ "HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF" ], "description": "Output only. The overwritten threshold for the safety category of Gemini 2.0 image out. If minors are detected in the output image, the threshold of each safety category will be overwritten if user sets a lower threshold.", "readOnly": true, "type": "string", "enumDescriptions": [ "The harm block threshold is unspecified.", "Block content with a low harm probability or higher.", "Block content with a medium harm probability or higher.", "Block content with a high harm probability.", "Do not block any content, regardless of its harm probability.", "Turn off the safety filter entirely." ] }, "blocked": { "description": "Output only. Indicates whether the content was blocked because of this rating.", "readOnly": true, "type": "boolean" }, "probability": { "readOnly": true, "type": "string", "enumDescriptions": [ "The harm probability is unspecified.", "The harm probability is negligible.", "The harm probability is low.", "The harm probability is medium.", "The harm probability is high." ], "enum": [ "HARM_PROBABILITY_UNSPECIFIED", "NEGLIGIBLE", "LOW", "MEDIUM", "HIGH" ], "description": "Output only. The probability of harm for this category." }, "probabilityScore": { "type": "number", "readOnly": true, "description": "Output only. The probability score of harm for this category.", "format": "float" }, "category": { "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "Content that promotes violence or incites hatred against individuals or groups based on certain attributes.", "Content that promotes, facilitates, or enables dangerous activities.", "Abusive, threatening, or content intended to bully, torment, or ridicule.", "Content that contains sexually explicit material.", "Deprecated: Election filter is not longer supported. The harm category is civic integrity.", "Images that contain hate speech.", "Images that contain dangerous content.", "Images that contain harassment.", "Images that contain sexually explicit content.", "Prompts designed to bypass safety filters." ], "enumDeprecated": [ false, false, false, false, false, true, false, false, false, false, false ], "readOnly": true, "description": "Output only. The harm category of this rating.", "enum": [ "HARM_CATEGORY_UNSPECIFIED", "HARM_CATEGORY_HATE_SPEECH", "HARM_CATEGORY_DANGEROUS_CONTENT", "HARM_CATEGORY_HARASSMENT", "HARM_CATEGORY_SEXUALLY_EXPLICIT", "HARM_CATEGORY_CIVIC_INTEGRITY", "HARM_CATEGORY_IMAGE_HATE", "HARM_CATEGORY_IMAGE_DANGEROUS_CONTENT", "HARM_CATEGORY_IMAGE_HARASSMENT", "HARM_CATEGORY_IMAGE_SEXUALLY_EXPLICIT", "HARM_CATEGORY_JAILBREAK" ] }, "severityScore": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. The severity score of harm for this category." }, "severity": { "type": "string", "enumDescriptions": [ "The harm severity is unspecified.", "The harm severity is negligible.", "The harm severity is low.", "The harm severity is medium.", "The harm severity is high." ], "readOnly": true, "description": "Output only. The severity of harm for this category.", "enum": [ "HARM_SEVERITY_UNSPECIFIED", "HARM_SEVERITY_NEGLIGIBLE", "HARM_SEVERITY_LOW", "HARM_SEVERITY_MEDIUM", "HARM_SEVERITY_HIGH" ] } }, "description": "A safety rating for a piece of content. The safety rating contains the harm category and the harm probability level." }, "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataRequest": { "id": "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataRequest", "type": "object", "description": "Request message for TensorboardService.WriteTensorboardRunData.", "properties": { "tensorboardRun": { "description": "Required. The resource name of the TensorboardRun to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", "type": "string" }, "timeSeriesData": { "description": "Required. The TensorboardTimeSeries data to write. Values with in a time series are indexed by their step value. Repeated writes to the same step will overwrite the existing value for that step. The upper limit of data points per write request is 5000.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TimeSeriesData" } } } }, "GoogleCloudAiplatformV1beta1GenerateVideoResponseVideo": { "id": "GoogleCloudAiplatformV1beta1GenerateVideoResponseVideo", "type": "object", "properties": { "bytesBase64Encoded": { "description": "Base64 encoded bytes string representing the video.", "type": "string" }, "mimeType": { "description": "The MIME type of the content of the video. - video/mp4", "type": "string" }, "gcsUri": { "description": "Cloud Storage URI where the generated video is written.", "type": "string" } }, "description": "A generated video." }, "GoogleCloudAiplatformV1beta1NearestNeighborQuery": { "id": "GoogleCloudAiplatformV1beta1NearestNeighborQuery", "type": "object", "description": "A query to find a number of similar entities.", "properties": { "entityId": { "description": "Optional. The entity id whose similar entities should be searched for. If embedding is set, search will use embedding instead of entity_id.", "type": "string" }, "perCrowdingAttributeNeighborCount": { "type": "integer", "description": "Optional. Crowding is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than sper_crowding_attribute_neighbor_count of the k neighbors returned have the same value of crowding_attribute. It's used for improving result diversity.", "format": "int32" }, "parameters": { "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborQueryParameters", "description": "Optional. Parameters that can be set to tune query on the fly." }, "neighborCount": { "type": "integer", "description": "Optional. The number of similar entities to be retrieved from feature view for each query.", "format": "int32" }, "embedding": { "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborQueryEmbedding", "description": "Optional. The embedding vector that be used for similar search." }, "stringFilters": { "description": "Optional. The list of string filters.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborQueryStringFilter" } }, "numericFilters": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborQueryNumericFilter" }, "description": "Optional. The list of numeric filters." } } }, "GoogleCloudAiplatformV1beta1EvaluationConfig": { "properties": { "autoraterConfig": { "$ref": "GoogleCloudAiplatformV1beta1AutoraterConfig", "description": "Optional. Autorater config for evaluation." }, "outputConfig": { "description": "Required. Config for evaluation output.", "$ref": "GoogleCloudAiplatformV1beta1OutputConfig" }, "metrics": { "description": "Required. The metrics used for evaluation.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Metric" } }, "inferenceGenerationConfig": { "description": "Optional. Configuration options for inference generation and outputs. If not set, default generation parameters are used.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig" }, "datasetCustomMetrics": { "description": "Optional. Specifications for custom dataset-level aggregations.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DatasetCustomMetric" } } }, "description": "Evaluation Config for Tuning Job.", "id": "GoogleCloudAiplatformV1beta1EvaluationConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectContentsSource": { "properties": { "events": { "description": "Required. The source content (i.e. chat history) to generate memories from.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectContentsSourceEvent" } } }, "description": "Defines a direct source of content from which to generate the memories.", "id": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectContentsSource", "type": "object" }, "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStore": { "description": "The data source for Vertex RagStore.", "properties": { "ragCorpora": { "deprecated": true, "type": "array", "items": { "type": "string" }, "description": "Optional. Deprecated. Please use rag_resources to specify the data source." }, "ragResources": { "description": "Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStoreRagResource" } }, "vectorDistanceThreshold": { "type": "number", "deprecated": true, "description": "Optional. Only return contexts with vector distance smaller than the threshold.", "format": "double" } }, "id": "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStore", "type": "object" }, "GoogleCloudAiplatformV1beta1QueryExtensionResponse": { "properties": { "steps": { "description": "Steps of extension or LLM interaction, can contain function call, function response, or text response. The last step contains the final response to the query.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "failureMessage": { "description": "Failure message if any.", "type": "string" } }, "description": "Response message for ExtensionExecutionService.QueryExtension.", "id": "GoogleCloudAiplatformV1beta1QueryExtensionResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1FluencySpec": { "id": "GoogleCloudAiplatformV1beta1FluencySpec", "type": "object", "description": "Spec for fluency score metric.", "properties": { "version": { "type": "integer", "format": "int32", "description": "Optional. Which version to use for evaluation." } } }, "GoogleCloudAiplatformV1beta1FeatureViewDataKeyCompositeKey": { "description": "ID that is comprised from several parts (columns).", "properties": { "parts": { "description": "Parts to construct Entity ID. Should match with the same ID columns as defined in FeatureView in the same order.", "type": "array", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1beta1FeatureViewDataKeyCompositeKey", "type": "object" }, "GoogleCloudAiplatformV1beta1WriteFeatureValuesResponse": { "id": "GoogleCloudAiplatformV1beta1WriteFeatureValuesResponse", "type": "object", "properties": {}, "description": "Response message for FeaturestoreOnlineServingService.WriteFeatureValues." }, "GoogleCloudAiplatformV1beta1PurgeArtifactsResponse": { "description": "Response message for MetadataService.PurgeArtifacts.", "properties": { "purgeCount": { "type": "string", "description": "The number of Artifacts that this request deleted (or, if `force` is false, the number of Artifacts that will be deleted). This can be an estimate.", "format": "int64" }, "purgeSample": { "description": "A sample of the Artifact names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer).", "type": "array", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1beta1PurgeArtifactsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1MutateDeployedModelOperationMetadata": { "description": "Runtime operation information for EndpointService.MutateDeployedModel.", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1beta1MutateDeployedModelOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective": { "id": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective", "type": "object", "description": "Stats requested for specific objective.", "properties": { "type": { "type": "string", "enumDescriptions": [ "Default value, should not be set.", "Raw feature values' stats to detect skew between Training-Prediction datasets.", "Raw feature values' stats to detect drift between Serving-Prediction datasets.", "Feature attribution scores to detect skew between Training-Prediction datasets.", "Feature attribution scores to detect skew between Prediction datasets collected within different time windows." ], "enum": [ "MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_TYPE_UNSPECIFIED", "RAW_FEATURE_SKEW", "RAW_FEATURE_DRIFT", "FEATURE_ATTRIBUTION_SKEW", "FEATURE_ATTRIBUTION_DRIFT" ] }, "topFeatureCount": { "description": "If set, all attribution scores between SearchModelDeploymentMonitoringStatsAnomaliesRequest.start_time and SearchModelDeploymentMonitoringStatsAnomaliesRequest.end_time are fetched, and page token doesn't take effect in this case. Only used to retrieve attribution score for the top Features which has the highest attribution score in the latest monitoring run.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingSpec": { "id": "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingSpec", "type": "object", "description": "Spec for RubricBasedInstructionFollowing metric - returns rubrics and verdicts corresponding to rubrics along with overall score.", "properties": {} }, "GoogleCloudAiplatformV1beta1CustomCodeExecutionResult": { "id": "GoogleCloudAiplatformV1beta1CustomCodeExecutionResult", "type": "object", "description": "Result for custom code execution metric.", "properties": { "score": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Custom code execution score." } } }, "GoogleCloudAiplatformV1beta1ListModelEvaluationsResponse": { "properties": { "modelEvaluations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluation" }, "description": "List of ModelEvaluations in the requested page." }, "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListModelEvaluationsRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for ModelService.ListModelEvaluations.", "id": "GoogleCloudAiplatformV1beta1ListModelEvaluationsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolGoogleSearchWebSearch": { "description": "Standard web search for grounding and related configurations. Only text results are returned.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearchWebSearch", "type": "object" }, "GoogleCloudAiplatformV1beta1PipelineTemplateMetadata": { "id": "GoogleCloudAiplatformV1beta1PipelineTemplateMetadata", "type": "object", "properties": { "version": { "description": "The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is \"sha256:abcdef123456...\".", "type": "string" } }, "description": "Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry." }, "GoogleCloudAiplatformV1beta1RagEngineConfig": { "id": "GoogleCloudAiplatformV1beta1RagEngineConfig", "type": "object", "description": "Config for RagEngine.", "properties": { "name": { "description": "Identifier. The name of the RagEngineConfig. Format: `projects/{project}/locations/{location}/ragEngineConfig`", "type": "string" }, "ragManagedDbConfig": { "$ref": "GoogleCloudAiplatformV1beta1RagManagedDbConfig", "description": "The config of the RagManagedDb used by RagEngine." } } }, "GoogleCloudAiplatformV1beta1Feature": { "description": "Feature Metadata information. For example, color is a feature that describes an apple.", "properties": { "name": { "description": "Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.", "type": "string" }, "valueType": { "type": "string", "enumDescriptions": [ "The value type is unspecified.", "Used for Feature that is a boolean.", "Used for Feature that is a list of boolean.", "Used for Feature that is double.", "Used for Feature that is a list of double.", "Used for Feature that is INT64.", "Used for Feature that is a list of INT64.", "Used for Feature that is string.", "Used for Feature that is a list of String.", "Used for Feature that is bytes.", "Used for Feature that is struct." ], "description": "Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.", "enum": [ "VALUE_TYPE_UNSPECIFIED", "BOOL", "BOOL_ARRAY", "DOUBLE", "DOUBLE_ARRAY", "INT64", "INT64_ARRAY", "STRING", "STRING_ARRAY", "BYTES", "STRUCT" ] }, "versionColumnName": { "description": "Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View column hosting data for this version. If no value is provided, will use feature_id.", "type": "string" }, "monitoringStatsAnomalies": { "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureMonitoringStatsAnomaly" }, "readOnly": true }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." }, "featureStatsAndAnomaly": { "description": "Output only. Only applicable for Vertex AI Feature Store. The list of historical stats and anomalies.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureStatsAndAnomaly" } }, "disableMonitoring": { "description": "Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.", "type": "boolean" }, "updateTime": { "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.", "format": "google-datetime", "type": "string", "readOnly": true }, "etag": { "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "createTime": { "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "description": { "description": "Description of the Feature.", "type": "string" }, "monitoringConfig": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfig", "description": "Optional. Only applicable for Vertex AI Feature Store (Legacy). Deprecated: The custom monitoring configuration for this Feature, if not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If this is populated with FeaturestoreMonitoringConfig.disabled = true, snapshot analysis monitoring is disabled; if FeaturestoreMonitoringConfig.monitoring_interval specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring config is same as the EntityType's this Feature belongs to." }, "pointOfContact": { "description": "Entity responsible for maintaining this feature. Can be comma separated list of email addresses or URIs.", "type": "string" }, "monitoringStats": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly" }, "readOnly": true, "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). A list of historical SnapshotAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending." } }, "id": "GoogleCloudAiplatformV1beta1Feature", "type": "object" }, "GoogleIamV1SetIamPolicyRequest": { "properties": { "policy": { "description": "REQUIRED: The complete policy to be applied to the `resource`. The size of the policy is limited to a few 10s of KB. An empty policy is a valid policy but certain Google Cloud services (such as Projects) might reject them.", "$ref": "GoogleIamV1Policy" } }, "description": "Request message for `SetIamPolicy` method.", "id": "GoogleIamV1SetIamPolicyRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethod": { "properties": { "lastEntry": { "$ref": "GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethodLastEntry", "description": "Use only the last entry of the conversation history (`contents_example.contents`) as the search key." } }, "description": "Options for generating the search key from the conversation history.", "id": "GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethod", "type": "object" }, "GoogleCloudAiplatformV1beta1ExportPublisherModelRequest": { "id": "GoogleCloudAiplatformV1beta1ExportPublisherModelRequest", "type": "object", "properties": { "destination": { "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", "description": "Required. The target where we are exporting the model weights to" } }, "description": "Request message for ModelGardenService.ExportPublisherModel." }, "GoogleCloudAiplatformV1beta1StreamRawPredictRequest": { "id": "GoogleCloudAiplatformV1beta1StreamRawPredictRequest", "type": "object", "description": "Request message for PredictionService.StreamRawPredict.", "properties": { "httpBody": { "$ref": "GoogleApiHttpBody", "description": "The prediction input. Supports HTTP headers and arbitrary data payload." } } }, "GoogleCloudAiplatformV1beta1ExportModelResponse": { "properties": {}, "description": "Response message of ModelService.ExportModel operation.", "id": "GoogleCloudAiplatformV1beta1ExportModelResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringSpec": { "description": "Monitoring monitoring job spec. It outlines the specifications for monitoring objectives, notifications, and result exports.", "properties": { "notificationSpec": { "description": "The model monitoring notification spec.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpec" }, "objectiveSpec": { "description": "The monitoring objective spec.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpec" }, "outputSpec": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringOutputSpec", "description": "The Output destination spec for metrics, error logs, etc." } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitoringSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ListRagMetadataResponse": { "description": "Response message for VertexRagDataService.ListRagMetadata.", "properties": { "ragMetadata": { "description": "List of RagMetadata in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RagMetadata" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListRagMetadataRequest.page_token to obtain that page.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListRagMetadataResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ListCachedContentsResponse": { "description": "Response with a list of CachedContents.", "properties": { "cachedContents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1CachedContent" }, "description": "List of cached contents." }, "nextPageToken": { "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListCachedContentsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1AssignNotebookRuntimeRequest": { "properties": { "notebookRuntime": { "description": "Required. Provide runtime specific information (e.g. runtime owner, notebook id) used for NotebookRuntime assignment.", "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntime" }, "notebookRuntimeId": { "description": "Optional. User specified ID for the notebook runtime.", "type": "string" }, "notebookRuntimeTemplate": { "description": "Required. The resource name of the NotebookRuntimeTemplate based on which a NotebookRuntime will be assigned (reuse or create a new one).", "type": "string" } }, "description": "Request message for NotebookService.AssignNotebookRuntime.", "id": "GoogleCloudAiplatformV1beta1AssignNotebookRuntimeRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics": { "properties": { "confidenceThreshold": { "type": "number", "format": "float", "description": "Metrics are computed with an assumption that the Model never returns predictions with score lower than this value." }, "precision": { "type": "number", "format": "float", "description": "Precision for the given confidence threshold." }, "f1Score": { "format": "float", "description": "The harmonic mean of recall and precision.", "type": "number" }, "recall": { "format": "float", "description": "Recall (True Positive Rate) for the given confidence threshold.", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics", "type": "object" }, "GoogleCloudAiplatformV1beta1ListEntityTypesResponse": { "properties": { "entityTypes": { "description": "The EntityTypes matching the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EntityType" } }, "nextPageToken": { "description": "A token, which can be sent as ListEntityTypesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "description": "Response message for FeaturestoreService.ListEntityTypes.", "id": "GoogleCloudAiplatformV1beta1ListEntityTypesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1RetrieveMemoriesRequestSimilaritySearchParams": { "description": "Parameters for semantic similarity search based retrieval.", "properties": { "searchQuery": { "description": "Required. Query to use for similarity search retrieval. If provided, then the parent ReasoningEngine must have ReasoningEngineContextSpec.MemoryBankConfig.SimilaritySearchConfig set.", "type": "string" }, "topK": { "type": "integer", "format": "int32", "description": "Optional. The maximum number of memories to return. The service may return fewer than this value. If unspecified, at most 3 memories will be returned. The maximum value is 100; values above 100 will be coerced to 100." } }, "id": "GoogleCloudAiplatformV1beta1RetrieveMemoriesRequestSimilaritySearchParams", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly": { "description": "Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.", "properties": { "distributionDeviation": { "type": "number", "format": "double", "description": "Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence." }, "anomalyUri": { "description": "Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).", "type": "string" }, "anomalyDetectionThreshold": { "format": "double", "description": "This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.", "type": "number" }, "startTime": { "format": "google-datetime", "description": "The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).", "type": "string" }, "statsUri": { "description": "Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message [tensorflow.metadata.v0.FeatureNameStatistics](https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/statistics.proto).", "type": "string" }, "endTime": { "type": "string", "description": "The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).", "format": "google-datetime" }, "score": { "type": "number", "format": "double", "description": "Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT." } }, "id": "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly", "type": "object" }, "GoogleCloudAiplatformV1beta1UserScenarioGenerationConfig": { "properties": { "userScenarioCount": { "type": "string", "format": "int64", "description": "Required. The number of user scenarios to generate. The maximum number of scenarios that can be generated is 100." }, "simulationInstruction": { "description": "Optional. Simulation instruction to guide the user scenario generation.", "type": "string" }, "environmentData": { "description": "Optional. Environment data in string type.", "type": "string" }, "modelName": { "description": "Optional. The model name to use for generation. It can be model name, e.g. \"gemini-3-pro-preview\". or the fully qualified name of the publisher model or endpoint. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string" } }, "description": "User scenario generation configuration.", "id": "GoogleCloudAiplatformV1beta1UserScenarioGenerationConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPromptInstancePromptExecution": { "id": "GoogleCloudAiplatformV1beta1SchemaPromptInstancePromptExecution", "type": "object", "description": "A prompt instance's parameters set that contains a set of variable values.", "properties": { "arguments": { "description": "Maps variable names to their value.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptInstanceVariableValue" } } } }, "GoogleCloudAiplatformV1beta1IndexStats": { "id": "GoogleCloudAiplatformV1beta1IndexStats", "type": "object", "properties": { "vectorsCount": { "type": "string", "readOnly": true, "description": "Output only. The number of dense vectors in the Index.", "format": "int64" }, "sparseVectorsCount": { "description": "Output only. The number of sparse vectors in the Index.", "format": "int64", "type": "string", "readOnly": true }, "shardsCount": { "format": "int32", "description": "Output only. The number of shards in the Index.", "readOnly": true, "type": "integer" } }, "description": "Stats of the Index." }, "GoogleCloudAiplatformV1beta1SummarizationQualityInstance": { "id": "GoogleCloudAiplatformV1beta1SummarizationQualityInstance", "type": "object", "properties": { "context": { "description": "Required. Text to be summarized.", "type": "string" }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "instruction": { "description": "Required. Summarization prompt for LLM.", "type": "string" }, "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" } }, "description": "Spec for summarization quality instance." }, "GoogleCloudAiplatformV1beta1Annotation": { "id": "GoogleCloudAiplatformV1beta1Annotation", "type": "object", "properties": { "payload": { "description": "Required. The schema of the payload can be found in payload_schema.", "type": "any" }, "annotationSource": { "description": "Output only. The source of the Annotation.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1UserActionReference" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The labels with user-defined metadata to organize your Annotations. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Annotation(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for each Annotation: * \"aiplatform.googleapis.com/annotation_set_name\": optional, name of the UI's annotation set this Annotation belongs to. If not set, the Annotation is not visible in the UI. * \"aiplatform.googleapis.com/payload_schema\": output only, its value is the payload_schema's title." }, "name": { "type": "string", "readOnly": true, "description": "Output only. Resource name of the Annotation." }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this Annotation was last updated.", "format": "google-datetime" }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "payloadSchemaUri": { "description": "Required. Google Cloud Storage URI points to a YAML file describing payload. The schema is defined as an [OpenAPI 3.0.2 Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/, note that the chosen schema must be consistent with the parent Dataset's metadata.", "type": "string" }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when this Annotation was created.", "readOnly": true, "type": "string" } }, "description": "Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem." }, "GoogleCloudAiplatformV1beta1FileData": { "id": "GoogleCloudAiplatformV1beta1FileData", "type": "object", "description": "URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage.", "properties": { "displayName": { "description": "Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.", "type": "string" }, "fileUri": { "description": "Required. The URI of the file in Google Cloud Storage.", "type": "string" }, "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1AgentConfig": { "description": "Represents configuration for an Agent.", "properties": { "tools": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" }, "description": "Optional. The list of tools available to this agent." }, "subAgents": { "type": "array", "items": { "type": "string" }, "description": "Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology." }, "agentType": { "description": "Optional. The type or class of the agent (e.g., \"LlmAgent\", \"RouterAgent\", \"ToolUseAgent\"). Useful for the autorater to understand the expected behavior of the agent.", "type": "string" }, "instruction": { "description": "Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.", "type": "string" }, "description": { "description": "Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.", "type": "string" }, "agentId": { "description": "Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1AgentConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaImageClassificationAnnotation": { "id": "GoogleCloudAiplatformV1beta1SchemaImageClassificationAnnotation", "type": "object", "description": "Annotation details specific to image classification.", "properties": { "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1RagVectorDbConfigPinecone": { "id": "GoogleCloudAiplatformV1beta1RagVectorDbConfigPinecone", "type": "object", "description": "The config for the Pinecone.", "properties": { "indexName": { "description": "Pinecone index name. This value cannot be changed after it's set.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1HyperparameterTuningJob": { "description": "Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.", "properties": { "studySpec": { "$ref": "GoogleCloudAiplatformV1beta1StudySpec", "description": "Required. Study configuration of the HyperparameterTuningJob." }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "parallelTrialCount": { "type": "integer", "format": "int32", "description": "Required. The desired number of Trials to run in parallel." }, "satisfiesPzs": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "name": { "type": "string", "readOnly": true, "description": "Output only. Resource name of the HyperparameterTuningJob." }, "displayName": { "description": "Required. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "maxTrialCount": { "type": "integer", "description": "Required. The desired total number of Trials.", "format": "int32" }, "startTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the HyperparameterTuningJob for the first time entered the `JOB_STATE_RUNNING` state." }, "trialJobSpec": { "description": "Required. The spec of a trial job. The same spec applies to the CustomJobs created in all the trials.", "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec" }, "state": { "enum": [ "JOB_STATE_UNSPECIFIED", "JOB_STATE_QUEUED", "JOB_STATE_PENDING", "JOB_STATE_RUNNING", "JOB_STATE_SUCCEEDED", "JOB_STATE_FAILED", "JOB_STATE_CANCELLING", "JOB_STATE_CANCELLED", "JOB_STATE_PAUSED", "JOB_STATE_EXPIRED", "JOB_STATE_UPDATING", "JOB_STATE_PARTIALLY_SUCCEEDED" ], "description": "Output only. The detailed state of the job.", "readOnly": true, "type": "string", "enumDescriptions": [ "The job state is unspecified.", "The job has been just created or resumed and processing has not yet begun.", "The service is preparing to run the job.", "The job is in progress.", "The job completed successfully.", "The job failed.", "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "The job has been cancelled.", "The job has been stopped, and can be resumed.", "The job has expired.", "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", "The job is partially succeeded, some results may be missing due to errors." ] }, "maxFailedTrialCount": { "format": "int32", "description": "The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.", "type": "integer" }, "createTime": { "format": "google-datetime", "description": "Output only. Time when the HyperparameterTuningJob was created.", "readOnly": true, "type": "string" }, "updateTime": { "format": "google-datetime", "description": "Output only. Time when the HyperparameterTuningJob was most recently updated.", "readOnly": true, "type": "string" }, "error": { "description": "Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." }, "endTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the HyperparameterTuningJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`." }, "encryptionSpec": { "description": "Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key.", "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" }, "trials": { "description": "Output only. Trials of the HyperparameterTuningJob.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Trial" }, "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1HyperparameterTuningJob", "type": "object" }, "GoogleCloudAiplatformV1beta1PairwiseMetricResult": { "id": "GoogleCloudAiplatformV1beta1PairwiseMetricResult", "type": "object", "description": "Spec for pairwise metric result.", "properties": { "customOutput": { "description": "Output only. Spec for custom output.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1CustomOutput" }, "explanation": { "description": "Output only. Explanation for pairwise metric score.", "type": "string", "readOnly": true }, "pairwiseChoice": { "description": "Output only. Pairwise metric choice.", "enum": [ "PAIRWISE_CHOICE_UNSPECIFIED", "BASELINE", "CANDIDATE", "TIE" ], "type": "string", "enumDescriptions": [ "Unspecified prediction choice.", "Baseline prediction wins", "Candidate prediction wins", "Winner cannot be determined" ], "readOnly": true } } }, "GoogleCloudAiplatformV1beta1StoredContentsExampleParametersContentSearchKey": { "description": "The chat history to use to generate the search key for retrieval.", "properties": { "contents": { "description": "Required. The conversation for generating a search key.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "searchKeyGenerationMethod": { "description": "Required. The method of generating a search key.", "$ref": "GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethod" } }, "id": "GoogleCloudAiplatformV1beta1StoredContentsExampleParametersContentSearchKey", "type": "object" }, "GoogleCloudAiplatformV1beta1Citation": { "id": "GoogleCloudAiplatformV1beta1Citation", "type": "object", "description": "A citation for a piece of generatedcontent.", "properties": { "endIndex": { "format": "int32", "description": "Output only. The end index of the citation in the content.", "readOnly": true, "type": "integer" }, "title": { "type": "string", "readOnly": true, "description": "Output only. The title of the source of the citation." }, "uri": { "description": "Output only. The URI of the source of the citation.", "readOnly": true, "type": "string" }, "startIndex": { "description": "Output only. The start index of the citation in the content.", "format": "int32", "type": "integer", "readOnly": true }, "publicationDate": { "readOnly": true, "$ref": "GoogleTypeDate", "description": "Output only. The publication date of the source of the citation." }, "license": { "description": "Output only. The license of the source of the citation.", "type": "string", "readOnly": true } } }, "GoogleCloudAiplatformV1beta1NotebookExecutionJobDirectNotebookSource": { "id": "GoogleCloudAiplatformV1beta1NotebookExecutionJobDirectNotebookSource", "type": "object", "properties": { "content": { "type": "string", "description": "The base64-encoded contents of the input notebook file.", "format": "byte" } }, "description": "The content of the input notebook in ipynb format." }, "GoogleCloudAiplatformV1beta1GenAiAdvancedFeaturesConfig": { "id": "GoogleCloudAiplatformV1beta1GenAiAdvancedFeaturesConfig", "type": "object", "properties": { "ragConfig": { "description": "Configuration for Retrieval Augmented Generation feature.", "$ref": "GoogleCloudAiplatformV1beta1GenAiAdvancedFeaturesConfigRagConfig" } }, "description": "Configuration for GenAiAdvancedFeatures." }, "GoogleCloudAiplatformV1beta1EvaluationItem": { "id": "GoogleCloudAiplatformV1beta1EvaluationItem", "type": "object", "description": "EvaluationItem is a single evaluation request or result. The content of an EvaluationItem is immutable - it cannot be updated once created. EvaluationItems can be deleted when no longer needed.", "properties": { "displayName": { "description": "Required. The display name of the EvaluationItem.", "type": "string" }, "gcsUri": { "description": "The Cloud Storage object where the request or response is stored.", "type": "string" }, "evaluationRequest": { "description": "The request to evaluate.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRequest" }, "evaluationItemType": { "enum": [ "EVALUATION_ITEM_TYPE_UNSPECIFIED", "REQUEST", "RESULT" ], "description": "Required. The type of the EvaluationItem.", "type": "string", "enumDescriptions": [ "The default value. This value is unused.", "The EvaluationItem is a request to evaluate.", "The EvaluationItem is the result of evaluation." ] }, "createTime": { "description": "Output only. Timestamp when this item was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "evaluationResponse": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1EvaluationResult", "description": "Output only. The response from evaluation." }, "metadata": { "description": "Optional. Metadata for the EvaluationItem.", "type": "any" }, "labels": { "description": "Optional. Labels for the EvaluationItem.", "type": "object", "additionalProperties": { "type": "string" } }, "name": { "description": "Identifier. The resource name of the EvaluationItem. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}`", "type": "string" }, "error": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. Error for the evaluation item." } } }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationFileInputSource": { "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationFileInputSource", "type": "object", "properties": { "mimeType": { "description": "The file's mime type.", "type": "string" }, "content": { "description": "The file's contents.", "type": "string" }, "displayName": { "description": "The file's display name.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1FunctionCall": { "properties": { "willContinue": { "description": "Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.", "type": "boolean" }, "name": { "description": "Optional. The name of the function to call. Matches FunctionDeclaration.name.", "type": "string" }, "id": { "description": "Optional. The unique id of the function call. If populated, the client to execute the `function_call` and return the response with the matching `id`.", "type": "string" }, "args": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details." }, "partialArgs": { "description": "Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PartialArg" } } }, "description": "A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values.", "id": "GoogleCloudAiplatformV1beta1FunctionCall", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateFeatureOnlineStoreOperationMetadata": { "properties": { "genericMetadata": { "description": "Operation metadata for FeatureOnlineStore.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Details of operations that perform update FeatureOnlineStore.", "id": "GoogleCloudAiplatformV1beta1UpdateFeatureOnlineStoreOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringBigQuerySource": { "properties": { "query": { "description": "Standard SQL to be used instead of the `table_uri`.", "type": "string" }, "tableUri": { "description": "BigQuery URI to a table, up to 2000 characters long. All the columns in the table will be selected. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.", "type": "string" } }, "description": "Dataset spec for data sotred in BigQuery.", "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringBigQuerySource", "type": "object" }, "GoogleCloudAiplatformV1beta1DeployIndexOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1DeployIndexOperationMetadata", "type": "object", "description": "Runtime operation information for IndexEndpointService.DeployIndex.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The operation generic information." }, "deployedIndexId": { "description": "The unique index id specified by user", "type": "string" } } }, "GoogleCloudAiplatformV1beta1EmbedContentResponseEmbedding": { "properties": { "values": { "type": "array", "items": { "format": "float", "type": "number" }, "description": "Embedding vector values." } }, "description": "A list of floats representing an embedding.", "id": "GoogleCloudAiplatformV1beta1EmbedContentResponseEmbedding", "type": "object" }, "GoogleCloudAiplatformV1beta1IndexDatapointNumericRestriction": { "properties": { "namespace": { "description": "The namespace of this restriction. e.g.: cost.", "type": "string" }, "valueFloat": { "format": "float", "description": "Represents 32 bit float.", "type": "number" }, "op": { "description": "This MUST be specified for queries and must NOT be specified for datapoints.", "enum": [ "OPERATOR_UNSPECIFIED", "LESS", "LESS_EQUAL", "EQUAL", "GREATER_EQUAL", "GREATER", "NOT_EQUAL" ], "type": "string", "enumDescriptions": [ "Default value of the enum.", "Datapoints are eligible iff their value is \u003c the query's.", "Datapoints are eligible iff their value is \u003c= the query's.", "Datapoints are eligible iff their value is == the query's.", "Datapoints are eligible iff their value is \u003e= the query's.", "Datapoints are eligible iff their value is \u003e the query's.", "Datapoints are eligible iff their value is != the query's." ] }, "valueInt": { "description": "Represents 64 bit integer.", "format": "int64", "type": "string" }, "valueDouble": { "format": "double", "description": "Represents 64 bit float.", "type": "number" } }, "description": "This field allows restricts to be based on numeric comparisons rather than categorical tokens.", "id": "GoogleCloudAiplatformV1beta1IndexDatapointNumericRestriction", "type": "object" }, "GoogleCloudAiplatformV1beta1AssignNotebookRuntimeOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1AssignNotebookRuntimeOperationMetadata", "type": "object", "description": "Metadata information for NotebookService.AssignNotebookRuntime.", "properties": { "progressMessage": { "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime.", "type": "string" }, "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1beta1SchemaTextSentimentSavedQueryMetadata": { "description": "The metadata of SavedQuery contains TextSentiment Annotations.", "properties": { "sentimentMax": { "type": "integer", "format": "int32", "description": "The maximum sentiment of sentiment Anntoation in this SavedQuery." } }, "id": "GoogleCloudAiplatformV1beta1SchemaTextSentimentSavedQueryMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1MeasurementMetric": { "properties": { "metricId": { "description": "Output only. The ID of the Metric. The Metric should be defined in StudySpec's Metrics.", "type": "string", "readOnly": true }, "value": { "readOnly": true, "type": "number", "format": "double", "description": "Output only. The value for this metric." } }, "description": "A message representing a metric in the measurement.", "id": "GoogleCloudAiplatformV1beta1MeasurementMetric", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateDatasetOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateDatasetOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Runtime operation information for DatasetService.CreateDataset." }, "GoogleCloudAiplatformV1beta1RagFileParsingConfig": { "id": "GoogleCloudAiplatformV1beta1RagFileParsingConfig", "type": "object", "description": "Specifies the parsing config for RagFiles.", "properties": { "useAdvancedPdfParsing": { "description": "Whether to use advanced PDF parsing.", "deprecated": true, "type": "boolean" }, "layoutParser": { "$ref": "GoogleCloudAiplatformV1beta1RagFileParsingConfigLayoutParser", "description": "The Layout Parser to use for RagFiles." }, "llmParser": { "$ref": "GoogleCloudAiplatformV1beta1RagFileParsingConfigLlmParser", "description": "The LLM Parser to use for RagFiles." }, "advancedParser": { "$ref": "GoogleCloudAiplatformV1beta1RagFileParsingConfigAdvancedParser", "description": "The Advanced Parser to use for RagFiles." } } }, "GoogleCloudAiplatformV1beta1ListEventsResponse": { "id": "GoogleCloudAiplatformV1beta1ListEventsResponse", "type": "object", "properties": { "sessionEvents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SessionEvent" }, "description": "A list of events matching the request. Ordered by timestamp in ascending order." }, "nextPageToken": { "description": "A token, which can be sent as ListEventsRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages.", "type": "string" } }, "description": "Response message for SessionService.ListEvents." }, "GoogleCloudAiplatformV1beta1MemoryStructuredContent": { "id": "GoogleCloudAiplatformV1beta1MemoryStructuredContent", "type": "object", "properties": { "data": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Required. Represents the structured value of the memory." }, "schemaId": { "description": "Required. Represents the schema ID for which this structured memory belongs to.", "type": "string" } }, "description": "Represents the structured value of the memory." }, "GoogleCloudAiplatformV1beta1ToolGoogleSearchImageSearch": { "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearchImageSearch", "type": "object", "properties": {}, "description": "Image search for grounding and related configurations." }, "GoogleCloudAiplatformV1beta1ListEvaluationItemsResponse": { "properties": { "evaluationItems": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationItem" }, "description": "List of EvaluationItems in the requested page." }, "nextPageToken": { "description": "A token to retrieve the next page of results.", "type": "string" } }, "description": "Response message for EvaluationManagementService.ListEvaluationItems.", "id": "GoogleCloudAiplatformV1beta1ListEvaluationItemsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1CustomOutputFormatConfig": { "id": "GoogleCloudAiplatformV1beta1CustomOutputFormatConfig", "type": "object", "description": "Spec for custom output format configuration.", "properties": { "returnRawOutput": { "description": "Optional. Whether to return raw output.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1ListTensorboardExperimentsResponse": { "description": "Response message for TensorboardService.ListTensorboardExperiments.", "properties": { "nextPageToken": { "description": "A token, which can be sent as ListTensorboardExperimentsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" }, "tensorboardExperiments": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" }, "description": "The TensorboardExperiments mathching the request." } }, "id": "GoogleCloudAiplatformV1beta1ListTensorboardExperimentsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoObjectTrackingPredictionInstance": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoObjectTrackingPredictionInstance", "type": "object", "description": "Prediction input format for Video Object Tracking.", "properties": { "mimeType": { "description": "The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime", "type": "string" }, "timeSegmentEnd": { "description": "The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision, and \"inf\" or \"Infinity\" is allowed, which means the end of the video.", "type": "string" }, "timeSegmentStart": { "description": "The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision.", "type": "string" }, "content": { "description": "The Google Cloud Storage location of the video on which to perform the prediction.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1GenerateInstanceRubricsRequest": { "id": "GoogleCloudAiplatformV1beta1GenerateInstanceRubricsRequest", "type": "object", "properties": { "location": { "description": "Required. The resource name of the Location to generate rubrics from. Format: `projects/{project}/locations/{location}`", "type": "string" }, "rubricGenerationSpec": { "$ref": "GoogleCloudAiplatformV1beta1RubricGenerationSpec", "description": "Optional. Specification for how the rubrics should be generated." }, "agentConfig": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentConfig", "description": "Optional. Agent configuration, required for agent-based rubric generation." }, "predefinedRubricGenerationSpec": { "$ref": "GoogleCloudAiplatformV1beta1PredefinedMetricSpec", "description": "Optional. Specification for using the rubric generation configs of a pre-defined metric, e.g. \"generic_quality_v1\" and \"instruction_following_v1\". Some of the configs may be only used in rubric generation and not supporting evaluation, e.g. \"fully_customized_generic_quality_v1\". If this field is set, the `rubric_generation_spec` field will be ignored." }, "metricResourceName": { "description": "Optional. The resource name of a registered metric. Rubric generation using predefined metric spec or LLMBasedMetricSpec is supported. If this field is set, the configuration provided in this field is used for rubric generation. The `predefined_rubric_generation_spec` and `rubric_generation_spec` fields will be ignored.", "type": "string" }, "contents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "description": "Required. The prompt to generate rubrics from. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request." } }, "description": "Request message for EvaluationService.GenerateInstanceRubrics." }, "GoogleCloudAiplatformV1beta1RagQuery": { "id": "GoogleCloudAiplatformV1beta1RagQuery", "type": "object", "properties": { "similarityTopK": { "description": "Optional. The number of contexts to retrieve.", "format": "int32", "type": "integer", "deprecated": true }, "ragRetrievalConfig": { "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfig", "description": "Optional. The retrieval config for the query." }, "text": { "description": "Optional. The query in text format to get relevant contexts.", "type": "string" }, "ranking": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1RagQueryRanking", "description": "Optional. Configurations for hybrid search results ranking." } }, "description": "A query to retrieve relevant contexts." }, "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteResponse": { "id": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteResponse", "type": "object", "properties": { "writeResponses": { "description": "Details about write for each key. If status is not OK, WriteResponse.data_key will have the key with error, but WriteResponse.online_store_write_time will not be present.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteResponseWriteResponse" } }, "status": { "$ref": "GoogleRpcStatus", "description": "Response status for the keys listed in FeatureViewDirectWriteResponse.write_responses. The error only applies to the listed data keys - the stream will remain open for further FeatureOnlineStoreService.FeatureViewDirectWriteRequest requests. Partial failures (e.g. if the first 10 keys of a request fail, but the rest succeed) from a single request may result in multiple responses - there will be one response for the successful request keys and one response for the failing request keys." } }, "description": "Response message for FeatureOnlineStoreService.FeatureViewDirectWrite." }, "GoogleCloudAiplatformV1beta1PauseScheduleRequest": { "id": "GoogleCloudAiplatformV1beta1PauseScheduleRequest", "type": "object", "description": "Request message for ScheduleService.PauseSchedule.", "properties": {} }, "GoogleCloudAiplatformV1beta1CreateTensorboardTimeSeriesRequest": { "id": "GoogleCloudAiplatformV1beta1CreateTensorboardTimeSeriesRequest", "type": "object", "properties": { "parent": { "description": "Required. The resource name of the TensorboardRun to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", "type": "string" }, "tensorboardTimeSeriesId": { "description": "Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match \"a-z0-9{0, 127}\"", "type": "string" }, "tensorboardTimeSeries": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries", "description": "Required. The TensorboardTimeSeries to create." } }, "description": "Request message for TensorboardService.CreateTensorboardTimeSeries." }, "GoogleCloudAiplatformV1beta1UpsertExamplesRequest": { "description": "Request message for ExampleStoreService.UpsertExamples.", "properties": { "examples": { "description": "Required. A list of examples to be created/updated.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Example" } }, "overwrite": { "description": "Optional. A flag indicating whether an example can be overwritten if it already exists. If False (default) and the example already exists, the example will not be updated. This does not affect behavior if the example does not exist already.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1UpsertExamplesRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecPromptMessage": { "description": "The prompt message that aligns with the prompt message in google.cloud.aiplatform.master.GenerateContentRequest.", "properties": { "contents": { "description": "The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "tools": { "description": "A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" } }, "systemInstruction": { "description": "The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.", "$ref": "GoogleCloudAiplatformV1beta1Content" }, "generationConfig": { "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig", "description": "Generation config." }, "model": { "description": "The model name.", "type": "string" }, "safetySettings": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SafetySetting" }, "description": "Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates." }, "toolConfig": { "$ref": "GoogleCloudAiplatformV1beta1ToolConfig", "description": "Tool config. This config is shared for all tools provided in the request." } }, "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecPromptMessage", "type": "object" }, "GoogleCloudAiplatformV1beta1RubricCritiqueResult": { "id": "GoogleCloudAiplatformV1beta1RubricCritiqueResult", "type": "object", "description": "Rubric critique result.", "properties": { "verdict": { "readOnly": true, "type": "boolean", "description": "Output only. Verdict for the rubric - true if the rubric is met, false otherwise." }, "rubric": { "type": "string", "readOnly": true, "description": "Output only. Rubric to be evaluated." } } }, "GoogleCloudAiplatformV1beta1RemoveContextChildrenResponse": { "id": "GoogleCloudAiplatformV1beta1RemoveContextChildrenResponse", "type": "object", "properties": {}, "description": "Response message for MetadataService.RemoveContextChildren." }, "GoogleCloudAiplatformV1beta1KeepAliveProbeHttpGet": { "id": "GoogleCloudAiplatformV1beta1KeepAliveProbeHttpGet", "type": "object", "properties": { "path": { "description": "Required. Specifies the path of the HTTP GET request (e.g., `\"/is_busy\"`).", "type": "string" }, "port": { "type": "integer", "format": "int32", "description": "Optional. Specifies the port number on the container to which the request is sent." } }, "description": "Specifies the HTTP GET configuration for the probe." }, "GoogleCloudAiplatformV1beta1ProbeExecAction": { "properties": { "command": { "description": "Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy.", "type": "array", "items": { "type": "string" } } }, "description": "ExecAction specifies a command to execute.", "id": "GoogleCloudAiplatformV1beta1ProbeExecAction", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTextDataItem": { "description": "Payload of Text DataItem.", "properties": { "gcsUri": { "description": "Output only. Google Cloud Storage URI points to a copy of the original text in the Vertex-managed bucket in the user's project. The text file is up to 10MB in size.", "type": "string", "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1SchemaTextDataItem", "type": "object" }, "GoogleCloudAiplatformV1beta1DestinationFeatureSetting": { "properties": { "featureId": { "description": "Required. The ID of the Feature to apply the setting to.", "type": "string" }, "destinationField": { "description": "Specify the field name in the export destination. If not specified, Feature ID is used.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1DestinationFeatureSetting", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngine": { "properties": { "spec": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpec", "description": "Optional. Configurations of the ReasoningEngine" }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "description": { "description": "Optional. The description of the ReasoningEngine.", "type": "string" }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this ReasoningEngine was created.", "format": "google-datetime" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Labels for the ReasoningEngine." }, "trafficConfig": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfig", "description": "Optional. Traffic distribution configuration for the Reasoning Engine." }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this ReasoningEngine was most recently updated." }, "name": { "description": "Identifier. The resource name of the ReasoningEngine. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string" }, "displayName": { "description": "Required. The display name of the ReasoningEngine.", "type": "string" }, "contextSpec": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpec", "description": "Optional. Configuration for how Agent Engine sub-resources should manage context." }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key spec for a ReasoningEngine. If set, this ReasoningEngine and all sub-resources of this ReasoningEngine will be secured by this key." } }, "description": "ReasoningEngine provides a customizable runtime for models to determine which actions to take and in which order.", "id": "GoogleCloudAiplatformV1beta1ReasoningEngine", "type": "object" }, "GoogleCloudAiplatformV1beta1GeminiPreferenceExample": { "id": "GoogleCloudAiplatformV1beta1GeminiPreferenceExample", "type": "object", "description": "Input example for preference optimization.", "properties": { "contents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "description": "Multi-turn contents that represents the Prompt." }, "completions": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GeminiPreferenceExampleCompletion" }, "description": "List of completions for a given prompt." } } }, "GoogleCloudAiplatformV1beta1ToolParallelAiSearch": { "properties": { "apiKey": { "description": "Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.", "type": "string" }, "customConfigs": { "description": "Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { \"source_policy\": { \"include_domains\": [\"google.com\", \"wikipedia.org\"], \"exclude_domains\": [\"example.com\"] }, \"fetch_policy\": { \"max_age_seconds\": 3600 } }", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "description": "ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding.", "id": "GoogleCloudAiplatformV1beta1ToolParallelAiSearch", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchMetricValue": { "properties": { "score": { "format": "float", "description": "Output only. Tool parameter key match score.", "readOnly": true, "type": "number" } }, "description": "Tool parameter key match metric value for an instance.", "id": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchMetricValue", "type": "object" }, "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition": { "properties": { "values": { "description": "Required. Matches values of the parent parameter of 'CATEGORICAL' type. All values must exist in `categorical_value_spec` of parent parameter.", "type": "array", "items": { "type": "string" } } }, "description": "Represents the spec to match categorical values from parent parameter.", "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition", "type": "object" }, "GoogleCloudAiplatformV1beta1ContentsExample": { "id": "GoogleCloudAiplatformV1beta1ContentsExample", "type": "object", "description": "A single example of a conversation with the model.", "properties": { "expectedContents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ContentsExampleExpectedContent" }, "description": "Required. The expected output for the given `contents`. To represent multi-step reasoning, this is a repeated field that contains the iterative steps of the expected output." }, "contents": { "description": "Required. The content of the conversation with the model that resulted in the expected output.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } } } }, "CloudAiLargeModelsVisionImage": { "id": "CloudAiLargeModelsVisionImage", "type": "object", "description": "Image.", "properties": { "raiInfo": { "description": "RAI info for image.", "$ref": "CloudAiLargeModelsVisionRaiInfo" }, "text": { "description": "Text/Expanded text input for imagen.", "type": "string" }, "imageRaiScores": { "$ref": "CloudAiLargeModelsVisionImageRAIScores", "description": "RAI scores for generated image." }, "uri": { "description": "Path to another storage (typically Google Cloud Storage).", "type": "string" }, "semanticFilterResponse": { "$ref": "CloudAiLargeModelsVisionSemanticFilterResponse", "description": "Semantic filter info for image." }, "encoding": { "description": "Image encoding, encoded as \"image/png\" or \"image/jpg\".", "type": "string" }, "imageSize": { "description": "Image size. The size of the image. Can be self reported, or computed from the image bytes.", "$ref": "CloudAiLargeModelsVisionImageImageSize" }, "image": { "type": "string", "format": "byte", "description": "Raw bytes." }, "generationSeed": { "description": "Generation seed for the sampled image. This parameter is exposed to the user only if one of the following is true: 1. The user specified per-example seeds in the request. 2. The user doesn't specify the generation seed in the request.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1beta1PointwiseMetricSpec": { "id": "GoogleCloudAiplatformV1beta1PointwiseMetricSpec", "type": "object", "properties": { "metricPromptTemplate": { "description": "Required. Metric prompt template for pointwise metric.", "type": "string" }, "systemInstruction": { "description": "Optional. System instructions for pointwise metric.", "type": "string" }, "customOutputFormatConfig": { "description": "Optional. CustomOutputFormatConfig allows customization of metric output. By default, metrics return a score and explanation. When this config is set, the default output is replaced with either: - The raw output string. - A parsed output based on a user-defined schema. If a custom format is chosen, the `score` and `explanation` fields in the corresponding metric result will be empty.", "$ref": "GoogleCloudAiplatformV1beta1CustomOutputFormatConfig" } }, "description": "Spec for pointwise metric." }, "GoogleCloudAiplatformV1beta1PersistentResource": { "description": "Represents long-lasting resources that are dedicated to users to runs custom workloads. A PersistentResource can have multiple node pools and each node pool can have its own machine spec.", "properties": { "satisfiesPzi": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "name": { "description": "Immutable. Resource name of a PersistentResource.", "type": "string" }, "network": { "description": "Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to peered with Vertex AI to host the persistent resources. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the resources aren't peered with any network.", "type": "string" }, "displayName": { "description": "Optional. The display name of the PersistentResource. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "resourceRuntimeSpec": { "description": "Optional. Persistent Resource runtime spec. For example, used for Ray cluster configuration.", "$ref": "GoogleCloudAiplatformV1beta1ResourceRuntimeSpec" }, "startTime": { "format": "google-datetime", "description": "Output only. Time when the PersistentResource for the first time entered the `RUNNING` state.", "readOnly": true, "type": "string" }, "state": { "readOnly": true, "type": "string", "enumDescriptions": [ "Not set.", "The PROVISIONING state indicates the persistent resources is being created.", "The RUNNING state indicates the persistent resource is healthy and fully usable.", "The STOPPING state indicates the persistent resource is being deleted.", "The ERROR state indicates the persistent resource may be unusable. Details can be found in the `error` field.", "The REBOOTING state indicates the persistent resource is being rebooted (PR is not available right now but is expected to be ready again later).", "The UPDATING state indicates the persistent resource is being updated." ], "enum": [ "STATE_UNSPECIFIED", "PROVISIONING", "RUNNING", "STOPPING", "ERROR", "REBOOTING", "UPDATING" ], "description": "Output only. The detailed state of a Study." }, "pscInterfaceConfig": { "description": "Optional. Configuration for PSC-I for PersistentResource.", "$ref": "GoogleCloudAiplatformV1beta1PscInterfaceConfig" }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Time when the PersistentResource was created.", "format": "google-datetime" }, "updateTime": { "description": "Output only. Time when the PersistentResource was most recently updated.", "format": "google-datetime", "type": "string", "readOnly": true }, "error": { "description": "Output only. Only populated when persistent resource's state is `STOPPING` or `ERROR`.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "labels": { "description": "Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", "type": "object", "additionalProperties": { "type": "string" } }, "encryptionSpec": { "description": "Optional. Customer-managed encryption key spec for a PersistentResource. If set, this PersistentResource and all sub-resources of this PersistentResource will be secured by this key.", "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" }, "resourcePools": { "description": "Required. The spec of the pools of different resources.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ResourcePool" } }, "resourceRuntime": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ResourceRuntime", "description": "Output only. Runtime information of the Persistent Resource." }, "reservedIpRanges": { "type": "array", "items": { "type": "string" }, "description": "Optional. A list of names for the reserved IP ranges under the VPC network that can be used for this persistent resource. If set, we will deploy the persistent resource within the provided IP ranges. Otherwise, the persistent resource is deployed to any IP ranges under the provided VPC network. Example: ['vertex-ai-ip-range']." } }, "id": "GoogleCloudAiplatformV1beta1PersistentResource", "type": "object" }, "GoogleCloudAiplatformV1beta1NotebookEucConfig": { "id": "GoogleCloudAiplatformV1beta1NotebookEucConfig", "type": "object", "description": "The euc configuration of NotebookRuntimeTemplate.", "properties": { "bypassActasCheck": { "readOnly": true, "type": "boolean", "description": "Output only. Whether ActAs check is bypassed for service account attached to the VM. If false, we need ActAs check for the default Compute Engine Service account. When a Runtime is created, a VM is allocated using Default Compute Engine Service Account. Any user requesting to use this Runtime requires Service Account User (ActAs) permission over this SA. If true, Runtime owner is using EUC and does not require the above permission as VM no longer use default Compute Engine SA, but a P4SA." }, "eucDisabled": { "description": "Input only. Whether EUC is disabled in this NotebookRuntimeTemplate. In proto3, the default value of a boolean is false. In this way, by default EUC will be enabled for NotebookRuntimeTemplate.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1EvaluationPrompt": { "id": "GoogleCloudAiplatformV1beta1EvaluationPrompt", "type": "object", "description": "Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations.", "properties": { "text": { "description": "Text prompt.", "type": "string" }, "agentData": { "description": "Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This serves as the input context for agent scraping.", "$ref": "GoogleCloudAiplatformV1beta1AgentData" }, "userScenario": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationPromptUserScenario", "description": "Optional. The generated user scenario used to drive multi-turn agent running results." }, "value": { "description": "Fields and values that can be used to populate the prompt template.", "type": "any" }, "promptTemplateData": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationPromptPromptTemplateData", "description": "Prompt template data." } } }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateResourceRequirements": { "description": "Message to define resource requests and limits (mirroring Kubernetes) for each sandbox instance created from this template.", "properties": { "requests": { "description": "Optional. The requested amounts of compute resources. Keys are resource names (e.g., \"cpu\", \"memory\"). Values are quantities (e.g., \"250m\", \"512Mi\").", "type": "object", "additionalProperties": { "type": "string" } }, "limits": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The maximum amounts of compute resources allowed. Keys are resource names (e.g., \"cpu\", \"memory\"). Values are quantities (e.g., \"500m\", \"1Gi\")." } }, "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateResourceRequirements", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecMultimodalPrompt": { "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecMultimodalPrompt", "type": "object", "description": "Prompt variation that embeds preambles to prompt string.", "properties": { "promptMessage": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecPromptMessage", "description": "The prompt message." } } }, "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsRequest": { "properties": { "artifacts": { "type": "array", "items": { "type": "string" }, "description": "The resource names of the Artifacts to attribute to the Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`" }, "executions": { "description": "The resource names of the Executions to associate with the Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`", "type": "array", "items": { "type": "string" } } }, "description": "Request message for MetadataService.AddContextArtifactsAndExecutions.", "id": "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationResult": { "id": "GoogleCloudAiplatformV1beta1EvaluationResult", "type": "object", "properties": { "request": { "description": "Required. The request that was evaluated.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRequest" }, "metric": { "description": "Required. The metric that was evaluated.", "type": "string" }, "candidateResults": { "description": "Optional. The results for the metric.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1CandidateResult" } }, "evaluationRequest": { "description": "Required. The request item that was evaluated. Format: projects/{project}/locations/{location}/evaluationItems/{evaluation_item}", "type": "string" }, "evaluationRun": { "description": "Required. The evaluation run that was used to generate the result. Format: projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}", "type": "string" }, "metadata": { "description": "Optional. Metadata about the evaluation result.", "type": "any" } }, "description": "Evaluation result." }, "GoogleCloudAiplatformV1beta1BatchMigrateResourcesRequest": { "id": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesRequest", "type": "object", "description": "Request message for MigrationService.BatchMigrateResources.", "properties": { "migrateResourceRequests": { "description": "Required. The request messages specifying the resources to migrate. They must be in the same location as the destination. Up to 50 resources can be migrated in one batch.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequest" } } } }, "GoogleCloudAiplatformV1beta1CreateTensorboardRunRequest": { "properties": { "parent": { "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "type": "string" }, "tensorboardRun": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun", "description": "Required. The TensorboardRun to create." }, "tensorboardRunId": { "description": "Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.", "type": "string" } }, "description": "Request message for TensorboardService.CreateTensorboardRun.", "id": "GoogleCloudAiplatformV1beta1CreateTensorboardRunRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolParameterKVMatchMetricValue": { "id": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchMetricValue", "type": "object", "description": "Tool parameter key value match metric value for an instance.", "properties": { "score": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Tool parameter key value match score." } } }, "GoogleCloudAiplatformV1beta1AddTrialMeasurementRequest": { "properties": { "measurement": { "description": "Required. The measurement to be added to a Trial.", "$ref": "GoogleCloudAiplatformV1beta1Measurement" } }, "description": "Request message for VizierService.AddTrialMeasurement.", "id": "GoogleCloudAiplatformV1beta1AddTrialMeasurementRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics", "type": "object", "description": "Model evaluation metrics for text sentiment problems.", "properties": { "linearKappa": { "type": "number", "format": "float", "description": "Linear weighted kappa. Only set for ModelEvaluations, not for ModelEvaluationSlices." }, "quadraticKappa": { "type": "number", "description": "Quadratic weighted kappa. Only set for ModelEvaluations, not for ModelEvaluationSlices.", "format": "float" }, "precision": { "type": "number", "description": "Precision.", "format": "float" }, "recall": { "description": "Recall.", "format": "float", "type": "number" }, "meanSquaredError": { "format": "float", "description": "Mean squared error. Only set for ModelEvaluations, not for ModelEvaluationSlices.", "type": "number" }, "confusionMatrix": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix", "description": "Confusion matrix of the evaluation. Only set for ModelEvaluations, not for ModelEvaluationSlices." }, "meanAbsoluteError": { "format": "float", "description": "Mean absolute error. Only set for ModelEvaluations, not for ModelEvaluationSlices.", "type": "number" }, "f1Score": { "type": "number", "description": "The harmonic mean of recall and precision.", "format": "float" } } }, "GoogleCloudAiplatformV1beta1BatchPredictionJobInputConfig": { "id": "GoogleCloudAiplatformV1beta1BatchPredictionJobInputConfig", "type": "object", "properties": { "bigquerySource": { "description": "The BigQuery location of the input table. The schema of the table should be in the format described by the given context OpenAPI Schema, if one is provided. The table may contain additional columns that are not described by the schema, and they will be ignored.", "$ref": "GoogleCloudAiplatformV1beta1BigQuerySource" }, "instancesFormat": { "description": "Required. The format in which instances are given, must be one of the Model's supported_input_storage_formats.", "type": "string" }, "gcsSource": { "description": "The Cloud Storage location for the input instances.", "$ref": "GoogleCloudAiplatformV1beta1GcsSource" }, "vertexMultimodalDatasetSource": { "description": "A Vertex Managed Dataset. Currently, only datasets of type Multimodal are supported.", "$ref": "GoogleCloudAiplatformV1beta1VertexMultimodalDatasetSource" } }, "description": "Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them." }, "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest": { "id": "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest", "type": "object", "description": "Request message for PipelineService.BatchDeletePipelineJobs.", "properties": { "names": { "description": "Required. The names of the PipelineJobs to delete. A maximum of 32 PipelineJobs can be deleted in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}`", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized": { "description": "Optimized storage type", "properties": {}, "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized", "type": "object" }, "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDbANN": { "properties": { "treeDepth": { "format": "int32", "description": "The depth of the tree-based structure. Only depth values of 2 and 3 are supported. Recommended value is 2 if you have if you have O(10K) files in the RagCorpus and set this to 3 if more than that. Default value is 2.", "type": "integer" }, "leafCount": { "format": "int32", "description": "Number of leaf nodes in the tree-based structure. Each leaf node contains groups of closely related vectors along with their corresponding centroid. Recommended value is 10 * sqrt(num of RagFiles in your RagCorpus). Default value is 500.", "type": "integer" } }, "description": "Config for ANN search. RagManagedDb uses a tree-based structure to partition data and facilitate faster searches. As a tradeoff, it requires longer indexing time and manual triggering of index rebuild via the ImportRagFiles and UpdateRagCorpus API.", "id": "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDbANN", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringSchema": { "description": "The Model Monitoring Schema definition.", "properties": { "featureFields": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema" }, "description": "Feature names of the model. Vertex AI will try to match the features from your dataset as follows: * For 'csv' files, the header names are required, and we will extract the corresponding feature values when the header names align with the feature names. * For 'jsonl' files, we will extract the corresponding feature values if the key names match the feature names. Note: Nested features are not supported, so please ensure your features are flattened. Ensure the feature values are scalar or an array of scalars. * For 'bigquery' dataset, we will extract the corresponding feature values if the column names match the feature names. Note: The column type can be a scalar or an array of scalars. STRUCT or JSON types are not supported. You may use SQL queries to select or aggregate the relevant features from your original table. However, ensure that the 'schema' of the query results meets our requirements. * For the Vertex AI Endpoint Request Response Logging table or Vertex AI Batch Prediction Job results. If the instance_type is an array, ensure that the sequence in feature_fields matches the order of features in the prediction instance. We will match the feature with the array in the order specified in [feature_fields]." }, "groundTruthFields": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema" }, "description": "Target /ground truth names of the model." }, "predictionFields": { "description": "Prediction output names of the model. The requirements are the same as the feature_fields. For AutoML Tables, the prediction output name presented in schema will be: `predicted_{target_column}`, the `target_column` is the one you specified when you train the model. For Prediction output drift analysis: * AutoML Classification, the distribution of the argmax label will be analyzed. * AutoML Regression, the distribution of the value will be analyzed.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema" } } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitoringSchema", "type": "object" }, "GoogleCloudAiplatformV1beta1FetchExamplesRequest": { "id": "GoogleCloudAiplatformV1beta1FetchExamplesRequest", "type": "object", "description": "Request message for ExampleStoreService.FetchExamples.", "properties": { "pageToken": { "description": "Optional. The next_page_token value returned from a previous list ExampleStoreService.FetchExamplesResponse call.", "type": "string" }, "storedContentsExampleFilter": { "description": "The metadata filters for StoredContentsExamples.", "$ref": "GoogleCloudAiplatformV1beta1StoredContentsExampleFilter" }, "pageSize": { "format": "int32", "description": "Optional. The maximum number of examples to return. The service may return fewer than this value. If unspecified, at most 100 examples will be returned.", "type": "integer" }, "exampleIds": { "type": "array", "items": { "type": "string" }, "description": "Optional. Example IDs to fetch. If both metadata filters and Example IDs are specified, then both ID and metadata filtering will be applied." } } }, "GoogleCloudAiplatformV1beta1UpdateFeaturestoreOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for Featurestore." } }, "description": "Details of operations that perform update Featurestore.", "id": "GoogleCloudAiplatformV1beta1UpdateFeaturestoreOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1SpeculativeDecodingSpecNgramSpeculation": { "id": "GoogleCloudAiplatformV1beta1SpeculativeDecodingSpecNgramSpeculation", "type": "object", "description": "N-Gram speculation works by trying to find matching tokens in the previous prompt sequence and use those as speculation for generating new tokens.", "properties": { "ngramSize": { "type": "integer", "format": "int32", "description": "The number of last N input tokens used as ngram to search/match against the previous prompt sequence. This is equal to the N in N-Gram. The default value is 3 if not specified." } } }, "GoogleCloudAiplatformV1beta1PredictLongRunningMetadata": { "id": "GoogleCloudAiplatformV1beta1PredictLongRunningMetadata", "type": "object", "properties": {}, "description": "Metadata for PredictLongRunning long running operations." }, "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigAgentRunConfig": { "description": "Configuration for Agent Run.", "properties": { "sessionInput": { "description": "Optional. The session input to get agent running results.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigSessionInput" }, "agentEngine": { "description": "Optional. The resource name of the Agent Engine. Format: projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine} For example: projects/123/locations/us-central1/reasoningEngines/456", "type": "string" }, "userSimulatorConfig": { "description": "The configuration for a user simulator that uses an LLM to generate messages on behalf of the user.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigAgentRunConfigUserSimulatorConfig" } }, "id": "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigAgentRunConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ExecuteExtensionResponse": { "properties": { "content": { "description": "Response content from the extension. The content should be conformant to the response.content schema in the extension's manifest/OpenAPI spec.", "type": "string" } }, "description": "Response message for ExtensionExecutionService.ExecuteExtension.", "id": "GoogleCloudAiplatformV1beta1ExecuteExtensionResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1AddContextChildrenRequest": { "description": "Request message for MetadataService.AddContextChildren.", "properties": { "childContexts": { "type": "array", "items": { "type": "string" }, "description": "The resource names of the child Contexts." } }, "id": "GoogleCloudAiplatformV1beta1AddContextChildrenRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureNoiseSigmaNoiseSigmaForFeature": { "id": "GoogleCloudAiplatformV1beta1FeatureNoiseSigmaNoiseSigmaForFeature", "type": "object", "properties": { "name": { "description": "The name of the input feature for which noise sigma is provided. The features are defined in explanation metadata inputs.", "type": "string" }, "sigma": { "format": "float", "description": "This represents the standard deviation of the Gaussian kernel that will be used to add noise to the feature prior to computing gradients. Similar to noise_sigma but represents the noise added to the current feature. Defaults to 0.1.", "type": "number" } }, "description": "Noise sigma for a single feature." }, "GoogleCloudAiplatformV1beta1ActiveLearningConfig": { "id": "GoogleCloudAiplatformV1beta1ActiveLearningConfig", "type": "object", "properties": { "maxDataItemCount": { "description": "Max number of human labeled DataItems.", "format": "int64", "type": "string" }, "sampleConfig": { "description": "Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.", "$ref": "GoogleCloudAiplatformV1beta1SampleConfig" }, "trainingConfig": { "$ref": "GoogleCloudAiplatformV1beta1TrainingConfig", "description": "CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems." }, "maxDataItemPercentage": { "description": "Max percent of total DataItems for human labeling.", "format": "int32", "type": "integer" } }, "description": "Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy." }, "GoogleCloudAiplatformV1beta1CreateRegistryFeatureOperationMetadata": { "properties": { "genericMetadata": { "description": "Operation metadata for Feature.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Details of operations that perform create FeatureGroup.", "id": "GoogleCloudAiplatformV1beta1CreateRegistryFeatureOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1LossExample": { "properties": { "evaluationItem": { "description": "Reference to the persisted EvalItem resource name. Format: projects/.../locations/.../evaluationItems/{item_id} Used when analysis is run on an EvalSet.", "type": "string" }, "failedRubrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FailedRubric" }, "description": "The specific rubric(s) that failed and caused this example to be classified here. An example might fail multiple rubrics, but only specific ones trigger this loss pattern." }, "evaluationResult": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationResult", "description": "The full evaluation result object provided inline. Used when the analysis is performed on ephemeral data (without an EvaluationSet)." } }, "description": "Represents a specific example of a loss pattern.", "id": "GoogleCloudAiplatformV1beta1LossExample", "type": "object" }, "GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeOperationMetadata", "type": "object", "description": "Metadata information for NotebookService.UpgradeNotebookRuntime.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The operation generic information." }, "progressMessage": { "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInstance": { "description": "Spec for question answering correctness instance.", "properties": { "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "instruction": { "description": "Required. The question asked and other instruction in the inference prompt.", "type": "string" }, "context": { "description": "Optional. Text provided as context to answer the question.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1PurgeMemoriesRequest": { "properties": { "filterGroups": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryConjunctionFilter" }, "description": "Optional. Metadata filters that will be applied to the memories to be purged. Filters are defined using disjunctive normal form (OR of ANDs). For example: `filter_groups: [{filters: [{key: \"author\", value: {string_value: \"agent 123\"}, op: EQUAL}]}, {filters: [{key: \"label\", value: {string_value: \"travel\"}, op: EQUAL}, {key: \"author\", value: {string_value: \"agent 321\"}, op: EQUAL}]}]` would be equivalent to the logical expression: `(metadata.author = \"agent 123\" OR (metadata.label = \"travel\" AND metadata.author = \"agent 321\"))`." }, "filter": { "description": "Required. The standard list filter to determine which memories to purge. More detail in [AIP-160](https://google.aip.dev/160).", "type": "string" }, "force": { "description": "Optional. If true, the memories will actually be purged. If false, the purge request will be validated but not executed.", "type": "boolean" } }, "description": "Request message for MemoryBankService.PurgeMemories.", "id": "GoogleCloudAiplatformV1beta1PurgeMemoriesRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs", "type": "object", "properties": { "sentimentMax": { "type": "integer", "format": "int32", "description": "A sentiment is expressed as an integer ordinal, where higher value means a more positive sentiment. The range of sentiments that will be used is between 0 and sentimentMax (inclusive on both ends), and all the values in the range must be represented in the dataset before a model can be created. Only the Annotations with this sentimentMax will be used for training. sentimentMax value must be between 1 and 10 (inclusive)." } } }, "GoogleCloudAiplatformV1beta1EvaluationInstance": { "properties": { "agentEvalData": { "description": "Optional. Data used for agent evaluation.", "$ref": "GoogleCloudAiplatformV1beta1AgentData" }, "rubricGroups": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1RubricGroup" }, "description": "Optional. Named groups of rubrics associated with the prompt. This is used for rubric-based evaluations where rubrics can be referenced by a key. The key could represent versions, associated metrics, etc." }, "otherData": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceMapInstance", "description": "Optional. Other data used to populate placeholders based on their key. If a key conflicts with a field in the EvaluationInstance (e.g. `prompt`), the value of the field will take precedence over the value in other_data." }, "response": { "description": "Optional. Data used to populate placeholder `response` in a metric prompt template.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData" }, "prompt": { "description": "Optional. Data used to populate placeholder `prompt` in a metric prompt template.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData" }, "agentData": { "description": "Optional. Deprecated: Use `agent_eval_data` instead. Data used for agent evaluation.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentData" }, "reference": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData", "description": "Optional. Data used to populate placeholder `reference` in a metric prompt template." } }, "description": "A single instance to be evaluated. Instances are used to specify the input data for evaluation, from simple string comparisons to complex, multi-turn model evaluations", "id": "GoogleCloudAiplatformV1beta1EvaluationInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1FlexStart": { "id": "GoogleCloudAiplatformV1beta1FlexStart", "type": "object", "description": "FlexStart is used to schedule the deployment workload on DWS resource. It contains the max duration of the deployment.", "properties": { "maxRuntimeDuration": { "description": "The max duration of the deployment is max_runtime_duration. The deployment will be terminated after the duration. The max_runtime_duration can be set up to 7 days.", "format": "google-duration", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ReportExecutionEventResponse": { "properties": {}, "description": "Response message for NotebookInternalService.ReportExecutionEvent.", "id": "GoogleCloudAiplatformV1beta1ReportExecutionEventResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaVideoDataItem": { "id": "GoogleCloudAiplatformV1beta1SchemaVideoDataItem", "type": "object", "description": "Payload of Video DataItem.", "properties": { "gcsUri": { "description": "Required. Google Cloud Storage URI points to the original video in user's bucket. The video is up to 50 GB in size and up to 3 hour in duration.", "type": "string" }, "mimeType": { "description": "Output only. The mime type of the content of the video. Only the videos in below listed mime types are supported. Supported mime_type: - video/mp4 - video/avi - video/quicktime", "readOnly": true, "type": "string" } } }, "GoogleCloudAiplatformV1beta1BatchDedicatedResources": { "id": "GoogleCloudAiplatformV1beta1BatchDedicatedResources", "type": "object", "properties": { "maxReplicaCount": { "format": "int32", "description": "Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.", "type": "integer" }, "machineSpec": { "description": "Required. Immutable. The specification of a single machine.", "$ref": "GoogleCloudAiplatformV1beta1MachineSpec" }, "startingReplicaCount": { "description": "Immutable. The number of machine replicas used at the start of the batch operation. If not set, Vertex AI decides starting number, not greater than max_replica_count", "format": "int32", "type": "integer" }, "flexStart": { "description": "Optional. Immutable. If set, use DWS resource to schedule the deployment workload. reference: (https://cloud.google.com/blog/products/compute/introducing-dynamic-workload-scheduler)", "$ref": "GoogleCloudAiplatformV1beta1FlexStart" }, "spot": { "description": "Optional. If true, schedule the deployment workload on [spot VMs](https://cloud.google.com/kubernetes-engine/docs/concepts/spot-vms).", "type": "boolean" } }, "description": "A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation": { "description": "Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.", "properties": { "columnName": { "type": "string" }, "timeFormat": { "description": "The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix-milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `\"Z\"` (e.g. 1985-04-12T23:20:50.52Z)", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation", "type": "object" }, "GoogleCloudAiplatformV1beta1SlackSource": { "id": "GoogleCloudAiplatformV1beta1SlackSource", "type": "object", "properties": { "channels": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SlackSourceSlackChannels" }, "description": "Required. The Slack channels." } }, "description": "The Slack source for the ImportRagFilesRequest." }, "GoogleCloudAiplatformV1beta1RagChunk": { "description": "A RagChunk includes the content of a chunk of a RagFile, and associated metadata.", "properties": { "text": { "description": "The content of the chunk.", "type": "string" }, "pageSpan": { "description": "If populated, represents where the chunk starts and ends in the document.", "$ref": "GoogleCloudAiplatformV1beta1RagChunkPageSpan" }, "chunkId": { "description": "The ID of the chunk.", "type": "string" }, "fileId": { "description": "The ID of the file that the chunk belongs to.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1RagChunk", "type": "object" }, "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityResult": { "properties": { "explanation": { "description": "Output only. Explanation for question answering quality score.", "readOnly": true, "type": "string" }, "score": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Question Answering Quality score." }, "confidence": { "format": "float", "description": "Output only. Confidence for question answering quality score.", "readOnly": true, "type": "number" } }, "description": "Spec for question answering quality result.", "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringQualityResult", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecEmailConfig": { "properties": { "userEmails": { "type": "array", "items": { "type": "string" }, "description": "The email addresses to send the alerts." } }, "description": "The config for email alerts.", "id": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecEmailConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchResults": { "id": "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchResults", "type": "object", "properties": { "trajectoryAnyOrderMatchMetricValues": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchMetricValue" }, "description": "Output only. TrajectoryAnyOrderMatch metric values." } }, "description": "Results for TrajectoryAnyOrderMatch metric." }, "GoogleCloudAiplatformV1beta1PipelineTaskRerunConfigArtifactList": { "id": "GoogleCloudAiplatformV1beta1PipelineTaskRerunConfigArtifactList", "type": "object", "description": "A list of artifact metadata.", "properties": { "artifacts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RuntimeArtifact" }, "description": "Optional. A list of artifact metadata." } } }, "GoogleCloudAiplatformV1beta1SafetyInstance": { "description": "Spec for safety instance.", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SafetyInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualitySpec": { "id": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualitySpec", "type": "object", "description": "Spec for pairwise summarization quality score metric.", "properties": { "useReference": { "description": "Optional. Whether to use instance.reference to compute pairwise summarization quality.", "type": "boolean" }, "version": { "type": "integer", "description": "Optional. Which version to use for evaluation.", "format": "int32" } } }, "GoogleCloudAiplatformV1beta1BatchReadTensorboardTimeSeriesDataResponse": { "properties": { "timeSeriesData": { "description": "The returned time series data.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TimeSeriesData" } } }, "description": "Response message for TensorboardService.BatchReadTensorboardTimeSeriesData.", "id": "GoogleCloudAiplatformV1beta1BatchReadTensorboardTimeSeriesDataResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ListEvaluationSetsResponse": { "id": "GoogleCloudAiplatformV1beta1ListEvaluationSetsResponse", "type": "object", "description": "Response message for EvaluationManagementService.ListEvaluationSets.", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results.", "type": "string" }, "evaluationSets": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationSet" }, "description": "List of EvaluationSets in the requested page." } } }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentConnectionInfo": { "properties": { "routingToken": { "description": "Output only. The routing token for the SandboxEnvironment.", "readOnly": true, "type": "string" }, "loadBalancerHostname": { "description": "Output only. The hostname of the load balancer.", "type": "string", "readOnly": true }, "loadBalancerIp": { "type": "string", "readOnly": true, "description": "Output only. The IP address of the load balancer." }, "sandboxInternalIp": { "description": "Output only. The internal IP address of the SandboxEnvironment.", "type": "string", "readOnly": true }, "sandboxHostname": { "description": "Output only. The hostname of the SandboxEnvironment.", "readOnly": true, "type": "string" } }, "description": "The connection information of the SandboxEnvironment.", "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentConnectionInfo", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolCodeExecution": { "id": "GoogleCloudAiplatformV1beta1ToolCodeExecution", "type": "object", "description": "Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool.", "properties": {} }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation": { "properties": { "timestamp": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation" }, "text": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation" }, "auto": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation" }, "repeatedText": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation" }, "numeric": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation" }, "categorical": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation" }, "repeatedNumeric": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation" }, "repeatedCategorical": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation", "type": "object" }, "GoogleCloudAiplatformV1beta1Tool": { "properties": { "googleSearchRetrieval": { "description": "Optional. Specialized retrieval tool that is powered by Google Search.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1GoogleSearchRetrieval" }, "urlContext": { "description": "Optional. Tool to support URL context retrieval.", "$ref": "GoogleCloudAiplatformV1beta1UrlContext" }, "googleSearch": { "description": "Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.", "$ref": "GoogleCloudAiplatformV1beta1ToolGoogleSearch" }, "enterpriseWebSearch": { "description": "Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.", "$ref": "GoogleCloudAiplatformV1beta1EnterpriseWebSearch" }, "functionDeclarations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FunctionDeclaration" }, "description": "Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided." }, "parallelAiSearch": { "$ref": "GoogleCloudAiplatformV1beta1ToolParallelAiSearch", "description": "Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation" }, "computerUse": { "description": "Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.", "$ref": "GoogleCloudAiplatformV1beta1ToolComputerUse" }, "retrieval": { "description": "Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.", "$ref": "GoogleCloudAiplatformV1beta1Retrieval" }, "googleMaps": { "description": "Optional. GoogleMaps tool type. Tool to support Google Maps in Model.", "$ref": "GoogleCloudAiplatformV1beta1GoogleMaps" }, "codeExecution": { "$ref": "GoogleCloudAiplatformV1beta1ToolCodeExecution", "description": "Optional. CodeExecution tool type. Enables the model to execute code as part of generation." } }, "description": "Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).", "id": "GoogleCloudAiplatformV1beta1Tool", "type": "object" }, "GoogleCloudAiplatformV1beta1StudyTimeConstraint": { "id": "GoogleCloudAiplatformV1beta1StudyTimeConstraint", "type": "object", "description": "Time-based Constraint for Study", "properties": { "endTime": { "description": "Compares the wallclock time to this time. Must use UTC timezone.", "format": "google-datetime", "type": "string" }, "maxDuration": { "type": "string", "description": "Counts the wallclock time passed since the creation of this Study.", "format": "google-duration" } } }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTextExtractionPredictionResult": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTextExtractionPredictionResult", "type": "object", "properties": { "textSegmentStartOffsets": { "description": "The start offsets, inclusive, of the text segment in which the AnnotationSpec has been identified. Expressed as a zero-based number of characters as measured from the start of the text snippet.", "type": "array", "items": { "type": "string", "format": "int64" } }, "displayNames": { "type": "array", "items": { "type": "string" }, "description": "The display names of the AnnotationSpecs that had been identified, order matches the IDs." }, "ids": { "description": "The resource IDs of the AnnotationSpecs that had been identified, ordered by the confidence score descendingly.", "type": "array", "items": { "format": "int64", "type": "string" } }, "textSegmentEndOffsets": { "type": "array", "items": { "format": "int64", "type": "string" }, "description": "The end offsets, inclusive, of the text segment in which the AnnotationSpec has been identified. Expressed as a zero-based number of characters as measured from the start of the text snippet." }, "confidences": { "description": "The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids.", "type": "array", "items": { "format": "float", "type": "number" } } }, "description": "Prediction output format for Text Extraction." }, "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenNotebooks": { "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenNotebooks", "type": "object", "properties": { "notebooks": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences" }, "description": "Required. Regional resource references to notebooks." } }, "description": "Open notebooks." }, "GoogleCloudAiplatformV1beta1StringArray": { "id": "GoogleCloudAiplatformV1beta1StringArray", "type": "object", "description": "A list of string values.", "properties": { "values": { "type": "array", "items": { "type": "string" }, "description": "A list of string values." } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpec": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpec", "type": "object", "description": "Monitoring objectives spec.", "properties": { "tabularObjective": { "description": "Tabular monitoring objective.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective" }, "targetDataset": { "description": "Target dataset.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInput" }, "baselineDataset": { "description": "Baseline dataset. It could be the training dataset or production serving dataset from a previous period.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInput" }, "explanationSpec": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec", "description": "The explanation spec. This spec is required when the objectives spec includes feature attribution objectives." } } }, "GoogleCloudAiplatformV1beta1Tensor": { "id": "GoogleCloudAiplatformV1beta1Tensor", "type": "object", "properties": { "stringVal": { "type": "array", "items": { "type": "string" }, "description": "STRING" }, "tensorVal": { "format": "byte", "description": "Serialized raw tensor content.", "type": "string" }, "dtype": { "type": "string", "enumDescriptions": [ "Not a legal value for DataType. Used to indicate a DataType field has not been set.", "Data types that all computation devices are expected to be capable to support.", "", "", "", "", "", "", "", "", "", "", "" ], "description": "The data type of tensor.", "enum": [ "DATA_TYPE_UNSPECIFIED", "BOOL", "STRING", "FLOAT", "DOUBLE", "INT8", "INT16", "INT32", "INT64", "UINT8", "UINT16", "UINT32", "UINT64" ] }, "intVal": { "description": "INT_8 INT_16 INT_32", "type": "array", "items": { "type": "integer", "format": "int32" } }, "floatVal": { "type": "array", "items": { "type": "number", "format": "float" }, "description": "FLOAT" }, "doubleVal": { "description": "DOUBLE", "type": "array", "items": { "format": "double", "type": "number" } }, "structVal": { "description": "A map of string to tensor.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1Tensor" } }, "bytesVal": { "type": "array", "items": { "format": "byte", "type": "string" }, "description": "STRING" }, "int64Val": { "description": "INT64", "type": "array", "items": { "type": "string", "format": "int64" } }, "uintVal": { "type": "array", "items": { "type": "integer", "format": "uint32" }, "description": "UINT8 UINT16 UINT32" }, "shape": { "type": "array", "items": { "format": "int64", "type": "string" }, "description": "Shape of the tensor." }, "listVal": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tensor" }, "description": "A list of tensor values." }, "uint64Val": { "type": "array", "items": { "type": "string", "format": "uint64" }, "description": "UINT64" }, "boolVal": { "description": "Type specific representations that make it easy to create tensor protos in all languages. Only the representation corresponding to \"dtype\" can be set. The values hold the flattened representation of the tensor in row major order. BOOL", "type": "array", "items": { "type": "boolean" } } }, "description": "A tensor value type." }, "GoogleCloudAiplatformV1beta1ListRagDataSchemasResponse": { "description": "Response message for VertexRagDataService.ListRagDataSchemas.", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListRagDataSchemasRequest.page_token to obtain that page.", "type": "string" }, "ragDataSchemas": { "description": "List of RagDataSchemas in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RagDataSchema" } } }, "id": "GoogleCloudAiplatformV1beta1ListRagDataSchemasResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringInputTimeOffset": { "description": "Time offset setting.", "properties": { "offset": { "description": "[offset] is the time difference from the cut-off time. For scheduled jobs, the cut-off time is the scheduled time. For non-scheduled jobs, it's the time when the job was created. Currently we support the following format: 'w|W': Week, 'd|D': Day, 'h|H': Hour E.g. '1h' stands for 1 hour, '2d' stands for 2 days.", "type": "string" }, "window": { "description": "[window] refers to the scope of data selected for analysis. It allows you to specify the quantity of data you wish to examine. Currently we support the following format: 'w|W': Week, 'd|D': Day, 'h|H': Hour E.g. '1h' stands for 1 hour, '2d' stands for 2 days.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputTimeOffset", "type": "object" }, "GoogleCloudAiplatformV1beta1DataItemView": { "description": "A container for a single DataItem and Annotations on it.", "properties": { "dataItem": { "$ref": "GoogleCloudAiplatformV1beta1DataItem", "description": "The DataItem." }, "hasTruncatedAnnotations": { "description": "True if and only if the Annotations field has been truncated. It happens if more Annotations for this DataItem met the request's annotation_filter than are allowed to be returned by annotations_limit. Note that if Annotations field is not being returned due to field mask, then this field will not be set to true no matter how many Annotations are there.", "type": "boolean" }, "annotations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Annotation" }, "description": "The Annotations on the DataItem. If too many Annotations should be returned for the DataItem, this field will be truncated per annotations_limit in request. If it was, then the has_truncated_annotations will be set to true." } }, "id": "GoogleCloudAiplatformV1beta1DataItemView", "type": "object" }, "GoogleCloudAiplatformV1beta1ExternalApiSimpleSearchParams": { "description": "The search parameters to use for SIMPLE_SEARCH spec.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1ExternalApiSimpleSearchParams", "type": "object" }, "GoogleCloudAiplatformV1beta1Featurestore": { "id": "GoogleCloudAiplatformV1beta1Featurestore", "type": "object", "description": "Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values.", "properties": { "labels": { "description": "Optional. The labels with user-defined metadata to organize your Featurestore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", "type": "object", "additionalProperties": { "type": "string" } }, "updateTime": { "description": "Output only. Timestamp when this Featurestore was last updated.", "format": "google-datetime", "type": "string", "readOnly": true }, "name": { "type": "string", "readOnly": true, "description": "Output only. Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`" }, "satisfiesPzs": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this Featurestore was created.", "format": "google-datetime" }, "state": { "enum": [ "STATE_UNSPECIFIED", "STABLE", "UPDATING" ], "description": "Output only. State of the featurestore.", "readOnly": true, "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "State when the featurestore configuration is not being updated and the fields reflect the current configuration of the featurestore. The featurestore is usable in this state.", "The state of the featurestore configuration when it is being updated. During an update, the fields reflect either the original configuration or the updated configuration of the featurestore. For example, `online_serving_config.fixed_node_count` can take minutes to update. While the update is in progress, the featurestore is in the UPDATING state, and the value of `fixed_node_count` can be the original value or the updated value, depending on the progress of the operation. Until the update completes, the actual number of nodes can still be the original value of `fixed_node_count`. The featurestore is still usable in this state." ] }, "onlineStorageTtlDays": { "type": "integer", "description": "Optional. TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than `online_storage_ttl_days` since the feature generation time. Note that `online_storage_ttl_days` should be less than or equal to `offline_storage_ttl_days` for each EntityType under a featurestore. If not set, default to 4000 days", "format": "int32" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Optional. Customer-managed encryption key spec for data storage. If set, both of the online and offline data storage will be secured by this key." }, "onlineServingConfig": { "description": "Optional. Config for online storage resources. The field should not co-exist with the field of `OnlineStoreReplicationConfig`. If both of it and OnlineStoreReplicationConfig are unset, the feature store will not have an online store and cannot be used for online serving.", "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfig" } } }, "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataConversationTurn": { "description": "Represents a single turn/invocation in the conversation.", "properties": { "turnIndex": { "type": "integer", "description": "Required. The 0-based index of the turn in the conversation sequence.", "format": "int32" }, "turnId": { "description": "Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.", "type": "string" }, "events": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataAgentEvent" }, "description": "Optional. The list of events that occurred during this turn." } }, "id": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataConversationTurn", "type": "object" }, "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInput": { "description": "Input for question answering helpfulness metric.", "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInstance", "description": "Required. Question answering helpfulness instance." }, "metricSpec": { "description": "Required. Spec for question answering helpfulness score metric.", "$ref": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessSpec" } }, "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInput", "type": "object" }, "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigSparseEmbeddingConfig": { "id": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigSparseEmbeddingConfig", "type": "object", "properties": { "bm25": { "$ref": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigSparseEmbeddingConfigBm25", "description": "Use BM25 scoring algorithm." } }, "description": "Configuration for sparse emebdding generation." }, "GoogleCloudAiplatformV1beta1CachedContentUsageMetadata": { "properties": { "imageCount": { "type": "integer", "description": "Number of images.", "format": "int32" }, "totalTokenCount": { "type": "integer", "description": "Total number of tokens that the cached content consumes.", "format": "int32" }, "textCount": { "type": "integer", "format": "int32", "description": "Number of text characters." }, "videoDurationSeconds": { "type": "integer", "description": "Duration of video in seconds.", "format": "int32" }, "audioDurationSeconds": { "format": "int32", "description": "Duration of audio in seconds.", "type": "integer" } }, "description": "Metadata on the usage of the cached content.", "id": "GoogleCloudAiplatformV1beta1CachedContentUsageMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1AgentData": { "id": "GoogleCloudAiplatformV1beta1AgentData", "type": "object", "properties": { "agents": { "description": "Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1AgentConfig" } }, "turns": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ConversationTurn" }, "description": "Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -\u003e Agent Response)." } }, "description": "Represents data specific to multi-turn agent evaluations." }, "GoogleCloudAiplatformV1beta1UpdatePersistentResourceOperationMetadata": { "properties": { "progressMessage": { "description": "Progress Message for Update LRO", "type": "string" }, "genericMetadata": { "description": "Operation metadata for PersistentResource.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Details of operations that perform update PersistentResource.", "id": "GoogleCloudAiplatformV1beta1UpdatePersistentResourceOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceResult": { "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceResult", "type": "object", "properties": { "score": { "description": "Output only. Question Answering Relevance score.", "format": "float", "type": "number", "readOnly": true }, "confidence": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Confidence for question answering relevance score." }, "explanation": { "description": "Output only. Explanation for question answering relevance score.", "readOnly": true, "type": "string" } }, "description": "Spec for question answering relevance result." }, "GoogleCloudAiplatformV1beta1ListReasoningEngineRuntimeRevisionsResponse": { "id": "GoogleCloudAiplatformV1beta1ListReasoningEngineRuntimeRevisionsResponse", "type": "object", "properties": { "reasoningEngineRuntimeRevisions": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineRuntimeRevision" }, "description": "List of ReasoningEngineRuntimeRevisions in the requested page." }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListReasoningEngineRuntimeRevisionsRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for ReasoningEngineRuntimeRevisionService.ListReasoningEngineRuntimeRevisions" }, "GoogleCloudAiplatformV1beta1ExtensionOperation": { "id": "GoogleCloudAiplatformV1beta1ExtensionOperation", "type": "object", "description": "Operation of an extension.", "properties": { "functionDeclaration": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1FunctionDeclaration", "description": "Output only. Structured representation of a function declaration as defined by the OpenAPI Spec." }, "operationId": { "description": "Operation ID that uniquely identifies the operations among the extension. See: \"Operation Object\" in https://swagger.io/specification/. This field is parsed from the OpenAPI spec. For HTTP extensions, if it does not exist in the spec, we will generate one from the HTTP method and path.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1RagFileParsingConfigAdvancedParser": { "description": "Specifies the advanced parsing for RagFiles.", "properties": { "useAdvancedPdfParsing": { "description": "Whether to use advanced PDF parsing.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1RagFileParsingConfigAdvancedParser", "type": "object" }, "GoogleCloudAiplatformV1beta1NetworkSpec": { "id": "GoogleCloudAiplatformV1beta1NetworkSpec", "type": "object", "properties": { "subnetwork": { "description": "The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`", "type": "string" }, "enableInternetAccess": { "description": "Whether to enable public internet access. Default false.", "type": "boolean" }, "network": { "description": "The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)", "type": "string" } }, "description": "Network spec." }, "GoogleCloudAiplatformV1beta1GoogleMaps": { "properties": { "enableWidget": { "description": "Optional. If true, include the widget context token in the response.", "type": "boolean" } }, "description": "Tool to retrieve public maps data for grounding, powered by Google.", "id": "GoogleCloudAiplatformV1beta1GoogleMaps", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaVertex": { "description": "Represents a 2D point in the image. Vertex coordinates are normalized to be relative to the original image dimensions and range from 0 to 1. The origin of the coordinate system (0,0) is the top-left corner of the image. x increases to the right, and y increases to the bottom.", "properties": { "x": { "description": "X coordinate of the vertex, normalized to [0.0, 1.0].", "format": "double", "type": "number" }, "y": { "type": "number", "format": "double", "description": "Y coordinate of the vertex, normalized to [0.0, 1.0]." } }, "id": "GoogleCloudAiplatformV1beta1SchemaVertex", "type": "object" }, "GoogleCloudAiplatformV1beta1Content": { "id": "GoogleCloudAiplatformV1beta1Content", "type": "object", "properties": { "role": { "description": "Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.", "type": "string" }, "parts": { "description": "Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Part" } } }, "description": "The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message." }, "GoogleCloudAiplatformV1beta1AskContextsRequest": { "id": "GoogleCloudAiplatformV1beta1AskContextsRequest", "type": "object", "description": "Agentic Retrieval Ask API for RAG. Request message for VertexRagService.AskContexts.", "properties": { "query": { "$ref": "GoogleCloudAiplatformV1beta1RagQuery", "description": "Required. Single RAG retrieve query." }, "tools": { "description": "Optional. The tools to use for AskContexts.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" } } } }, "GoogleCloudAiplatformV1beta1DynamicRetrievalConfig": { "id": "GoogleCloudAiplatformV1beta1DynamicRetrievalConfig", "type": "object", "properties": { "mode": { "description": "The mode of the predictor to be used in dynamic retrieval.", "enum": [ "MODE_UNSPECIFIED", "MODE_DYNAMIC" ], "type": "string", "enumDescriptions": [ "Always trigger retrieval.", "Run retrieval only when system decides it is necessary." ] }, "dynamicThreshold": { "type": "number", "description": "Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.", "format": "float" } }, "description": "Describes the options to customize dynamic retrieval." }, "GoogleCloudAiplatformV1beta1InternalOsServiceStateInstance": { "id": "GoogleCloudAiplatformV1beta1InternalOsServiceStateInstance", "type": "object", "properties": { "serviceState": { "description": "Required. internal service state.", "enum": [ "UNKNOWN", "HEALTHY", "UNHEALTHY" ], "type": "string", "enumDescriptions": [ "Health status is unknown: not initialized or failed to retrieve.", "The resource is healthy.", "The resource is unhealthy." ] }, "serviceName": { "enum": [ "INTERNAL_OS_SERVICE_ENUM_UNSPECIFIED", "DOCKER_SERVICE_STATE", "CONTROL_PLANE_API_DNS_STATE", "PROXY_REGISTRATION_DNS_STATE", "JUPYTER_STATE", "JUPYTER_API_STATE", "EUC_METADATA_API_STATE", "EUC_AGENT_API_STATE", "IDLE_SHUTDOWN_AGENT_STATE", "PROXY_AGENT_STATE", "GCR_DNS_STATE", "GUEST_ATTRIBUTE_STATE" ], "description": "Required. internal service name.", "type": "string", "enumDescriptions": [ "Service name unknown.", "Represents the internal os docker client.", "Represents resolving DNS for the control plane api endpoint.", "Represents resolving DNS for the proxy registration endpoint.", "Represents the jupyter endpoint.", "Represents the jupyter/api endpoint.", "Represents the EUC metadata server API endpoint.", "Represents the EUC agent server API endpoint.", "Represents the idle shutdown agent sidecar container.", "Represents the proxy agent sidecar container.", "Represents resolving DNS for the gcr.io endpoint.", "Represents if the guest attribute service is enabled." ] } }, "description": "Request message for [InternalOsServiceStateInstance]." }, "GoogleCloudAiplatformV1beta1CustomOutput": { "properties": { "rawOutputs": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1RawOutput", "description": "Output only. List of raw output strings." } }, "description": "Spec for custom output.", "id": "GoogleCloudAiplatformV1beta1CustomOutput", "type": "object" }, "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsResponse": { "id": "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsResponse", "type": "object", "properties": {}, "description": "Response message for MetadataService.AddContextArtifactsAndExecutions." }, "GoogleCloudAiplatformV1beta1CopyModelOperationMetadata": { "description": "Details of ModelService.CopyModel operation.", "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1beta1CopyModelOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilter": { "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilter", "type": "object", "description": "Filter for searching ModelMonitoringStats.", "properties": { "tabularStatsFilter": { "description": "Tabular statistics filter.", "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilterTabularStatsFilter" } } }, "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchSpec": { "id": "GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchSpec", "type": "object", "description": "Spec for TrajectoryAnyOrderMatch metric - returns 1 if all tool calls in the reference trajectory appear in the predicted trajectory in any order, else 0.", "properties": {} }, "GoogleCloudAiplatformV1beta1ListFeatureMonitorsResponse": { "id": "GoogleCloudAiplatformV1beta1ListFeatureMonitorsResponse", "type": "object", "description": "Response message for FeatureRegistryService.ListFeatureMonitors.", "properties": { "featureMonitors": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureMonitor" }, "description": "The FeatureMonitors matching the request." }, "nextPageToken": { "description": "A token, which can be sent as ListFeatureMonitorsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } } }, "CloudAiPlatformCommonCreatePipelineJobApiErrorDetail": { "id": "CloudAiPlatformCommonCreatePipelineJobApiErrorDetail", "type": "object", "description": "Create API error message for Vertex Pipeline.", "properties": { "publicMessage": { "description": "Public messages contains actionable items for the error cause.", "type": "string" }, "errorCause": { "type": "string", "enumDescriptions": [ "Should never be used.", "IR Pipeline Spec can not been parsed to yaml or json format.", "A pipeline spec is invalid.", "A deployment config is invalid.", "A deployment spec is invalid.", "An instance schema is invalid.", "A custom job is invalid.", "A container spec is invalid.", "Notification email setup is invalid.", "Service account setup is invalid.", "KMS setup is invalid.", "Network setup is invalid.", "Task spec is invalid.", "Task artifact is invalid.", "Importer spec is invalid.", "Resolver spec is invalid.", "Runtime Parameters are invalid.", "Cloud API not enabled.", "Invalid Cloud Storage input uri", "Invalid Cloud Storage output uri", "Component spec of pipeline is invalid.", "DagOutputsSpec is invalid.", "DagSpec is invalid.", "Project does not have enough quota.", "An internal error with unknown cause." ], "description": "The error root cause returned by CreatePipelineJob API.", "enum": [ "ERROR_CAUSE_UNSPECIFIED", "INVALID_PIPELINE_SPEC_FORMAT", "INVALID_PIPELINE_SPEC", "INVALID_DEPLOYMENT_CONFIG", "INVALID_DEPLOYMENT_SPEC", "INVALID_INSTANCE_SCHEMA", "INVALID_CUSTOM_JOB", "INVALID_CONTAINER_SPEC", "INVALID_NOTIFICATION_EMAIL_SETUP", "INVALID_SERVICE_ACCOUNT_SETUP", "INVALID_KMS_SETUP", "INVALID_NETWORK_SETUP", "INVALID_PIPELINE_TASK_SPEC", "INVALID_PIPELINE_TASK_ARTIFACT", "INVALID_IMPORTER_SPEC", "INVALID_RESOLVER_SPEC", "INVALID_RUNTIME_PARAMETERS", "CLOUD_API_NOT_ENABLED", "INVALID_GCS_INPUT_URI", "INVALID_GCS_OUTPUT_URI", "INVALID_COMPONENT_SPEC", "INVALID_DAG_OUTPUTS_SPEC", "INVALID_DAG_SPEC", "INSUFFICIENT_QUOTA", "INTERNAL" ] } } }, "GoogleCloudAiplatformV1beta1GroundingChunkWeb": { "description": "A `Web` chunk is a piece of evidence that comes from a web page. It contains the URI of the web page, the title of the page, and the domain of the page. This is used to provide the user with a link to the source of the information.", "properties": { "uri": { "description": "The URI of the web page that contains the evidence.", "type": "string" }, "title": { "description": "The title of the web page that contains the evidence.", "type": "string" }, "domain": { "description": "The domain of the web page that contains the evidence. This can be used to filter out low-quality sources.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1GroundingChunkWeb", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateFeatureOperationMetadata": { "description": "Details of operations that perform update Feature.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for Feature Update." } }, "id": "GoogleCloudAiplatformV1beta1UpdateFeatureOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective", "type": "object", "properties": { "featureDriftSpec": { "description": "Input feature distribution drift monitoring spec.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec" }, "featureAttributionSpec": { "description": "Feature attribution monitoring spec.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecFeatureAttributionSpec" }, "predictionOutputDriftSpec": { "description": "Prediction output distribution drift monitoring spec.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec" } }, "description": "Tabular monitoring objective." }, "GoogleCloudAiplatformV1beta1PrebuiltVoiceConfig": { "id": "GoogleCloudAiplatformV1beta1PrebuiltVoiceConfig", "type": "object", "properties": { "voiceName": { "description": "The name of the prebuilt voice to use.", "type": "string" } }, "description": "Configuration for a prebuilt voice." }, "GoogleCloudAiplatformV1beta1RayMetricSpec": { "id": "GoogleCloudAiplatformV1beta1RayMetricSpec", "type": "object", "description": "Configuration for the Ray metrics.", "properties": { "disabled": { "description": "Optional. Flag to disable the Ray metrics collection.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1NotebookExecutionJobCustomEnvironmentSpec": { "description": "Compute configuration to use for an execution job.", "properties": { "persistentDiskSpec": { "description": "The specification of a persistent disk to attach for the execution job.", "$ref": "GoogleCloudAiplatformV1beta1PersistentDiskSpec" }, "networkSpec": { "description": "The network configuration to use for the execution job.", "$ref": "GoogleCloudAiplatformV1beta1NetworkSpec" }, "machineSpec": { "$ref": "GoogleCloudAiplatformV1beta1MachineSpec", "description": "The specification of a single machine for the execution job." } }, "id": "GoogleCloudAiplatformV1beta1NotebookExecutionJobCustomEnvironmentSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateInstanceRubricsResponse": { "id": "GoogleCloudAiplatformV1beta1GenerateInstanceRubricsResponse", "type": "object", "description": "Response message for EvaluationService.GenerateInstanceRubrics.", "properties": { "generatedRubrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Rubric" }, "readOnly": true, "description": "Output only. A list of generated rubrics." } } }, "GoogleCloudAiplatformV1beta1ModelEvaluationModelEvaluationExplanationSpec": { "properties": { "explanationType": { "description": "Explanation type. For AutoML Image Classification models, possible values are: * `image-integrated-gradients` * `image-xrai`", "type": "string" }, "explanationSpec": { "description": "Explanation spec details.", "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec" } }, "id": "GoogleCloudAiplatformV1beta1ModelEvaluationModelEvaluationExplanationSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchCreateRagDataSchemasRequest": { "id": "GoogleCloudAiplatformV1beta1BatchCreateRagDataSchemasRequest", "type": "object", "properties": { "requests": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1CreateRagDataSchemaRequest" }, "description": "Required. The request messages for VertexRagDataService.CreateRagDataSchema. A maximum of 500 schemas can be created in a batch." } }, "description": "Request message for VertexRagDataService.BatchCreateRagDataSchemas." }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTextSentimentPredictionResult": { "description": "Prediction output format for Text Sentiment", "properties": { "sentiment": { "format": "int32", "description": "The integer sentiment labels between 0 (inclusive) and sentimentMax label (inclusive), while 0 maps to the least positive sentiment and sentimentMax maps to the most positive one. The higher the score is, the more positive the sentiment in the text snippet is. Note: sentimentMax is an integer value between 1 (inclusive) and 10 (inclusive).", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTextSentimentPredictionResult", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaVideoActionRecognitionAnnotation": { "description": "Annotation details specific to video action recognition.", "properties": { "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "timeSegment": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTimeSegment", "description": "This Annotation applies to the time period represented by the TimeSegment. If it's not set, the Annotation applies to the whole video." }, "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaVideoActionRecognitionAnnotation", "type": "object" }, "GoogleCloudAiplatformV1beta1QueryExtensionRequest": { "description": "Request message for ExtensionExecutionService.QueryExtension.", "properties": { "contents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "description": "Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request." } }, "id": "GoogleCloudAiplatformV1beta1QueryExtensionRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecValue": { "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecValue", "type": "object", "description": "Single value that supports strings and floats.", "properties": { "stringValue": { "description": "String type.", "type": "string" }, "floatValue": { "type": "number", "format": "float", "description": "Float type." } } }, "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestSnapshotExport": { "id": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestSnapshotExport", "type": "object", "description": "Describes exporting the latest Feature values of all entities of the EntityType between [start_time, snapshot_time].", "properties": { "snapshotTime": { "type": "string", "description": "Exports Feature values as of this timestamp. If not set, retrieve values as of now. Timestamp, if present, must not have higher than millisecond precision.", "format": "google-datetime" }, "startTime": { "description": "Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision.", "format": "google-datetime", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaPredictParamsGroundingConfig": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsGroundingConfig", "type": "object", "description": "The configuration for grounding checking.", "properties": { "sources": { "description": "The sources for the grounding checking.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPredictParamsGroundingConfigSourceEntry" } }, "disableAttribution": { "description": "If set, skip finding claim attributions (i.e not generate grounding citation).", "type": "boolean", "deprecated": true } } }, "GoogleCloudAiplatformV1beta1ModelGardenSource": { "properties": { "versionId": { "description": "Optional. The model garden source model version ID.", "type": "string" }, "skipHfModelCache": { "description": "Optional. Whether to avoid pulling the model from the HF cache.", "type": "boolean" }, "publicModelName": { "description": "Required. The model garden source model resource name.", "type": "string" } }, "description": "Contains information about the source of the models generated from Model Garden.", "id": "GoogleCloudAiplatformV1beta1ModelGardenSource", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTextClassificationAnnotation": { "id": "GoogleCloudAiplatformV1beta1SchemaTextClassificationAnnotation", "type": "object", "description": "Annotation details specific to text classification.", "properties": { "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1GenerateFetchAccessTokenRequest": { "properties": {}, "description": "Request message for FeatureOnlineStoreService.GenerateFetchAccessToken.", "id": "GoogleCloudAiplatformV1beta1GenerateFetchAccessTokenRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1UserScenario": { "id": "GoogleCloudAiplatformV1beta1UserScenario", "type": "object", "description": "Output of user scenario generation.", "properties": { "startingPrompt": { "description": "Starting prompt for the conversation between simulated user and agent under the test.", "type": "string" }, "conversationPlan": { "description": "Conversation plan to drive multi-turn agent run and get simulated agent eval dataset.", "type": "string" }, "testCaseTitle": { "description": "Represents a short 3-5 word title for eval test case.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1UpdateIndexOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1UpdateIndexOperationMetadata", "type": "object", "description": "Runtime operation information for IndexService.UpdateIndex.", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" }, "nearestNeighborSearchOperationMetadata": { "description": "The operation metadata with regard to Matching Engine Index operation.", "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadata" } } }, "GoogleCloudAiplatformV1beta1JiraSourceJiraQueries": { "properties": { "serverUri": { "description": "Required. The Jira server URI.", "type": "string" }, "projects": { "description": "A list of Jira projects to import in their entirety.", "type": "array", "items": { "type": "string" } }, "customQueries": { "type": "array", "items": { "type": "string" }, "description": "A list of custom Jira queries to import. For information about JQL (Jira Query Language), see https://support.atlassian.com/jira-service-management-cloud/docs/use-advanced-search-with-jira-query-language-jql/" }, "email": { "description": "Required. The Jira email address.", "type": "string" }, "apiKeyConfig": { "$ref": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig", "description": "Required. The SecretManager secret version resource name (e.g. projects/{project}/secrets/{secret}/versions/{version}) storing the Jira API key. See [Manage API tokens for your Atlassian account](https://support.atlassian.com/atlassian-account/docs/manage-api-tokens-for-your-atlassian-account/)." } }, "description": "JiraQueries contains the Jira queries and corresponding authentication.", "id": "GoogleCloudAiplatformV1beta1JiraSourceJiraQueries", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation", "type": "object", "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index.", "properties": { "columnName": { "type": "string" } } }, "GoogleCloudAiplatformV1beta1FulfillmentInstance": { "id": "GoogleCloudAiplatformV1beta1FulfillmentInstance", "type": "object", "description": "Spec for fulfillment instance.", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "instruction": { "description": "Required. Inference instruction prompt to compare prediction with.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ExportDataOperationMetadata": { "properties": { "gcsOutputDirectory": { "description": "A Google Cloud Storage directory which path ends with '/'. The exported data is stored in the directory.", "type": "string" }, "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The common part of the operation metadata." } }, "description": "Runtime operation information for DatasetService.ExportData.", "id": "GoogleCloudAiplatformV1beta1ExportDataOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback": { "id": "GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback", "type": "object", "description": "Content filter results for a prompt sent in the request. Note: This is sent only in the first stream chunk and only if no candidates were generated due to content violations.", "properties": { "blockReasonMessage": { "readOnly": true, "type": "string", "description": "Output only. A readable message that explains the reason why the prompt was blocked." }, "blockReason": { "description": "Output only. The reason why the prompt was blocked.", "enum": [ "BLOCKED_REASON_UNSPECIFIED", "SAFETY", "OTHER", "BLOCKLIST", "PROHIBITED_CONTENT", "MODEL_ARMOR", "IMAGE_SAFETY", "JAILBREAK" ], "type": "string", "enumDescriptions": [ "The blocked reason is unspecified.", "The prompt was blocked for safety reasons.", "The prompt was blocked for other reasons. For example, it may be due to the prompt's language, or because it contains other harmful content.", "The prompt was blocked because it contains a term from the terminology blocklist.", "The prompt was blocked because it contains prohibited content.", "The prompt was blocked by Model Armor.", "The prompt was blocked because it contains content that is unsafe for image generation.", "The prompt was blocked as a jailbreak attempt." ], "readOnly": true }, "safetyRatings": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SafetyRating" }, "readOnly": true, "description": "Output only. A list of safety ratings for the prompt. There is one rating per category." } } }, "GoogleCloudAiplatformV1beta1VertexRagStore": { "id": "GoogleCloudAiplatformV1beta1VertexRagStore", "type": "object", "properties": { "ragResources": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource" }, "description": "Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support." }, "storeContext": { "description": "Optional. Currently only supported for Gemini Multimodal Live API. In Gemini Multimodal Live API, if `store_context` bool is specified, Gemini will leverage it to automatically memorize the interactions between the client and Gemini, and retrieve context when needed to augment the response generation for users' ongoing and future interactions.", "type": "boolean" }, "similarityTopK": { "type": "integer", "deprecated": true, "description": "Optional. Number of top k results to return from the selected corpora.", "format": "int32" }, "ragCorpora": { "description": "Optional. Deprecated. Please use rag_resources instead.", "deprecated": true, "type": "array", "items": { "type": "string" } }, "vectorDistanceThreshold": { "deprecated": true, "type": "number", "format": "double", "description": "Optional. Only return results with vector distance smaller than the threshold." }, "ragRetrievalConfig": { "description": "Optional. The retrieval config for the Rag query.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfig" } }, "description": "Retrieve from Vertex RAG Store for grounding." }, "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployVertex": { "description": "Multiple setups to deploy the PublisherModel.", "properties": { "multiDeployVertex": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeploy" }, "description": "Optional. One click deployment configurations." } }, "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployVertex", "type": "object" }, "GoogleCloudAiplatformV1beta1ReportRuntimeEventRequest": { "description": "Request message for NotebookInternalService.ReportRuntimeEvent.", "properties": { "eventDetails": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The details of the request for debug." }, "vmToken": { "description": "Required. The VM identity token (a JWT) for authenticating the VM. https://cloud.google.com/compute/docs/instances/verifying-instance-identity", "type": "string" }, "internalOsServiceStateInstance": { "description": "The details of the internal os service states.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1InternalOsServiceStateInstance" }, "deprecated": true }, "eventType": { "type": "string", "enumDescriptions": [ "Unspecified.", "Used for readiness reporting.", "Used for idle reporting." ], "description": "Required. The type of the event.", "enum": [ "EVENT_TYPE_UNSPECIFIED", "HEARTBEAT", "IDLE" ] }, "internalOsServiceStateInstances": { "description": "Optional. The details of the internal os service states.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1InternalOsServiceStateInstance" } } }, "id": "GoogleCloudAiplatformV1beta1ReportRuntimeEventRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1Scalar": { "description": "One point viewable on a scalar metric plot.", "properties": { "value": { "format": "double", "description": "Value of the point at this step / timestamp.", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1Scalar", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureViewSync": { "id": "GoogleCloudAiplatformV1beta1FeatureViewSync", "type": "object", "description": "FeatureViewSync is a representation of sync operation which copies data from data source to Feature View in Online Store.", "properties": { "syncSummary": { "description": "Output only. Summary of the sync job.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1FeatureViewSyncSyncSummary" }, "name": { "description": "Identifier. Name of the FeatureViewSync. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`", "type": "string" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "finalStatus": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. Final status of the FeatureViewSync." }, "runTime": { "readOnly": true, "$ref": "GoogleTypeInterval", "description": "Output only. Time when this FeatureViewSync is finished." }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when this FeatureViewSync is created. Creation of a FeatureViewSync means that the job is pending / waiting for sufficient resources but may not have started the actual data transfer yet." } } }, "GoogleCloudAiplatformV1beta1PredictLongRunningResponse": { "description": "Response message for [PredictionService.PredictLongRunning]", "properties": { "generateVideoResponse": { "$ref": "GoogleCloudAiplatformV1beta1GenerateVideoResponse", "description": "The response of the video generation prediction." } }, "id": "GoogleCloudAiplatformV1beta1PredictLongRunningResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation", "type": "object", "properties": { "numeric": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation" }, "categorical": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation" }, "timestamp": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation" }, "text": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation" }, "auto": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation" } } }, "GoogleCloudAiplatformV1beta1RagFileTransformationConfig": { "id": "GoogleCloudAiplatformV1beta1RagFileTransformationConfig", "type": "object", "properties": { "ragFileChunkingConfig": { "$ref": "GoogleCloudAiplatformV1beta1RagFileChunkingConfig", "description": "Specifies the chunking config for RagFiles." } }, "description": "Specifies the transformation config for RagFiles." }, "GoogleCloudAiplatformV1beta1AgentEvent": { "id": "GoogleCloudAiplatformV1beta1AgentEvent", "type": "object", "properties": { "content": { "$ref": "GoogleCloudAiplatformV1beta1Content", "description": "Required. The content of the event (e.g., text response, tool call, tool response)." }, "author": { "description": "Required. The ID of the agent or entity that generated this event. Use \"user\" to denote events generated by the end-user.", "type": "string" }, "stateDelta": { "description": "Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "eventTime": { "type": "string", "description": "Optional. The timestamp when the event occurred.", "format": "google-datetime" }, "activeTools": { "description": "Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" } } }, "description": "Represents a single event in the execution trace." }, "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfigAuthProvider": { "description": "Configuration for an authentication provider, including support for [JSON Web Token (JWT)](https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32).", "properties": { "audiences": { "type": "array", "items": { "type": "string" }, "description": "The list of JWT [audiences](https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32#section-4.1.3). that are allowed to access. A JWT containing any of these audiences will be accepted." }, "allowedIssuers": { "description": "A list of allowed JWT issuers. Each entry must be a valid Google service account, in the following format: `service-account-name@project-id.iam.gserviceaccount.com`", "type": "array", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfigAuthProvider", "type": "object" }, "GoogleCloudAiplatformV1beta1EncryptionSpec": { "id": "GoogleCloudAiplatformV1beta1EncryptionSpec", "type": "object", "description": "Represents a customer-managed encryption key specification that can be applied to a Vertex AI resource.", "properties": { "kmsKeyName": { "description": "Required. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1UnmanagedContainerModel": { "properties": { "artifactUri": { "description": "The path to the directory containing the Model artifact and any of its supporting files.", "type": "string" }, "predictSchemata": { "$ref": "GoogleCloudAiplatformV1beta1PredictSchemata", "description": "Contains the schemata used in Model's predictions and explanations" }, "containerSpec": { "description": "Input only. The specification of the container that is to be used when deploying this Model.", "$ref": "GoogleCloudAiplatformV1beta1ModelContainerSpec" } }, "description": "Contains model information necessary to perform batch prediction without requiring a full model import.", "id": "GoogleCloudAiplatformV1beta1UnmanagedContainerModel", "type": "object" }, "GoogleCloudAiplatformV1beta1PublisherModelEulaAcceptance": { "description": "Response message for ModelGardenService.UpdatePublisherModelEula.", "properties": { "projectNumber": { "format": "int64", "description": "The project number requesting access for named model.", "type": "string" }, "publisherModel": { "description": "The publisher model resource name.", "type": "string" }, "publisherModelEulaAcked": { "description": "The EULA content acceptance status.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1PublisherModelEulaAcceptance", "type": "object" }, "GoogleCloudAiplatformV1beta1TrainingConfig": { "properties": { "timeoutTrainingMilliHours": { "format": "int64", "description": "The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.", "type": "string" } }, "description": "CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.", "id": "GoogleCloudAiplatformV1beta1TrainingConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureMonitorJobJobSummary": { "properties": { "totalSlotMs": { "type": "string", "readOnly": true, "description": "Output only. BigQuery slot milliseconds consumed.", "format": "int64" }, "featureStatsAndAnomalies": { "description": "Output only. Features and their stats and anomalies", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureStatsAndAnomaly" } } }, "description": "Summary from the FeatureMonitorJob.", "id": "GoogleCloudAiplatformV1beta1FeatureMonitorJobJobSummary", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationMaskAnnotation": { "properties": { "maskGcsUri": { "description": "Google Cloud Storage URI that points to the mask image. The image must be in PNG format. It must have the same size as the DataItem's image. Each pixel in the image mask represents the AnnotationSpec which the pixel in the image DataItem belong to. Each color is mapped to one AnnotationSpec based on annotation_spec_colors.", "type": "string" }, "annotationSpecColors": { "description": "The mapping between color and AnnotationSpec for this Annotation.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaAnnotationSpecColor" } } }, "description": "The mask based segmentation annotation.", "id": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationMaskAnnotation", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata", "type": "object", "description": "Model metadata specific to Seq2Seq Plus Forecasting.", "properties": { "trainCostMilliNodeHours": { "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget.", "format": "int64", "type": "string" }, "evaluatedDataItemsBigqueryUri": { "description": "BigQuery destination uri for exported evaluated examples.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1Candidate": { "description": "A response candidate generated from the model.", "properties": { "content": { "description": "Output only. The content of the candidate.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1Content" }, "safetyRatings": { "description": "Output only. A list of ratings for the safety of a response candidate. There is at most one rating per category.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SafetyRating" }, "readOnly": true }, "urlContextMetadata": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1UrlContextMetadata", "description": "Output only. Metadata returned when the model uses the `url_context` tool to get information from a user-provided URL." }, "logprobsResult": { "description": "Output only. The detailed log probability information for the tokens in this candidate. This is useful for debugging, understanding model uncertainty, and identifying potential \"hallucinations\".", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1LogprobsResult" }, "finishMessage": { "description": "Output only. Describes the reason the model stopped generating tokens in more detail. This field is returned only when `finish_reason` is set.", "type": "string", "readOnly": true }, "index": { "format": "int32", "description": "Output only. The 0-based index of this candidate in the list of generated responses. This is useful for distinguishing between multiple candidates when `candidate_count` \u003e 1.", "readOnly": true, "type": "integer" }, "avgLogprobs": { "description": "Output only. The average log probability of the tokens in this candidate. This is a length-normalized score that can be used to compare the quality of candidates of different lengths. A higher average log probability suggests a more confident and coherent response.", "format": "double", "type": "number", "readOnly": true }, "finishReason": { "readOnly": true, "type": "string", "enumDescriptions": [ "The finish reason is unspecified.", "The model reached a natural stopping point or a configured stop sequence.", "The model generated the maximum number of tokens allowed by the `max_output_tokens` parameter.", "The model stopped generating because the content potentially violates safety policies. NOTE: When streaming, the `content` field is empty if content filters block the output.", "The model stopped generating because the content may be a recitation from a source.", "The model stopped generating for a reason not otherwise specified.", "The model stopped generating because the content contains a term from a configured blocklist.", "The model stopped generating because the content may be prohibited.", "The model stopped generating because the content may contain sensitive personally identifiable information (SPII).", "The model generated a function call that is syntactically invalid and can't be parsed.", "The model response was blocked by Model Armor.", "The generated image potentially violates safety policies.", "The generated image may contain prohibited content.", "The generated image may be a recitation from a source.", "The image generation stopped for a reason not otherwise specified.", "The model generated a function call that is semantically invalid. This can happen, for example, if function calling is not enabled or the generated function is not in the function declaration.", "The model was expected to generate an image, but didn't." ], "enum": [ "FINISH_REASON_UNSPECIFIED", "STOP", "MAX_TOKENS", "SAFETY", "RECITATION", "OTHER", "BLOCKLIST", "PROHIBITED_CONTENT", "SPII", "MALFORMED_FUNCTION_CALL", "MODEL_ARMOR", "IMAGE_SAFETY", "IMAGE_PROHIBITED_CONTENT", "IMAGE_RECITATION", "IMAGE_OTHER", "UNEXPECTED_TOOL_CALL", "NO_IMAGE" ], "description": "Output only. The reason why the model stopped generating tokens. If empty, the model has not stopped generating." }, "citationMetadata": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1CitationMetadata", "description": "Output only. A collection of citations that apply to the generated content." }, "groundingMetadata": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1GroundingMetadata", "description": "Output only. Metadata returned when grounding is enabled. It contains the sources used to ground the generated content." } }, "id": "GoogleCloudAiplatformV1beta1Candidate", "type": "object" }, "GoogleCloudAiplatformV1beta1ExportFeatureValuesResponse": { "id": "GoogleCloudAiplatformV1beta1ExportFeatureValuesResponse", "type": "object", "properties": {}, "description": "Response message for FeaturestoreService.ExportFeatureValues." }, "GoogleCloudAiplatformV1beta1ExtensionPrivateServiceConnectConfig": { "properties": { "serviceDirectory": { "description": "Required. The Service Directory resource name in which the service endpoints associated to the extension are registered. Format: `projects/{project_id}/locations/{location_id}/namespaces/{namespace_id}/services/{service_id}` - The Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) should be granted `servicedirectory.viewer` and `servicedirectory.pscAuthorizedService` roles on the resource.", "type": "string" } }, "description": "PrivateExtensionConfig configuration for the extension.", "id": "GoogleCloudAiplatformV1beta1ExtensionPrivateServiceConnectConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairList": { "properties": { "features": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair" }, "description": "List of feature names and values." } }, "description": "Response structure in the format of key (feature name) and (feature) value pair.", "id": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairList", "type": "object" }, "GoogleCloudAiplatformV1beta1ListArtifactsResponse": { "id": "GoogleCloudAiplatformV1beta1ListArtifactsResponse", "type": "object", "properties": { "artifacts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Artifact" }, "description": "The Artifacts retrieved from the MetadataStore." }, "nextPageToken": { "description": "A token, which can be sent as ListArtifactsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages.", "type": "string" } }, "description": "Response message for MetadataService.ListArtifacts." }, "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataRequest": { "id": "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataRequest", "type": "object", "properties": { "pageToken": { "description": "A page token, received from a previous ExportTensorboardTimeSeriesData call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to ExportTensorboardTimeSeriesData must match the call that provided the page token.", "type": "string" }, "pageSize": { "format": "int32", "description": "The maximum number of data points to return per page. The default page_size is 1000. Values must be between 1 and 10000. Values above 10000 are coerced to 10000.", "type": "integer" }, "orderBy": { "description": "Field to use to sort the TensorboardTimeSeries' data. By default, TensorboardTimeSeries' data is returned in a pseudo random order.", "type": "string" }, "filter": { "description": "Exports the TensorboardTimeSeries' data that match the filter expression.", "type": "string" } }, "description": "Request message for TensorboardService.ExportTensorboardTimeSeriesData." }, "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequest": { "id": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequest", "type": "object", "description": "Request message for FeaturestoreService.BatchReadFeatureValues.", "properties": { "destination": { "description": "Required. Specifies output location and format.", "$ref": "GoogleCloudAiplatformV1beta1FeatureValueDestination" }, "entityTypeSpecs": { "description": "Required. Specifies EntityType grouping Features to read values of and settings.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestEntityTypeSpec" } }, "csvReadInstances": { "$ref": "GoogleCloudAiplatformV1beta1CsvSource", "description": "Each read instance consists of exactly one read timestamp and one or more entity IDs identifying entities of the corresponding EntityTypes whose Features are requested. Each output instance contains Feature values of requested entities concatenated together as of the read time. An example read instance may be `foo_entity_id, bar_entity_id, 2020-01-01T10:00:00.123Z`. An example output instance may be `foo_entity_id, bar_entity_id, 2020-01-01T10:00:00.123Z, foo_entity_feature1_value, bar_entity_feature2_value`. Timestamp in each read instance must be millisecond-aligned. `csv_read_instances` are read instances stored in a plain-text CSV file. The header should be: [ENTITY_TYPE_ID1], [ENTITY_TYPE_ID2], ..., timestamp The columns can be in any order. Values in the timestamp column must use the RFC 3339 format, e.g. `2012-07-30T10:43:17.123Z`." }, "bigqueryReadInstances": { "$ref": "GoogleCloudAiplatformV1beta1BigQuerySource", "description": "Similar to csv_read_instances, but from BigQuery source." }, "passThroughFields": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestPassThroughField" }, "description": "When not empty, the specified fields in the *_read_instances source will be joined as-is in the output, in addition to those fields from the Featurestore Entity. For BigQuery source, the type of the pass-through values will be automatically inferred. For CSV source, the pass-through values will be passed as opaque bytes." }, "startTime": { "description": "Optional. Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision.", "format": "google-datetime", "type": "string" } } }, "GoogleCloudAiplatformV1beta1MemoryGenerationTriggerConfig": { "description": "Represents configuration for triggering generation.", "properties": { "generationRule": { "$ref": "GoogleCloudAiplatformV1beta1MemoryGenerationTriggerConfigGenerationTriggerRule", "description": "Optional. Represents the active rule that determines when to flush the buffer. If not set, then the stream will be force flushed immediately." } }, "id": "GoogleCloudAiplatformV1beta1MemoryGenerationTriggerConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureOnlineStoreEmbeddingManagement": { "type": "object", "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreEmbeddingManagement", "deprecated": true, "description": "Deprecated: This sub message is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type. Contains settings for embedding management.", "properties": { "enabled": { "description": "Optional. Immutable. Whether to enable embedding management in this FeatureOnlineStore. It's immutable after creation to ensure the FeatureOnlineStore availability.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1BleuSpec": { "id": "GoogleCloudAiplatformV1beta1BleuSpec", "type": "object", "properties": { "useEffectiveOrder": { "description": "Optional. Whether to use_effective_order to compute bleu score.", "type": "boolean" } }, "description": "Spec for bleu score metric - calculates the precision of n-grams in the prediction as compared to reference - returns a score ranging between 0 to 1." }, "GoogleCloudAiplatformV1beta1ListModelDeploymentMonitoringJobsResponse": { "properties": { "modelDeploymentMonitoringJobs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob" }, "description": "A list of ModelDeploymentMonitoringJobs that matches the specified filter in the request." }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "description": "Response message for JobService.ListModelDeploymentMonitoringJobs.", "id": "GoogleCloudAiplatformV1beta1ListModelDeploymentMonitoringJobsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ExplanationSpecOverride": { "properties": { "parameters": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationParameters", "description": "The parameters to be overridden. Note that the attribution method cannot be changed. If not specified, no parameter is overridden." }, "examplesOverride": { "$ref": "GoogleCloudAiplatformV1beta1ExamplesOverride", "description": "The example-based explanations parameter overrides." }, "metadata": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataOverride", "description": "The metadata to be overridden. If not specified, no metadata is overridden." } }, "description": "The ExplanationSpec entries that can be overridden at online explanation time.", "id": "GoogleCloudAiplatformV1beta1ExplanationSpecOverride", "type": "object" }, "GoogleCloudAiplatformV1beta1SummaryMetrics": { "properties": { "totalItems": { "type": "integer", "format": "int32", "description": "Optional. The total number of items that were evaluated." }, "metrics": { "type": "object", "additionalProperties": { "type": "any" }, "description": "Optional. Map of metric name to metric value." }, "failedItems": { "format": "int32", "description": "Optional. The number of items that failed to be evaluated.", "type": "integer" } }, "description": "The summary metrics for the evaluation run.", "id": "GoogleCloudAiplatformV1beta1SummaryMetrics", "type": "object" }, "GoogleCloudAiplatformV1beta1StudySpecConvexStopConfig": { "type": "object", "description": "Configuration for ConvexStopPolicy.", "properties": { "autoregressiveOrder": { "description": "The number of Trial measurements used in autoregressive model for value prediction. A trial won't be considered early stopping if has fewer measurement points.", "format": "int64", "type": "string" }, "useSeconds": { "description": "This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_seconds==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_seconds==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.", "type": "boolean" }, "minNumSteps": { "type": "string", "format": "int64", "description": "Minimum number of steps for a trial to complete. Trials which do not have a measurement with num_steps \u003e min_num_steps won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_num_steps is set to be one-tenth of the max_num_steps. When use_steps is false, this field is set to the minimum elapsed seconds." }, "learningRateParameterName": { "description": "The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial.", "type": "string" }, "maxNumSteps": { "type": "string", "description": "Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. When use_steps is false, this field is set to the maximum elapsed seconds.", "format": "int64" } }, "id": "GoogleCloudAiplatformV1beta1StudySpecConvexStopConfig", "deprecated": true }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics", "type": "object", "properties": { "confidenceThreshold": { "format": "float", "description": "The confidence threshold value used to compute the metrics.", "type": "number" }, "mismatchRate": { "format": "float", "description": "Mismatch rate, which measures the tracking consistency, i.e. correctness of instance ID continuity.", "type": "number" }, "trackingPrecision": { "type": "number", "description": "Tracking precision.", "format": "float" }, "trackingRecall": { "format": "float", "description": "Tracking recall.", "type": "number" }, "boundingBoxIou": { "type": "number", "format": "float", "description": "Bounding box intersection-over-union precision. Measures how well the bounding boxes overlap between each other (e.g. complete overlap or just barely above iou_threshold)." } }, "description": "Metrics for a single confidence threshold." }, "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseFeatureDescriptor": { "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseFeatureDescriptor", "type": "object", "properties": { "id": { "description": "Feature ID.", "type": "string" } }, "description": "Metadata for requested Features." }, "GoogleCloudAiplatformV1beta1CometSpec": { "description": "Spec for Comet metric.", "properties": { "sourceLanguage": { "description": "Optional. Source language in BCP-47 format.", "type": "string" }, "version": { "type": "string", "enumDescriptions": [ "Comet version unspecified.", "Comet 22 for translation + source + reference (source-reference-combined)." ], "description": "Required. Which version to use for evaluation.", "enum": [ "COMET_VERSION_UNSPECIFIED", "COMET_22_SRC_REF" ] }, "targetLanguage": { "description": "Optional. Target language in BCP-47 format. Covers both prediction and reference.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1CometSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ListExampleStoresResponse": { "description": "Response message for ExampleStoreService.ListExampleStores.", "properties": { "exampleStores": { "description": "List of ExampleStore in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ExampleStore" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListExampleStoresRequest.page_token to obtain that page.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListExampleStoresResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1TaskOutput": { "description": "Represents the final output of a task.", "properties": { "artifacts": { "description": "Optional. A list of artifacts (files, data) produced by the task.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TaskArtifact" } } }, "id": "GoogleCloudAiplatformV1beta1TaskOutput", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecInlineSource": { "description": "Specifies source code provided as a byte stream.", "properties": { "sourceArchive": { "type": "string", "description": "Required. Input only. The application source code archive. It must be a compressed tarball (.tar.gz) file.", "format": "byte" } }, "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecInlineSource", "type": "object" }, "GoogleCloudAiplatformV1beta1MemoryTopicId": { "id": "GoogleCloudAiplatformV1beta1MemoryTopicId", "type": "object", "properties": { "customMemoryTopicLabel": { "description": "Optional. Represents the custom memory topic label.", "type": "string" }, "managedMemoryTopic": { "description": "Optional. Represents the managed memory topic.", "enum": [ "MANAGED_TOPIC_ENUM_UNSPECIFIED", "USER_PERSONAL_INFO", "USER_PREFERENCES", "KEY_CONVERSATION_DETAILS", "EXPLICIT_INSTRUCTIONS" ], "type": "string", "enumDescriptions": [ "Represents an unspecified topic. This value should not be used.", "Represents significant personal information about the User like first names, relationships, hobbies, important dates.", "Represents stated or implied likes, dislikes, preferred styles, or patterns.", "Represents important milestones or conclusions within the dialogue.", "Represents information that the user explicitly requested to remember or forget." ] } }, "description": "A memory topic identifier. This will be used to label a Memory and to restrict which topics are eligible for generation or retrieval." }, "GoogleCloudAiplatformV1beta1EvaluatedAnnotationExplanation": { "id": "GoogleCloudAiplatformV1beta1EvaluatedAnnotationExplanation", "type": "object", "properties": { "explanationType": { "description": "Explanation type. For AutoML Image Classification models, possible values are: * `image-integrated-gradients` * `image-xrai`", "type": "string" }, "explanation": { "$ref": "GoogleCloudAiplatformV1beta1Explanation", "description": "Explanation attribution response details." } }, "description": "Explanation result of the prediction produced by the Model." }, "GoogleCloudAiplatformV1beta1PredictResponse": { "properties": { "metadata": { "readOnly": true, "type": "any", "description": "Output only. Request-level metadata returned by the model. The metadata type will be dependent upon the model implementation." }, "deployedModelId": { "description": "ID of the Endpoint's DeployedModel that served this prediction.", "type": "string" }, "model": { "readOnly": true, "type": "string", "description": "Output only. The resource name of the Model which is deployed as the DeployedModel that this prediction hits." }, "modelVersionId": { "type": "string", "readOnly": true, "description": "Output only. The version ID of the Model which is deployed as the DeployedModel that this prediction hits." }, "modelDisplayName": { "description": "Output only. The display name of the Model which is deployed as the DeployedModel that this prediction hits.", "type": "string", "readOnly": true }, "predictions": { "type": "array", "items": { "type": "any" }, "description": "The predictions that are the output of the predictions call. The schema of any single prediction may be specified via Endpoint's DeployedModels' Model's PredictSchemata's prediction_schema_uri." } }, "description": "Response message for PredictionService.Predict.", "id": "GoogleCloudAiplatformV1beta1PredictResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1TaskDescriptionStrategy": { "id": "GoogleCloudAiplatformV1beta1TaskDescriptionStrategy", "type": "object", "description": "Defines a generation strategy based on a general task description.", "properties": { "taskDescription": { "description": "Required. A general description of the type of synthetic data you want to generate. For example, \"Generate customer reviews for a new smartphone.\"", "type": "string" } } }, "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailCustomJobDetail": { "description": "The detailed info for a custom job executor.", "properties": { "job": { "description": "Output only. The name of the CustomJob.", "readOnly": true, "type": "string" }, "failedJobs": { "description": "Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.", "readOnly": true, "type": "array", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailCustomJobDetail", "type": "object" }, "GoogleCloudAiplatformV1beta1TaskMessage": { "properties": { "parts": { "description": "Required. The parts of the message.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Part" } }, "role": { "description": "Required. The role of the sender of the message. e.g. \"user\", \"agent\"", "type": "string" }, "metadata": { "description": "Optional. A2A message may have extension_uris or reference_task_ids. They will be stored under metadata.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "messageId": { "description": "Required. The unique identifier of the message.", "type": "string" } }, "description": "Represents a single message in a conversation, compliant with the A2A specification.", "id": "GoogleCloudAiplatformV1beta1TaskMessage", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateTensorboardOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for Tensorboard." } }, "description": "Details of operations that perform create Tensorboard.", "id": "GoogleCloudAiplatformV1beta1CreateTensorboardOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateNotebookRuntimeTemplateOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateNotebookRuntimeTemplateOperationMetadata", "type": "object", "description": "Metadata information for NotebookService.CreateNotebookRuntimeTemplate.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The operation generic information." } } }, "GoogleTypeInterval": { "id": "GoogleTypeInterval", "type": "object", "properties": { "startTime": { "type": "string", "format": "google-datetime", "description": "Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start." }, "endTime": { "type": "string", "format": "google-datetime", "description": "Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end." } }, "description": "Represents a time interval, encoded as a Timestamp start (inclusive) and a Timestamp end (exclusive). The start must be less than or equal to the end. When the start equals the end, the interval is empty (matches no time). When both start and end are unspecified, the interval matches any time." }, "GoogleTypeDate": { "description": "Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values. * A month and day, with a zero year (for example, an anniversary). * A year on its own, with a zero month and a zero day. * A year and month, with a zero day (for example, a credit card expiration date). Related types: * google.type.TimeOfDay * google.type.DateTime * google.protobuf.Timestamp", "properties": { "month": { "format": "int32", "description": "Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.", "type": "integer" }, "year": { "description": "Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.", "format": "int32", "type": "integer" }, "day": { "format": "int32", "description": "Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn't significant.", "type": "integer" } }, "id": "GoogleTypeDate", "type": "object" }, "GoogleCloudAiplatformV1beta1DeployModelResponse": { "id": "GoogleCloudAiplatformV1beta1DeployModelResponse", "type": "object", "properties": { "deployedModel": { "$ref": "GoogleCloudAiplatformV1beta1DeployedModel", "description": "The DeployedModel that had been deployed in the Endpoint." } }, "description": "Response message for EndpointService.DeployModel." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtraction": { "description": "A TrainingJob that trains and uploads an AutoML Text Extraction Model.", "properties": { "inputs": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs", "description": "The input parameters of this TrainingJob." } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtraction", "type": "object" }, "GoogleCloudAiplatformV1beta1MutateDeployedIndexOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1MutateDeployedIndexOperationMetadata", "type": "object", "description": "Runtime operation information for IndexEndpointService.MutateDeployedIndex.", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" }, "deployedIndexId": { "description": "The unique index id specified by user", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSlice": { "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSlice", "type": "object", "description": "Definition of a slice.", "properties": { "dimension": { "description": "Output only. The dimension of the slice. Well-known dimensions are: * `annotationSpec`: This slice is on the test data that has either ground truth or prediction with AnnotationSpec.display_name equals to value. * `slice`: This slice is a user customized slice defined by its SliceSpec.", "readOnly": true, "type": "string" }, "sliceSpec": { "description": "Output only. Specification for how the data was sliced.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpec" }, "value": { "type": "string", "readOnly": true, "description": "Output only. The value of the dimension in this slice." } } }, "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseInput": { "id": "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseInput", "type": "object", "description": "Instances and metric spec for TrajectorySingleToolUse metric.", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseSpec", "description": "Required. Spec for TrajectorySingleToolUse metric." }, "instances": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseInstance" }, "description": "Required. Repeated TrajectorySingleToolUse instance." } } }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetrics": { "description": "Metrics for classification evaluation results.", "properties": { "auPrc": { "type": "number", "format": "float", "description": "The Area Under Precision-Recall Curve metric. Micro-averaged for the overall evaluation." }, "confusionMatrix": { "description": "Confusion matrix of the evaluation.", "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix" }, "confidenceMetrics": { "description": "Metrics for each `confidenceThreshold` in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and `positionThreshold` = INT32_MAX_VALUE. ROC and precision-recall curves, and other aggregated metrics are derived from them. The confidence metrics entries may also be supplied for additional values of `positionThreshold`, but from these no aggregated metrics are computed.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics" } }, "auRoc": { "description": "The Area Under Receiver Operating Characteristic curve metric. Micro-averaged for the overall evaluation.", "format": "float", "type": "number" }, "logLoss": { "description": "The Log Loss metric.", "format": "float", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetrics", "type": "object" }, "GoogleCloudAiplatformV1beta1StopNotebookRuntimeRequest": { "id": "GoogleCloudAiplatformV1beta1StopNotebookRuntimeRequest", "type": "object", "properties": {}, "description": "Request message for NotebookService.StopNotebookRuntime." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassification": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassification", "type": "object", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs" } }, "description": "A TrainingJob that trains and uploads an AutoML Video Classification Model." }, "GoogleCloudAiplatformV1beta1CreateMetadataStoreOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for creating a MetadataStore." } }, "description": "Details of operations that perform MetadataService.CreateMetadataStore.", "id": "GoogleCloudAiplatformV1beta1CreateMetadataStoreOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ThresholdConfig": { "properties": { "value": { "description": "Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.", "format": "double", "type": "number" } }, "description": "The config for feature monitoring threshold.", "id": "GoogleCloudAiplatformV1beta1ThresholdConfig", "type": "object" }, "CloudAiLargeModelsVisionRaiInfoDetectedLabels": { "description": "Filters returning list of deteceted labels, scores, and bounding boxes.", "properties": { "raiCategory": { "description": "The RAI category for the deteceted labels.", "type": "string" }, "entities": { "description": "The list of detected entities for the rai signal.", "type": "array", "items": { "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity" } } }, "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabels", "type": "object" }, "GoogleCloudAiplatformV1beta1MetadataList": { "description": "List representation in metadata.", "properties": { "values": { "description": "The values of `LIST` data type metadata.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MetadataValue" } } }, "id": "GoogleCloudAiplatformV1beta1MetadataList", "type": "object" }, "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlModelConfig": { "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlModelConfig", "type": "object", "properties": { "model": { "description": "Required. Full resource name of automl Model. Format: `projects/{project}/locations/{location}/models/{model}`.", "type": "string" }, "modelDisplayName": { "description": "Optional. Display name of the model in Vertex AI. System will pick a display name if unspecified.", "type": "string" } }, "description": "Config for migrating Model in automl.googleapis.com to Vertex AI's Model." }, "GoogleCloudAiplatformV1beta1GenerationConfigThinkingConfig": { "id": "GoogleCloudAiplatformV1beta1GenerationConfigThinkingConfig", "type": "object", "description": "Configuration for the model's thinking features. \"Thinking\" is a process where the model breaks down a complex task into smaller, manageable steps. This allows the model to reason about the task, plan its approach, and execute the plan to generate a high-quality response.", "properties": { "thinkingLevel": { "enum": [ "THINKING_LEVEL_UNSPECIFIED", "LOW", "MEDIUM", "HIGH", "MINIMAL" ], "description": "Optional. The number of thoughts tokens that the model should generate.", "type": "string", "enumDescriptions": [ "Unspecified thinking level.", "Low thinking level.", "Medium thinking level.", "High thinking level.", "MINIMAL thinking level." ] }, "includeThoughts": { "description": "Optional. If true, the model will include its thoughts in the response. \"Thoughts\" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available.", "type": "boolean" }, "thinkingBudget": { "type": "integer", "format": "int32", "description": "Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency." } } }, "GoogleCloudAiplatformV1beta1ToolUseExample": { "id": "GoogleCloudAiplatformV1beta1ToolUseExample", "type": "object", "description": "A single example of the tool usage.", "properties": { "responseSummary": { "description": "Summary of the tool response to the user query.", "type": "string" }, "extensionOperation": { "description": "Extension operation to call.", "$ref": "GoogleCloudAiplatformV1beta1ToolUseExampleExtensionOperation" }, "requestParams": { "description": "Request parameters used for executing this tool.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "functionName": { "description": "Function name to call.", "type": "string" }, "responseParams": { "description": "Response parameters generated by this tool.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "displayName": { "description": "Required. The display name for example.", "type": "string" }, "query": { "description": "Required. Query that should be routed to this tool.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ExplainResponse": { "description": "Response message for PredictionService.Explain.", "properties": { "explanations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Explanation" }, "description": "The explanations of the Model's PredictResponse.predictions. It has the same number of elements as instances to be explained." }, "predictions": { "description": "The predictions that are the output of the predictions call. Same as PredictResponse.predictions.", "type": "array", "items": { "type": "any" } }, "concurrentExplanations": { "description": "This field stores the results of the explanations run in parallel with The default explanation strategy/method.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation" } }, "deployedModelId": { "description": "ID of the Endpoint's DeployedModel that served this explanation.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ExplainResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecRange": { "properties": { "low": { "description": "Inclusive low value for the range.", "format": "float", "type": "number" }, "high": { "type": "number", "description": "Exclusive high value for the range.", "format": "float" } }, "description": "A range of values for slice(s). `low` is inclusive, `high` is exclusive.", "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecRange", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolGoogleSearch": { "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearch", "type": "object", "properties": { "excludeDomains": { "description": "Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: [\"amazon.com\", \"facebook.com\"].", "type": "array", "items": { "type": "string" } }, "blockingConfidence": { "enum": [ "PHISH_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_HIGH_AND_ABOVE", "BLOCK_HIGHER_AND_ABOVE", "BLOCK_VERY_HIGH_AND_ABOVE", "BLOCK_ONLY_EXTREMELY_HIGH" ], "description": "Optional. Sites with confidence level chosen & above this value will be blocked from the search results.", "type": "string", "enumDescriptions": [ "Defaults to unspecified.", "Blocks Low and above confidence URL that is risky.", "Blocks Medium and above confidence URL that is risky.", "Blocks High and above confidence URL that is risky.", "Blocks Higher and above confidence URL that is risky.", "Blocks Very high and above confidence URL that is risky.", "Blocks Extremely high confidence URL that is risky." ] }, "searchTypes": { "$ref": "GoogleCloudAiplatformV1beta1ToolGoogleSearchSearchTypes", "description": "Optional. The set of search types to enable. If not set, web search is enabled by default." } }, "description": "GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google." }, "GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricGenerationSpec": { "id": "GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricGenerationSpec", "type": "object", "properties": { "modelConfig": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigAutoraterConfig", "description": "Optional. Configuration for the model used in rubric generation. Configs including sampling count and base model can be specified here. Flipping is not supported for rubric generation." }, "promptTemplate": { "description": "Optional. Template for the prompt used to generate rubrics. The details should be updated based on the most-recent recipe requirements.", "type": "string" }, "rubricContentType": { "description": "Optional. The type of rubric content to be generated.", "enum": [ "RUBRIC_CONTENT_TYPE_UNSPECIFIED", "PROPERTY", "NL_QUESTION_ANSWER", "PYTHON_CODE_ASSERTION" ], "type": "string", "enumDescriptions": [ "The content type to generate is not specified.", "Generate rubrics based on properties.", "Generate rubrics in an NL question answer format.", "Generate rubrics in a unit test format." ] }, "rubricTypeOntology": { "type": "array", "items": { "type": "string" }, "description": "Optional. An optional, pre-defined list of allowed types for generated rubrics. If this field is provided, it implies `include_rubric_type` should be true, and the generated rubric types should be chosen from this ontology." }, "metricResourceName": { "description": "Optional. Resource name of the metric definition.", "type": "string" } }, "description": "Specification for how rubrics should be generated." }, "GoogleCloudAiplatformV1beta1TrajectoryPrecisionInput": { "id": "GoogleCloudAiplatformV1beta1TrajectoryPrecisionInput", "type": "object", "properties": { "metricSpec": { "description": "Required. Spec for TrajectoryPrecision metric.", "$ref": "GoogleCloudAiplatformV1beta1TrajectoryPrecisionSpec" }, "instances": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryPrecisionInstance" }, "description": "Required. Repeated TrajectoryPrecision instance." } }, "description": "Instances and metric spec for TrajectoryPrecision metric." }, "GoogleCloudAiplatformV1beta1ImageConfig": { "id": "GoogleCloudAiplatformV1beta1ImageConfig", "type": "object", "description": "Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people.", "properties": { "aspectRatio": { "description": "Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: \"1:1\" \"2:3\", \"3:2\" \"3:4\", \"4:3\" \"4:5\", \"5:4\" \"9:16\", \"16:9\" \"21:9\"", "type": "string" }, "prominentPeople": { "type": "string", "enumDescriptions": [ "Unspecified value. The model will proceed with the default behavior, which is to allow generation of prominent people.", "Allows the model to generate images of prominent people.", "Prevents the model from generating images of prominent people." ], "enum": [ "PROMINENT_PEOPLE_UNSPECIFIED", "ALLOW_PROMINENT_PEOPLE", "BLOCK_PROMINENT_PEOPLE" ], "description": "Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people." }, "imageOutputOptions": { "$ref": "GoogleCloudAiplatformV1beta1ImageConfigImageOutputOptions", "description": "Optional. The image output format for generated images." }, "imageSize": { "description": "Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.", "type": "string" }, "personGeneration": { "enum": [ "PERSON_GENERATION_UNSPECIFIED", "ALLOW_ALL", "ALLOW_ADULT", "ALLOW_NONE" ], "description": "Optional. Controls whether the model can generate people.", "type": "string", "enumDescriptions": [ "The default behavior is unspecified. The model will decide whether to generate images of people.", "Allows the model to generate images of people, including adults and children.", "Allows the model to generate images of adults, but not children.", "Prevents the model from generating images of people." ] } } }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentSnapshot": { "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSnapshot", "type": "object", "properties": { "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. The timestamp when this SandboxEnvironment was most recently updated." }, "sourceSandboxEnvironment": { "description": "Required. The resource name of the source SandboxEnvironment this snapshot was taken from.", "type": "string" }, "parentSnapshot": { "description": "Output only. The resource name of the parent SandboxEnvironmentSnapshot. Empty if this is a root Snapshot (the first snapshot from a newly created sandbox). Can be used to reconstruct the whole ancestry tree of snapshots.", "type": "string", "readOnly": true }, "name": { "description": "Identifier. The resource name of the SandboxEnvironmentSnapshot. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentSnapshots/{sandbox_environment_snapshot}`", "type": "string" }, "owner": { "description": "Optional. Owner information for this sandbox snapshot. Different owners will have isolations on snapshot storage and identity. If not set, snapshot will be created as the default owner.", "type": "string" }, "createTime": { "format": "google-datetime", "description": "Output only. The timestamp when this SandboxEnvironmentSnapshot was created.", "readOnly": true, "type": "string" }, "expireTime": { "type": "string", "description": "Optional. Timestamp in UTC of when this SandboxEnvironmentSnapshot is considered expired. This is *always* provided on output, regardless of what `expiration` was sent on input.", "format": "google-datetime" }, "ttl": { "description": "Optional. Input only. The TTL for the sandbox environment snapshot. The expiration time is computed: now + TTL.", "format": "google-duration", "type": "string" }, "postSnapshotAction": { "description": "Optional. Input only. Action to take on the source SandboxEnvironment after the snapshot is taken. This field is only used in CreateSandboxEnvironmentSnapshotRequest and it is not stored in the resource.", "enum": [ "POST_SNAPSHOT_ACTION_UNSPECIFIED", "RUNNING", "PAUSE" ], "type": "string", "enumDescriptions": [ "The default value. This value is unused.", "Sandbox environment will continue to run after snapshot is taken.", "Sandbox environment will be paused after snapshot is taken." ] }, "displayName": { "description": "Required. The display name of the SandboxEnvironmentSnapshot.", "type": "string" }, "sizeBytes": { "readOnly": true, "type": "string", "format": "int64", "description": "Optional. Output only. Size of the snapshot data in bytes." } }, "description": "SandboxEnvironmentSnapshot is a snapshot of the SandboxEnvironment." }, "GoogleCloudAiplatformV1beta1ReadTensorboardBlobDataResponse": { "id": "GoogleCloudAiplatformV1beta1ReadTensorboardBlobDataResponse", "type": "object", "properties": { "blobs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardBlob" }, "description": "Blob messages containing blob bytes." } }, "description": "Response message for TensorboardService.ReadTensorboardBlobData." }, "GoogleCloudAiplatformV1beta1RougeMetricValue": { "properties": { "score": { "type": "number", "readOnly": true, "description": "Output only. Rouge score.", "format": "float" } }, "description": "Rouge metric value for an instance.", "id": "GoogleCloudAiplatformV1beta1RougeMetricValue", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateSyntheticDataResponse": { "id": "GoogleCloudAiplatformV1beta1GenerateSyntheticDataResponse", "type": "object", "properties": { "syntheticExamples": { "description": "A list of generated synthetic examples, each containing a complete synthetic data instance generated based on your request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SyntheticExample" } } }, "description": "The response message for the `GenerateSyntheticData` method, containing the synthetic examples generated by the Gen AI evaluation service." }, "GoogleCloudAiplatformV1beta1CreateRagDataSchemaRequest": { "properties": { "ragDataSchema": { "$ref": "GoogleCloudAiplatformV1beta1RagDataSchema", "description": "Required. The RagDataSchema to create." }, "ragDataSchemaId": { "description": "Optional. The ID to use for the RagDataSchema, which will become the final component of the RagDataSchema's resource name if the user chooses to specify. Otherwise, RagDataSchema id will be generated by system. This value should be up to 63 characters, and valid characters are /a-z-/. The first character must be a letter, the last could be a letter or a number.", "type": "string" }, "parent": { "description": "Required. The resource name of the RagCorpus to create the RagDataSchema in. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "type": "string" } }, "description": "Request message for VertexRagDataService.CreateRagDataSchema.", "id": "GoogleCloudAiplatformV1beta1CreateRagDataSchemaRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1AuthConfigOauthConfig": { "description": "Config for user oauth.", "properties": { "accessToken": { "description": "Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.", "type": "string" }, "serviceAccount": { "description": "The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1AuthConfigOauthConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1RagFileChunkingConfigFixedLengthChunking": { "id": "GoogleCloudAiplatformV1beta1RagFileChunkingConfigFixedLengthChunking", "type": "object", "description": "Specifies the fixed length chunking config.", "properties": { "chunkSize": { "type": "integer", "format": "int32", "description": "The size of the chunks." }, "chunkOverlap": { "type": "integer", "description": "The overlap between chunks.", "format": "int32" } } }, "GoogleCloudAiplatformV1beta1PrivateEndpoints": { "id": "GoogleCloudAiplatformV1beta1PrivateEndpoints", "type": "object", "description": "PrivateEndpoints proto is used to provide paths for users to send requests privately. To send request via private service access, use predict_http_uri, explain_http_uri or health_http_uri. To send request via private service connect, use service_attachment.", "properties": { "healthHttpUri": { "description": "Output only. Http(s) path to send health check requests.", "type": "string", "readOnly": true }, "serviceAttachment": { "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled.", "type": "string", "readOnly": true }, "predictHttpUri": { "type": "string", "readOnly": true, "description": "Output only. Http(s) path to send prediction requests." }, "explainHttpUri": { "description": "Output only. Http(s) path to send explain requests.", "readOnly": true, "type": "string" } } }, "GoogleCloudAiplatformV1beta1FullFineTuningSpec": { "properties": { "trainingDatasetUri": { "description": "Required. Training dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset.", "type": "string" }, "validationDatasetUri": { "description": "Optional. Validation dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset.", "type": "string" }, "hyperParameters": { "description": "Optional. Hyperparameters for Full Fine Tuning.", "$ref": "GoogleCloudAiplatformV1beta1SupervisedHyperParameters" } }, "description": "Tuning Spec for Full Fine Tuning.", "id": "GoogleCloudAiplatformV1beta1FullFineTuningSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1SamplingStrategyRandomSampleConfig": { "id": "GoogleCloudAiplatformV1beta1SamplingStrategyRandomSampleConfig", "type": "object", "description": "Requests are randomly selected.", "properties": { "sampleRate": { "description": "Sample rate (0, 1]", "format": "double", "type": "number" } } }, "GoogleCloudAiplatformV1beta1PublisherModel": { "id": "GoogleCloudAiplatformV1beta1PublisherModel", "type": "object", "description": "A Model Garden Publisher Model.", "properties": { "predictSchemata": { "description": "Optional. The schemata that describes formats of the PublisherModel's predictions and explanations as given and returned via PredictionService.Predict.", "$ref": "GoogleCloudAiplatformV1beta1PredictSchemata" }, "openSourceCategory": { "type": "string", "enumDescriptions": [ "The open source category is unspecified, which should not be used.", "Used to indicate the PublisherModel is not open sourced.", "Used to indicate the PublisherModel is a Google-owned open source model w/ Google checkpoint.", "Used to indicate the PublisherModel is a 3p-owned open source model w/ Google checkpoint.", "Used to indicate the PublisherModel is a Google-owned pure open source model.", "Used to indicate the PublisherModel is a 3p-owned pure open source model." ], "enum": [ "OPEN_SOURCE_CATEGORY_UNSPECIFIED", "PROPRIETARY", "GOOGLE_OWNED_OSS_WITH_GOOGLE_CHECKPOINT", "THIRD_PARTY_OWNED_OSS_WITH_GOOGLE_CHECKPOINT", "GOOGLE_OWNED_OSS", "THIRD_PARTY_OWNED_OSS" ], "description": "Required. Indicates the open source category of the publisher model." }, "versionId": { "description": "Output only. Immutable. The version ID of the PublisherModel. A new version is committed when a new model version is uploaded under an existing model id. It is an auto-incrementing decimal number in string representation.", "type": "string", "readOnly": true }, "frameworks": { "type": "array", "items": { "type": "string" }, "description": "Optional. Additional information about the model's Frameworks." }, "supportedActions": { "description": "Optional. Supported call-to-action options.", "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToAction" }, "launchStage": { "description": "Optional. Indicates the launch stage of the model.", "enum": [ "LAUNCH_STAGE_UNSPECIFIED", "EXPERIMENTAL", "PRIVATE_PREVIEW", "PUBLIC_PREVIEW", "GA" ], "type": "string", "enumDescriptions": [ "The model launch stage is unspecified.", "Used to indicate the PublisherModel is at Experimental launch stage, available to a small set of customers.", "Used to indicate the PublisherModel is at Private Preview launch stage, only available to a small set of customers, although a larger set of customers than an Experimental launch. Previews are the first launch stage used to get feedback from customers.", "Used to indicate the PublisherModel is at Public Preview launch stage, available to all customers, although not supported for production workloads.", "Used to indicate the PublisherModel is at GA launch stage, available to all customers and ready for production workload." ] }, "name": { "readOnly": true, "type": "string", "description": "Output only. Identifier. The resource name of the PublisherModel." }, "parent": { "description": "Optional. The parent that this model was customized from. E.g., Vision API, Natural Language API, LaMDA, T5, etc. Foundation models don't have parents.", "$ref": "GoogleCloudAiplatformV1beta1PublisherModelParent" }, "publisherModelTemplate": { "type": "string", "readOnly": true, "description": "Optional. Output only. Immutable. Used to indicate this model has a publisher model and provide the template of the publisher model resource name." }, "versionState": { "description": "Optional. Indicates the state of the model version.", "enum": [ "VERSION_STATE_UNSPECIFIED", "VERSION_STATE_STABLE", "VERSION_STATE_UNSTABLE" ], "type": "string", "enumDescriptions": [ "The version state is unspecified.", "Used to indicate the version is stable.", "Used to indicate the version is unstable." ] } } }, "GoogleCloudAiplatformV1beta1TrajectoryPrecisionSpec": { "properties": {}, "description": "Spec for TrajectoryPrecision metric - returns a float score based on average precision of individual tool calls.", "id": "GoogleCloudAiplatformV1beta1TrajectoryPrecisionSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobRequest": { "id": "GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobRequest", "type": "object", "description": "Request message for [NotebookService.CreateNotebookExecutionJob]", "properties": { "notebookExecutionJob": { "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJob", "description": "Required. The NotebookExecutionJob to create." }, "parent": { "description": "Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`", "type": "string" }, "notebookExecutionJobId": { "description": "Optional. User specified ID for the NotebookExecutionJob.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1DnsPeeringConfig": { "description": "DNS peering configuration. These configurations are used to create DNS peering zones in the Vertex tenant project VPC, enabling resolution of records within the specified domain hosted in the target network's Cloud DNS.", "properties": { "domain": { "description": "Required. The DNS name suffix of the zone being peered to, e.g., \"my-internal-domain.corp.\". Must end with a dot.", "type": "string" }, "targetProject": { "description": "Required. The project ID hosting the Cloud DNS managed zone that contains the 'domain'. The Vertex AI Service Agent requires the dns.peer role on this project.", "type": "string" }, "targetNetwork": { "description": "Required. The VPC network name in the target_project where the DNS zone specified by 'domain' is visible.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1DnsPeeringConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigHybridSearchConfig": { "description": "Config for hybrid search.", "properties": { "sparseEmbeddingConfig": { "description": "Optional. The configuration for sparse embedding generation. This field is optional the default behavior depends on the vector database choice on the RagCorpus.", "$ref": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigSparseEmbeddingConfig" }, "denseEmbeddingModelPredictionEndpoint": { "description": "Required. The Vertex AI Prediction Endpoint that hosts the embedding model for dense embedding generations.", "$ref": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigVertexPredictionEndpoint" } }, "id": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigHybridSearchConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1GenericOperationMetadata": { "properties": { "createTime": { "type": "string", "readOnly": true, "description": "Output only. Time when the operation was created.", "format": "google-datetime" }, "partialFailures": { "type": "array", "items": { "$ref": "GoogleRpcStatus" }, "readOnly": true, "description": "Output only. Partial failures encountered. E.g. single files that couldn't be read. This field should never exceed 20 entries. Status details field will contain standard Google Cloud error details." }, "updateTime": { "description": "Output only. Time when the operation was updated for the last time. If the operation has finished (successfully or not), this is the finish time.", "format": "google-datetime", "type": "string", "readOnly": true } }, "description": "Generic Metadata shared by all operations.", "id": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ExecutableCode": { "id": "GoogleCloudAiplatformV1beta1ExecutableCode", "type": "object", "description": "Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated.", "properties": { "language": { "type": "string", "enumDescriptions": [ "Unspecified language. This value should not be used.", "Python \u003e= 3.10, with numpy and simpy available." ], "description": "Required. Programming language of the `code`.", "enum": [ "LANGUAGE_UNSPECIFIED", "PYTHON" ] }, "code": { "description": "Required. The code to be executed.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadata", "type": "object", "properties": { "inputConfig": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataInputConfig" } }, "description": "The metadata of Datasets that contain tables data." }, "GoogleCloudAiplatformV1beta1RawPredictRequest": { "description": "Request message for PredictionService.RawPredict.", "properties": { "httpBody": { "description": "The prediction input. Supports HTTP headers and arbitrary data payload. A DeployedModel may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the RawPredict method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the predict_schemata.instance_schema_uri field when you create a Model. This schema applies when you deploy the `Model` as a `DeployedModel` to an Endpoint and use the `RawPredict` method.", "$ref": "GoogleApiHttpBody" } }, "id": "GoogleCloudAiplatformV1beta1RawPredictRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringBigQueryTable": { "id": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringBigQueryTable", "type": "object", "description": "ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table.", "properties": { "requestResponseLoggingSchemaVersion": { "readOnly": true, "type": "string", "description": "Output only. The schema version of the request/response logging BigQuery table. Default to v1 if unset." }, "logType": { "type": "string", "enumDescriptions": [ "Unspecified type.", "Predict logs.", "Explain logs." ], "description": "The type of log.", "enum": [ "LOG_TYPE_UNSPECIFIED", "PREDICT", "EXPLAIN" ] }, "logSource": { "type": "string", "enumDescriptions": [ "Unspecified source.", "Logs coming from Training dataset.", "Logs coming from Serving traffic." ], "enum": [ "LOG_SOURCE_UNSPECIFIED", "TRAINING", "SERVING" ], "description": "The source of log." }, "bigqueryTablePath": { "description": "The created BigQuery table to store logs. Customer could do their own query & analysis. Format: `bq://.model_deployment_monitoring_._`", "type": "string" } } }, "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigSparseEmbeddingConfigBm25": { "id": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigSparseEmbeddingConfigBm25", "type": "object", "properties": { "b": { "type": "number", "format": "float", "description": "Optional. The parameter to control document length normalization. It determines how much the document length affects the final score. b is in the range of [0, 1]. The default value is 0.75." }, "multilingual": { "description": "Optional. Use multilingual tokenizer if set to true.", "type": "boolean" }, "k1": { "description": "Optional. The parameter to control term frequency saturation. It determines the scaling between the matching term frequency and final score. k1 is in the range of [1.2, 3]. The default value is 1.2.", "format": "float", "type": "number" } }, "description": "Message for BM25 parameters." }, "GoogleCloudAiplatformV1beta1CreateFeaturestoreOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateFeaturestoreOperationMetadata", "type": "object", "description": "Details of operations that perform create Featurestore.", "properties": { "genericMetadata": { "description": "Operation metadata for Featurestore.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1beta1ExportDataRequest": { "id": "GoogleCloudAiplatformV1beta1ExportDataRequest", "type": "object", "properties": { "exportConfig": { "description": "Required. The desired output location.", "$ref": "GoogleCloudAiplatformV1beta1ExportDataConfig" } }, "description": "Request message for DatasetService.ExportData." }, "GoogleCloudAiplatformV1beta1AnnotationSpec": { "properties": { "name": { "description": "Output only. Resource name of the AnnotationSpec.", "type": "string", "readOnly": true }, "updateTime": { "description": "Output only. Timestamp when AnnotationSpec was last updated.", "format": "google-datetime", "type": "string", "readOnly": true }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "displayName": { "description": "Required. The user-defined name of the AnnotationSpec. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this AnnotationSpec was created." } }, "description": "Identifies a concept with which DataItems may be annotated with.", "id": "GoogleCloudAiplatformV1beta1AnnotationSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition": { "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition", "type": "object", "properties": { "values": { "type": "array", "items": { "type": "number", "format": "double" }, "description": "Required. Matches values of the parent parameter of 'DISCRETE' type. All values must exist in `discrete_value_spec` of parent parameter. The Epsilon of the value matching is 1e-10." } }, "description": "Represents the spec to match discrete values from parent parameter." }, "GoogleCloudAiplatformV1beta1GenAiAdvancedFeaturesConfigRagConfig": { "description": "Configuration for Retrieval Augmented Generation feature.", "properties": { "enableRag": { "description": "If true, enable Retrieval Augmented Generation in ChatCompletion request. Once enabled, the endpoint will be identified as GenAI endpoint and Arthedain router will be used.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1GenAiAdvancedFeaturesConfigRagConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1PurgeContextsRequest": { "id": "GoogleCloudAiplatformV1beta1PurgeContextsRequest", "type": "object", "description": "Request message for MetadataService.PurgeContexts.", "properties": { "filter": { "description": "Required. A required filter matching the Contexts to be purged. E.g., `update_time \u003c= 2020-11-19T11:30:00-04:00`.", "type": "string" }, "force": { "description": "Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Context names that would be deleted.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1MutateDeployedModelRequest": { "id": "GoogleCloudAiplatformV1beta1MutateDeployedModelRequest", "type": "object", "description": "Request message for EndpointService.MutateDeployedModel.", "properties": { "deployedModel": { "$ref": "GoogleCloudAiplatformV1beta1DeployedModel", "description": "Required. The DeployedModel to be mutated within the Endpoint. Only the following fields can be mutated: * `min_replica_count` in either DedicatedResources or AutomaticResources * `max_replica_count` in either DedicatedResources or AutomaticResources * `required_replica_count` in DedicatedResources * autoscaling_metric_specs * `disable_container_logging` (v1 only) * `enable_container_logging` (v1beta1 only) * `scale_to_zero_spec` in DedicatedResources (v1beta1 only) * `initial_replica_count` in DedicatedResources (v1beta1 only)" }, "updateMask": { "type": "string", "format": "google-fieldmask", "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask." } } }, "GoogleCloudAiplatformV1beta1ExplanationMetadataOverride": { "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataOverride", "type": "object", "properties": { "inputs": { "description": "Required. Overrides the input metadata of the features. The key is the name of the feature to be overridden. The keys specified here must exist in the input metadata to be overridden. If a feature is not specified here, the corresponding feature's input metadata is not overridden.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataOverrideInputMetadataOverride" } } }, "description": "The ExplanationMetadata entries that can be overridden at online explanation time." }, "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataTools": { "id": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataTools", "type": "object", "description": "Deprecated: Use `agent_eval_data` instead. Represents a list of tools for an agent.", "properties": { "tool": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" }, "deprecated": true, "description": "Optional. List of tools: each tool can have multiple function declarations." } } }, "GoogleCloudAiplatformV1beta1SampleConfig": { "properties": { "initialBatchSamplePercentage": { "type": "integer", "description": "The percentage of data needed to be labeled in the first batch.", "format": "int32" }, "sampleStrategy": { "enum": [ "SAMPLE_STRATEGY_UNSPECIFIED", "UNCERTAINTY" ], "description": "Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.", "type": "string", "enumDescriptions": [ "Default will be treated as UNCERTAINTY.", "Sample the most uncertain data to label." ] }, "followingBatchSamplePercentage": { "description": "The percentage of data needed to be labeled in each following batch (except the first batch).", "format": "int32", "type": "integer" } }, "description": "Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.", "id": "GoogleCloudAiplatformV1beta1SampleConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1RayLogsSpec": { "properties": { "disabled": { "description": "Optional. Flag to disable the export of Ray OSS logs to Cloud Logging.", "type": "boolean" } }, "description": "Configuration for the Ray OSS Logs.", "id": "GoogleCloudAiplatformV1beta1RayLogsSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1RagContexts": { "id": "GoogleCloudAiplatformV1beta1RagContexts", "type": "object", "description": "Relevant contexts for one query.", "properties": { "contexts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RagContextsContext" }, "description": "All its contexts." } } }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsRegressionEvaluationMetrics": { "description": "Metrics for regression evaluation results.", "properties": { "rootMeanSquaredError": { "format": "float", "description": "Root Mean Squared Error (RMSE).", "type": "number" }, "meanAbsolutePercentageError": { "type": "number", "description": "Mean absolute percentage error. Infinity when there are zeros in the ground truth.", "format": "float" }, "rSquared": { "type": "number", "description": "Coefficient of determination as Pearson correlation coefficient. Undefined when ground truth or predictions are constant or near constant.", "format": "float" }, "meanAbsoluteError": { "format": "float", "description": "Mean Absolute Error (MAE).", "type": "number" }, "rootMeanSquaredLogError": { "type": "number", "format": "float", "description": "Root mean squared log error. Undefined when there are negative ground truth values or predictions." } }, "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsRegressionEvaluationMetrics", "type": "object" }, "GoogleCloudAiplatformV1beta1CancelDataLabelingJobRequest": { "id": "GoogleCloudAiplatformV1beta1CancelDataLabelingJobRequest", "type": "object", "properties": {}, "description": "Request message for JobService.CancelDataLabelingJob." }, "GoogleCloudAiplatformV1beta1LargeModelReference": { "id": "GoogleCloudAiplatformV1beta1LargeModelReference", "type": "object", "description": "Contains information about the Large Model.", "properties": { "name": { "description": "Required. The unique name of the large Foundation or pre-built model. Like \"chat-bison\", \"text-bison\". Or model name with version ID, like \"chat-bison@001\", \"text-bison@005\", etc.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricBasedMetricSpecRepeatedRubrics": { "id": "GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricBasedMetricSpecRepeatedRubrics", "type": "object", "description": "Defines a list of rubrics, used when providing rubrics inline.", "properties": { "rubrics": { "description": "The list of rubrics.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Rubric" } } } }, "GoogleCloudAiplatformV1beta1FeatureStatsAndAnomaly": { "id": "GoogleCloudAiplatformV1beta1FeatureStatsAndAnomaly", "type": "object", "description": "Stats and Anomaly generated by FeatureMonitorJobs. Anomaly only includes Drift.", "properties": { "distributionDeviation": { "format": "double", "description": "Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.", "type": "number" }, "driftDetectionThreshold": { "type": "number", "description": "This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold", "format": "double" }, "statsTime": { "type": "string", "format": "google-datetime", "description": "The timestamp we take snapshot for feature values to generate stats." }, "featureStats": { "description": "Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.", "type": "any" }, "featureMonitorId": { "description": "The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.", "type": "string" }, "driftDetected": { "description": "If set to true, indicates current stats is detected as and comparing with baseline stats.", "type": "boolean" }, "featureMonitorJobId": { "type": "string", "format": "int64", "description": "The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly." }, "featureId": { "description": "Feature Id.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateRequest": { "id": "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateRequest", "type": "object", "description": "Request message for VizierService.CheckTrialEarlyStoppingState.", "properties": {} }, "GoogleCloudAiplatformV1beta1RagCorpus": { "id": "GoogleCloudAiplatformV1beta1RagCorpus", "type": "object", "properties": { "displayName": { "description": "Required. The display name of the RagCorpus. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "corpusStatus": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1CorpusStatus", "description": "Output only. RagCorpus state." }, "ragVectorDbConfig": { "description": "Optional. Immutable. The Vector DB config of the RagCorpus.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1RagVectorDbConfig" }, "vertexAiSearchConfig": { "description": "Optional. Immutable. The config for the Vertex AI Search.", "$ref": "GoogleCloudAiplatformV1beta1VertexAiSearchConfig" }, "corpusTypeConfig": { "description": "Optional. The corpus type config of the RagCorpus.", "$ref": "GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfig" }, "satisfiesPzi": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "satisfiesPzs": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "name": { "type": "string", "readOnly": true, "description": "Output only. The resource name of the RagCorpus." }, "vectorDbConfig": { "$ref": "GoogleCloudAiplatformV1beta1RagVectorDbConfig", "description": "Optional. Immutable. The config for the Vector DBs." }, "encryptionSpec": { "description": "Optional. Immutable. The CMEK key name used to encrypt at-rest data related to this Corpus. Only applicable to RagManagedDb option for Vector DB. This field can only be set at corpus creation time, and cannot be updated or deleted.", "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" }, "ragFilesCount": { "type": "integer", "readOnly": true, "description": "Output only. Number of RagFiles in the RagCorpus. NOTE: This field is not populated in the response of VertexRagDataService.ListRagCorpora.", "format": "int32" }, "createTime": { "description": "Output only. Timestamp when this RagCorpus was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "description": { "description": "Optional. The description of the RagCorpus.", "type": "string" }, "ragEmbeddingModelConfig": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfig", "description": "Optional. Immutable. The embedding model config of the RagCorpus." }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this RagCorpus was last updated.", "format": "google-datetime" } }, "description": "A RagCorpus is a RagFile container and a project can have multiple RagCorpora." }, "GoogleCloudAiplatformV1beta1ToolCallValidResults": { "id": "GoogleCloudAiplatformV1beta1ToolCallValidResults", "type": "object", "description": "Results for tool call valid metric.", "properties": { "toolCallValidMetricValues": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ToolCallValidMetricValue" }, "readOnly": true, "description": "Output only. Tool call valid metric values." } } }, "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDoubleValueSpec": { "description": "Value specification for a parameter in `DOUBLE` type.", "properties": { "maxValue": { "type": "number", "description": "Required. Inclusive maximum value of the parameter.", "format": "double" }, "defaultValue": { "type": "number", "format": "double", "description": "A default value for a `DOUBLE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline." }, "minValue": { "type": "number", "format": "double", "description": "Required. Inclusive minimum value of the parameter." } }, "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDoubleValueSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1StudySpecParameterSpec": { "properties": { "doubleValueSpec": { "description": "The value spec for a 'DOUBLE' parameter.", "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDoubleValueSpec" }, "parameterId": { "description": "Required. The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs.", "type": "string" }, "integerValueSpec": { "description": "The value spec for an 'INTEGER' parameter.", "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecIntegerValueSpec" }, "categoricalValueSpec": { "description": "The value spec for a 'CATEGORICAL' parameter.", "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecCategoricalValueSpec" }, "scaleType": { "type": "string", "enumDescriptions": [ "By default, no scaling is applied.", "Scales the feasible space to (0, 1) linearly.", "Scales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.", "Scales the feasible space \"reverse\" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive." ], "enum": [ "SCALE_TYPE_UNSPECIFIED", "UNIT_LINEAR_SCALE", "UNIT_LOG_SCALE", "UNIT_REVERSE_LOG_SCALE" ], "description": "How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters." }, "conditionalParameterSpecs": { "description": "A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition. If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpec" } }, "discreteValueSpec": { "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDiscreteValueSpec", "description": "The value spec for a 'DISCRETE' parameter." } }, "description": "Represents a single parameter to optimize.", "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ExtensionManifest": { "id": "GoogleCloudAiplatformV1beta1ExtensionManifest", "type": "object", "description": "Manifest spec of an Extension needed for runtime execution.", "properties": { "name": { "description": "Required. Extension name shown to the LLM. The name can be up to 128 characters long.", "type": "string" }, "description": { "description": "Required. The natural language description shown to the LLM. It should describe the usage of the extension, and is essential for the LLM to perform reasoning. e.g., if the extension is a data store, you can let the LLM know what data it contains.", "type": "string" }, "apiSpec": { "$ref": "GoogleCloudAiplatformV1beta1ExtensionManifestApiSpec", "description": "Required. Immutable. The API specification shown to the LLM." }, "authConfig": { "$ref": "GoogleCloudAiplatformV1beta1AuthConfig", "description": "Required. Immutable. Type of auth supported by this extension." } } }, "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityView": { "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityView", "type": "object", "properties": { "entityId": { "description": "ID of the requested entity.", "type": "string" }, "data": { "description": "Each piece of data holds the k requested values for one requested Feature. If no values for the requested Feature exist, the corresponding cell will be empty. This has the same size and is in the same order as the features from the header ReadFeatureValuesResponse.header.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityViewData" } } }, "description": "Entity view with Feature values." }, "GoogleCloudAiplatformV1beta1ListA2aTaskEventsResponse": { "description": "Response message for AgentEngineTaskStoreService.ListA2aTaskEvents.", "properties": { "taskEvents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TaskEvent" }, "description": "List of TaskEvents in the requested page." }, "nextPageToken": { "description": "A token to retrieve the next page of results.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListA2aTaskEventsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1TuningDataStats": { "id": "GoogleCloudAiplatformV1beta1TuningDataStats", "type": "object", "description": "The tuning data statistic values for TuningJob.", "properties": { "preferenceOptimizationDataStats": { "description": "Output only. Statistics for preference optimization.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1PreferenceOptimizationDataStats" }, "distillationDataStats": { "description": "Output only. Statistics for distillation prompt dataset. These statistics do not include the responses sampled from the teacher model.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1DistillationDataStats" }, "supervisedTuningDataStats": { "description": "The SFT Tuning data stats.", "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningDataStats" } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingMetadata", "type": "object", "description": "Model metadata specific to AutoML Forecasting.", "properties": { "trainCostMilliNodeHours": { "type": "string", "format": "int64", "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget." }, "evaluatedDataItemsBigqueryUri": { "description": "BigQuery destination uri for exported evaluated examples.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecasting": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecasting", "type": "object", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputs" }, "metadata": { "description": "The metadata information.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingMetadata" } }, "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model." }, "GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsResponse": { "properties": { "pipelineJobs": { "description": "PipelineJobs cancelled.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" } } }, "description": "Response message for PipelineService.BatchCancelPipelineJobs.", "id": "GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1PipelineJobDetail": { "properties": { "taskDetails": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskDetail" }, "description": "Output only. The runtime details of the tasks under the pipeline." }, "pipelineRunContext": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1Context", "description": "Output only. The context of the current pipeline run." }, "pipelineContext": { "description": "Output only. The context of the pipeline.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1Context" } }, "description": "The runtime detail of PipelineJob.", "id": "GoogleCloudAiplatformV1beta1PipelineJobDetail", "type": "object" }, "GoogleCloudAiplatformV1beta1TensorboardBlobSequence": { "description": "One point viewable on a blob metric plot, but mostly just a wrapper message to work around repeated fields can't be used directly within `oneof` fields.", "properties": { "values": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardBlob" }, "description": "List of blobs contained within the sequence." } }, "id": "GoogleCloudAiplatformV1beta1TensorboardBlobSequence", "type": "object" }, "GoogleCloudAiplatformV1beta1LossAnalysisResult": { "description": "The top-level result for loss analysis, stored within an EvalSet.", "properties": { "clusters": { "description": "The list of identified loss clusters.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LossCluster" } }, "config": { "description": "The configuration used to generate this analysis.", "$ref": "GoogleCloudAiplatformV1beta1LossAnalysisConfig" }, "analysisTime": { "type": "string", "format": "google-datetime", "description": "The timestamp when this analysis was performed." } }, "id": "GoogleCloudAiplatformV1beta1LossAnalysisResult", "type": "object" }, "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig": { "description": "Config for HTTP Basic Authentication.", "properties": { "credentialSecret": { "description": "Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomJobMetadata": { "properties": { "backingCustomJob": { "description": "The resource name of the CustomJob that has been created to carry out this custom task.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomJobMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryPrecisionMetricValue": { "id": "GoogleCloudAiplatformV1beta1TrajectoryPrecisionMetricValue", "type": "object", "properties": { "score": { "format": "float", "description": "Output only. TrajectoryPrecision score.", "readOnly": true, "type": "number" } }, "description": "TrajectoryPrecision metric value for an instance." }, "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecSliceConfig": { "id": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecSliceConfig", "type": "object", "description": "Specification message containing the config for this SliceSpec. When `kind` is selected as `value` and/or `range`, only a single slice will be computed. When `all_values` is present, a separate slice will be computed for each possible label/value for the corresponding key in `config`. Examples, with feature zip_code with values 12345, 23334, 88888 and feature country with values \"US\", \"Canada\", \"Mexico\" in the dataset: Example 1: { \"zip_code\": { \"value\": { \"float_value\": 12345.0 } } } A single slice for any data with zip_code 12345 in the dataset. Example 2: { \"zip_code\": { \"range\": { \"low\": 12345, \"high\": 20000 } } } A single slice containing data where the zip_codes between 12345 and 20000 For this example, data with the zip_code of 12345 will be in this slice. Example 3: { \"zip_code\": { \"range\": { \"low\": 10000, \"high\": 20000 } }, \"country\": { \"value\": { \"string_value\": \"US\" } } } A single slice containing data where the zip_codes between 10000 and 20000 has the country \"US\". For this example, data with the zip_code of 12345 and country \"US\" will be in this slice. Example 4: { \"country\": {\"all_values\": { \"value\": true } } } Three slices are computed, one for each unique country in the dataset. Example 5: { \"country\": { \"all_values\": { \"value\": true } }, \"zip_code\": { \"value\": { \"float_value\": 12345.0 } } } Three slices are computed, one for each unique country in the dataset where the zip_code is also 12345. For this example, data with zip_code 12345 and country \"US\" will be in one slice, zip_code 12345 and country \"Canada\" in another slice, and zip_code 12345 and country \"Mexico\" in another slice, totaling 3 slices.", "properties": { "value": { "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecValue", "description": "A unique specific value for a given feature. Example: `{ \"value\": { \"string_value\": \"12345\" } }`" }, "range": { "description": "A range of values for a numerical feature. Example: `{\"range\":{\"low\":10000.0,\"high\":50000.0}}` will capture 12345 and 23334 in the slice.", "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecRange" }, "allValues": { "description": "If all_values is set to true, then all possible labels of the keyed feature will have another slice computed. Example: `{\"all_values\":{\"value\":true}}`", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1MetricSource": { "id": "GoogleCloudAiplatformV1beta1MetricSource", "type": "object", "properties": { "metricResourceName": { "description": "Resource name for registered metric.", "type": "string" }, "metric": { "description": "Inline metric config.", "$ref": "GoogleCloudAiplatformV1beta1Metric" } }, "description": "The metric source used for evaluation." }, "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectEntity": { "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectEntity", "type": "object", "description": "Message to select entity. If an entity id is selected, all the feature values corresponding to the entity id will be deleted, including the entityId.", "properties": { "entityIdSelector": { "$ref": "GoogleCloudAiplatformV1beta1EntityIdSelector", "description": "Required. Selectors choosing feature values of which entity id to be deleted from the EntityType." } } }, "GoogleCloudAiplatformV1beta1ListSessionsResponse": { "description": "Response message for SessionService.ListSessions.", "properties": { "nextPageToken": { "description": "A token, which can be sent as ListSessionsRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages.", "type": "string" }, "sessions": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Session" }, "description": "A list of sessions matching the request." } }, "id": "GoogleCloudAiplatformV1beta1ListSessionsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1GoogleDriveSource": { "properties": { "resourceIds": { "description": "Required. Google Drive resource IDs.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GoogleDriveSourceResourceId" } } }, "description": "The Google Drive location for the input content.", "id": "GoogleCloudAiplatformV1beta1GoogleDriveSource", "type": "object" }, "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequest": { "id": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequest", "type": "object", "properties": { "settings": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DestinationFeatureSetting" }, "description": "Per-Feature export settings." }, "fullExport": { "$ref": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestFullExport", "description": "Exports all historical values of all entities of the EntityType within a time range" }, "snapshotExport": { "$ref": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestSnapshotExport", "description": "Exports the latest Feature values of all entities of the EntityType within a time range." }, "destination": { "description": "Required. Specifies destination location and format.", "$ref": "GoogleCloudAiplatformV1beta1FeatureValueDestination" }, "featureSelector": { "$ref": "GoogleCloudAiplatformV1beta1FeatureSelector", "description": "Required. Selects Features to export values of." } }, "description": "Request message for FeaturestoreService.ExportFeatureValues." }, "GoogleCloudAiplatformV1beta1FractionSplit": { "id": "GoogleCloudAiplatformV1beta1FractionSplit", "type": "object", "description": "Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.", "properties": { "trainingFraction": { "description": "The fraction of the input data that is to be used to train the Model.", "format": "double", "type": "number" }, "validationFraction": { "format": "double", "description": "The fraction of the input data that is to be used to validate the Model.", "type": "number" }, "testFraction": { "format": "double", "description": "The fraction of the input data that is to be used to evaluate the Model.", "type": "number" } } }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateDefaultContainerEnvironment": { "description": "The default sandbox runtime environment for default container workloads.", "properties": { "defaultContainerCategory": { "type": "string", "enumDescriptions": [ "The default value. This value is unused.", "The default container image for Computer Use." ], "enum": [ "DEFAULT_CONTAINER_CATEGORY_UNSPECIFIED", "DEFAULT_CONTAINER_CATEGORY_COMPUTER_USE" ], "description": "Required. The category of the default container image." } }, "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateDefaultContainerEnvironment", "type": "object" }, "GoogleCloudAiplatformV1beta1Example": { "id": "GoogleCloudAiplatformV1beta1Example", "type": "object", "properties": { "exampleId": { "description": "Optional. Immutable. Unique identifier of an example. If not specified when upserting new examples, the example_id will be generated.", "type": "string" }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when this Example was created.", "readOnly": true, "type": "string" }, "displayName": { "description": "Optional. The display name for Example.", "type": "string" }, "storedContentsExample": { "description": "An example of chat history and its expected outcome to be used with GenerateContent.", "$ref": "GoogleCloudAiplatformV1beta1StoredContentsExample" } } }, "GoogleCloudAiplatformV1beta1FetchPredictOperationRequest": { "id": "GoogleCloudAiplatformV1beta1FetchPredictOperationRequest", "type": "object", "properties": { "operationName": { "description": "Required. The server-assigned name for the operation.", "type": "string" } }, "description": "Request message for PredictionService.FetchPredictOperation." }, "GoogleCloudAiplatformV1beta1ModelExportFormat": { "id": "GoogleCloudAiplatformV1beta1ModelExportFormat", "type": "object", "description": "Represents export format supported by the Model. All formats export to Google Cloud Storage.", "properties": { "id": { "description": "Output only. The ID of the export format. The possible format IDs are: * `tflite` Used for Android mobile devices. * `edgetpu-tflite` Used for [Edge TPU](https://cloud.google.com/edge-tpu/) devices. * `tf-saved-model` A tensorflow model in SavedModel format. * `tf-js` A [TensorFlow.js](https://www.tensorflow.org/js) model that can be used in the browser and in Node.js using JavaScript. * `core-ml` Used for iOS mobile devices. * `custom-trained` A Model that was uploaded or trained by custom code. * `genie` A tuned Model Garden model.", "readOnly": true, "type": "string" }, "exportableContents": { "readOnly": true, "type": "array", "items": { "enum": [ "EXPORTABLE_CONTENT_UNSPECIFIED", "ARTIFACT", "IMAGE" ], "type": "string", "enumDescriptions": [ "Should not be used.", "Model artifact and any of its supported files. Will be exported to the location specified by the `artifactDestination` field of the ExportModelRequest.output_config object.", "The container image that is to be used when deploying this Model. Will be exported to the location specified by the `imageDestination` field of the ExportModelRequest.output_config object." ] }, "description": "Output only. The content of this Model that may be exported." } } }, "GoogleCloudAiplatformV1beta1ExplanationMetadataOverrideInputMetadataOverride": { "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataOverrideInputMetadataOverride", "type": "object", "properties": { "inputBaselines": { "description": "Baseline inputs for this feature. This overrides the `input_baseline` field of the ExplanationMetadata.InputMetadata object of the corresponding feature's input metadata. If it's not specified, the original baselines are not overridden.", "type": "array", "items": { "type": "any" } } }, "description": "The input metadata entries to be overridden." }, "GoogleCloudAiplatformV1beta1RecommendSpecResponse": { "description": "Response message for ModelService.RecommendSpec.", "properties": { "baseModel": { "type": "string", "readOnly": true, "description": "Output only. The base model used to finetune the custom model." }, "recommendations": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RecommendSpecResponseRecommendation" }, "description": "Output only. Recommendations of deployment options for the given custom weights model." }, "specs": { "description": "Output only. The machine and model container specs.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RecommendSpecResponseMachineAndModelContainerSpec" }, "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1RecommendSpecResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateCustomContainerSpec": { "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateCustomContainerSpec", "type": "object", "description": "Specification for deploying from a custom container image.", "properties": { "imageUri": { "description": "Required. The Artifact Registry Docker image URI (e.g., us-central1-docker.pkg.dev/my-project/my-repo/my-image:tag) of the container image that is to be run on each worker replica.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1NearestNeighborQueryParameters": { "description": "Parameters that can be overrided in each query to tune query latency and recall.", "properties": { "approximateNeighborCandidates": { "type": "integer", "format": "int32", "description": "Optional. The number of neighbors to find via approximate search before exact reordering is performed; if set, this value must be \u003e neighbor_count." }, "leafNodesSearchFraction": { "description": "Optional. The fraction of the number of leaves to search, set at query time allows user to tune search performance. This value increase result in both search accuracy and latency increase. The value should be between 0.0 and 1.0.", "format": "double", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1NearestNeighborQueryParameters", "type": "object" }, "GoogleCloudAiplatformV1beta1LineageSubgraph": { "properties": { "artifacts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Artifact" }, "description": "The Artifact nodes in the subgraph." }, "executions": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Execution" }, "description": "The Execution nodes in the subgraph." }, "events": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Event" }, "description": "The Event edges between Artifacts and Executions in the subgraph." } }, "description": "A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.", "id": "GoogleCloudAiplatformV1beta1LineageSubgraph", "type": "object" }, "GoogleIamV1TestIamPermissionsRequest": { "description": "Request message for `TestIamPermissions` method.", "properties": { "permissions": { "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", "type": "array", "items": { "type": "string" } } }, "id": "GoogleIamV1TestIamPermissionsRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolCallValidInput": { "id": "GoogleCloudAiplatformV1beta1ToolCallValidInput", "type": "object", "properties": { "metricSpec": { "description": "Required. Spec for tool call valid metric.", "$ref": "GoogleCloudAiplatformV1beta1ToolCallValidSpec" }, "instances": { "description": "Required. Repeated tool call valid instances.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ToolCallValidInstance" } } }, "description": "Input for tool call valid metric." }, "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSource": { "id": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSource", "type": "object", "properties": { "events": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSourceEvent" }, "description": "Optional. Represents the input conversation events for the example." } }, "description": "A conversation source for the example. This is similar to `DirectContentsSource`." }, "GoogleCloudAiplatformV1beta1RetrievalConfig": { "description": "Retrieval config.", "properties": { "languageCode": { "description": "The language code of the user.", "type": "string" }, "latLng": { "$ref": "GoogleTypeLatLng", "description": "The location of the user." } }, "id": "GoogleCloudAiplatformV1beta1RetrievalConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1PredictLongRunningRequest": { "properties": { "instances": { "description": "Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.", "type": "array", "items": { "type": "any" } }, "parameters": { "description": "Optional. The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.", "type": "any" }, "labels": { "description": "Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter.", "type": "object", "additionalProperties": { "type": "string" } } }, "description": "Request message for PredictionService.PredictLongRunning.", "id": "GoogleCloudAiplatformV1beta1PredictLongRunningRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1RagMetadataSchemaDetailsSearchStrategy": { "description": "The search strategy for the metadata value of the `key`.", "properties": { "searchStrategyType": { "description": "The search strategy type to be applied on the metadata key.", "enum": [ "SEARCH_STRATEGY_TYPE_UNSPECIFIED", "NO_SEARCH", "EXACT_SEARCH" ], "type": "string", "enumDescriptions": [ "Unspecified search strategy type.", "metadata values of the `key` above will not be searchable.", "When searching with `key`, the value must be exactly as the metadata value that has been ingested." ] } }, "id": "GoogleCloudAiplatformV1beta1RagMetadataSchemaDetailsSearchStrategy", "type": "object" }, "GoogleCloudAiplatformV1beta1MigratableResourceMlEngineModelVersion": { "id": "GoogleCloudAiplatformV1beta1MigratableResourceMlEngineModelVersion", "type": "object", "description": "Represents one model Version in ml.googleapis.com.", "properties": { "version": { "description": "Full resource name of ml engine model Version. Format: `projects/{project}/models/{model}/versions/{version}`.", "type": "string" }, "endpoint": { "description": "The ml.googleapis.com endpoint that this model Version currently lives in. Example values: * ml.googleapis.com * us-centrall-ml.googleapis.com * europe-west4-ml.googleapis.com * asia-east1-ml.googleapis.com", "type": "string" } } }, "GoogleCloudAiplatformV1beta1CopyModelRequest": { "description": "Request message for ModelService.CopyModel.", "properties": { "modelId": { "description": "Optional. Copy source_model into a new Model with this ID. The ID will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen.", "type": "string" }, "sourceModel": { "description": "Required. The resource name of the Model to copy. That Model must be in the same Project. Format: `projects/{project}/locations/{location}/models/{model}`", "type": "string" }, "parentModel": { "description": "Optional. Specify this field to copy source_model into this existing Model as a new version. Format: `projects/{project}/locations/{location}/models/{model}`", "type": "string" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key options. If this is set, then the Model copy will be encrypted with the provided encryption key." } }, "id": "GoogleCloudAiplatformV1beta1CopyModelRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1CancelCustomJobRequest": { "description": "Request message for JobService.CancelCustomJob.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1CancelCustomJobRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaVideoObjectTrackingAnnotation": { "id": "GoogleCloudAiplatformV1beta1SchemaVideoObjectTrackingAnnotation", "type": "object", "properties": { "timeOffset": { "format": "google-duration", "description": "A time (frame) of a video to which this annotation pertains. Represented as the duration since the video's start.", "type": "string" }, "instanceId": { "type": "string", "description": "The instance of the object, expressed as a positive integer. Used to track the same object across different frames.", "format": "int64" }, "yMin": { "type": "number", "format": "double", "description": "The topmost coordinate of the bounding box." }, "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "xMax": { "type": "number", "format": "double", "description": "The rightmost coordinate of the bounding box." }, "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "xMin": { "type": "number", "description": "The leftmost coordinate of the bounding box.", "format": "double" }, "yMax": { "format": "double", "description": "The bottommost coordinate of the bounding box.", "type": "number" } }, "description": "Annotation details specific to video object tracking." }, "GoogleCloudAiplatformV1beta1ModelMonitoringInputBatchPredictionOutput": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputBatchPredictionOutput", "type": "object", "description": "Data from Vertex AI Batch prediction job output.", "properties": { "batchPredictionJob": { "description": "Vertex AI Batch prediction job resource name. The job must match the model version specified in [ModelMonitor].[model_monitoring_target].", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ListOptimalTrialsRequest": { "id": "GoogleCloudAiplatformV1beta1ListOptimalTrialsRequest", "type": "object", "description": "Request message for VizierService.ListOptimalTrials.", "properties": {} }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig": { "properties": { "temporalTotalWeight": { "type": "number", "format": "double", "description": "The weight of the loss for predictions aggregated over the horizon for a single time series." }, "groupTotalWeight": { "type": "number", "description": "The weight of the loss for predictions aggregated over time series in the same group.", "format": "double" }, "groupColumns": { "description": "A list of time series attribute column names that define the time series hierarchy. Only one level of hierarchy is supported, ex. 'region' for a hierarchy of stores or 'department' for a hierarchy of products. If multiple columns are specified, time series will be grouped by their combined values, ex. ('blue', 'large') for 'color' and 'size', up to 5 columns are accepted. If no group columns are specified, all time series are considered to be part of the same group.", "type": "array", "items": { "type": "string" } }, "groupTemporalTotalWeight": { "type": "number", "format": "double", "description": "The weight of the loss for predictions aggregated over both the horizon and time series in the same hierarchy group." } }, "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies.", "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SummarizationVerbosityResult": { "id": "GoogleCloudAiplatformV1beta1SummarizationVerbosityResult", "type": "object", "description": "Spec for summarization verbosity result.", "properties": { "explanation": { "type": "string", "readOnly": true, "description": "Output only. Explanation for summarization verbosity score." }, "confidence": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Confidence for summarization verbosity score." }, "score": { "format": "float", "description": "Output only. Summarization Verbosity score.", "readOnly": true, "type": "number" } } }, "GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadataPartialResult": { "description": "Represents a partial result in batch migration operation for one MigrateResourceRequest.", "properties": { "model": { "description": "Migrated model resource name.", "type": "string" }, "dataset": { "description": "Migrated dataset resource name.", "type": "string" }, "request": { "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceRequest", "description": "It's the same as the value in BatchMigrateResourcesRequest.migrate_resource_requests." }, "error": { "$ref": "GoogleRpcStatus", "description": "The error result of the migration request in case of failure." } }, "id": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadataPartialResult", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsResponse": { "description": "Response message for ModelMonitoringService.SearchModelMonitoringStats.", "properties": { "monitoringStats": { "description": "Stats retrieved for requested objectives.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStats" } }, "nextPageToken": { "description": "The page token that can be used by the next ModelMonitoringService.SearchModelMonitoringStats call.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1DeployedModelRef": { "id": "GoogleCloudAiplatformV1beta1DeployedModelRef", "type": "object", "properties": { "checkpointId": { "description": "Immutable. The ID of the Checkpoint deployed in the DeployedModel.", "type": "string" }, "endpoint": { "description": "Immutable. A resource name of an Endpoint.", "type": "string" }, "deployedModelId": { "description": "Immutable. An ID of a DeployedModel in the above Endpoint.", "type": "string" } }, "description": "Points to a DeployedModel." }, "GoogleCloudAiplatformV1beta1SchemaPromptInstanceVariableValue": { "description": "The value of a variable in prompt.", "properties": { "partList": { "description": "The parts of the variable value.", "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecPartList" } }, "id": "GoogleCloudAiplatformV1beta1SchemaPromptInstanceVariableValue", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfig": { "properties": { "enableFeatureAttributes": { "description": "If want to analyze the Vertex Explainable AI feature attribute scores or not. If set to true, Vertex AI will log the feature attributions from explain response and do the skew/drift detection for them.", "type": "boolean" }, "explanationBaseline": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline", "description": "Predictions generated by the BatchPredictionJob using baseline dataset." } }, "description": "The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated.", "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1PairwiseMetricInstance": { "id": "GoogleCloudAiplatformV1beta1PairwiseMetricInstance", "type": "object", "description": "Pairwise metric instance. Usually one instance corresponds to one row in an evaluation dataset.", "properties": { "contentMapInstance": { "$ref": "GoogleCloudAiplatformV1beta1ContentMap", "description": "Key-value contents for the mutlimodality input, including text, image, video, audio, and pdf, etc. The key is placeholder in metric prompt template, and the value is the multimodal content." }, "jsonInstance": { "description": "Instance specified as a json string. String key-value pairs are expected in the json_instance to render PairwiseMetricSpec.instance_prompt_template.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfigEmailAlertConfig": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfigEmailAlertConfig", "type": "object", "properties": { "userEmails": { "description": "The email addresses to send the alert.", "type": "array", "items": { "type": "string" } } }, "description": "The config for email alert." }, "GoogleCloudAiplatformV1beta1MetricResult": { "properties": { "rubricVerdicts": { "description": "Output only. For rubric-based metrics, the verdicts for each rubric.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RubricVerdict" }, "readOnly": true }, "explanation": { "readOnly": true, "type": "string", "description": "Output only. The explanation for the metric result." }, "error": { "description": "Output only. The error status for the metric result.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "score": { "format": "float", "description": "Output only. The score for the metric. Please refer to each metric's documentation for the meaning of the score.", "readOnly": true, "type": "number" } }, "description": "Result for a single metric on a single instance.", "id": "GoogleCloudAiplatformV1beta1MetricResult", "type": "object" }, "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopicManagedMemoryTopic": { "properties": { "managedTopicEnum": { "enum": [ "MANAGED_TOPIC_ENUM_UNSPECIFIED", "USER_PERSONAL_INFO", "USER_PREFERENCES", "KEY_CONVERSATION_DETAILS", "EXPLICIT_INSTRUCTIONS" ], "description": "Required. Represents the managed topic.", "type": "string", "enumDescriptions": [ "Represents an unspecified topic. This value should not be used.", "Represents significant personal information about the User like first names, relationships, hobbies, important dates.", "Represents stated or implied likes, dislikes, preferred styles, or patterns.", "Represents important milestones or conclusions within the dialogue.", "Represents information that the user explicitly requested to remember or forget." ] } }, "description": "A managed memory topic defined by the system.", "id": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopicManagedMemoryTopic", "type": "object" }, "GoogleCloudAiplatformV1beta1PointwiseMetricResult": { "description": "Spec for pointwise metric result.", "properties": { "score": { "description": "Output only. Pointwise metric score.", "format": "float", "type": "number", "readOnly": true }, "explanation": { "readOnly": true, "type": "string", "description": "Output only. Explanation for pointwise metric score." }, "customOutput": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1CustomOutput", "description": "Output only. Spec for custom output." } }, "id": "GoogleCloudAiplatformV1beta1PointwiseMetricResult", "type": "object" }, "GoogleCloudAiplatformV1beta1NasJobOutput": { "description": "Represents a uCAIP NasJob output.", "properties": { "multiTrialJobOutput": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1NasJobOutputMultiTrialJobOutput", "description": "Output only. The output of this multi-trial Neural Architecture Search (NAS) job." } }, "id": "GoogleCloudAiplatformV1beta1NasJobOutput", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureSelectionConfigFeatureConfig": { "id": "GoogleCloudAiplatformV1beta1FeatureSelectionConfigFeatureConfig", "type": "object", "properties": { "driftThreshold": { "type": "number", "description": "Optional. Drift threshold. If calculated difference with baseline data larger than threshold, it will be considered as the feature has drift. If not present, the threshold will be default to 0.3. Must be in range [0, 1).", "format": "double" }, "featureId": { "description": "Required. The ID of the feature resource. Final component of the Feature's resource name.", "type": "string" } }, "description": "Feature configuration." }, "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig": { "description": "Config for authentication with API key.", "properties": { "apiKeyString": { "description": "Optional. The API key to be used in the request directly.", "type": "string" }, "httpElementLocation": { "description": "Optional. The location of the API key.", "enum": [ "HTTP_IN_UNSPECIFIED", "HTTP_IN_QUERY", "HTTP_IN_HEADER", "HTTP_IN_PATH", "HTTP_IN_BODY", "HTTP_IN_COOKIE" ], "type": "string", "enumDescriptions": [ "", "Element is in the HTTP request query.", "Element is in the HTTP request header.", "Element is in the HTTP request path.", "Element is in the HTTP request body.", "Element is in the HTTP request cookie." ] }, "name": { "description": "Optional. The parameter name of the API key. E.g. If the API request is \"https://example.com/act?api_key=\", \"api_key\" would be the parameter name.", "type": "string" }, "apiKeySecret": { "description": "Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1StartNotebookRuntimeOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1StartNotebookRuntimeOperationMetadata", "type": "object", "properties": { "progressMessage": { "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime.", "type": "string" }, "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Metadata information for NotebookService.StartNotebookRuntime." }, "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilterTabularStatsFilter": { "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilterTabularStatsFilter", "type": "object", "properties": { "statsName": { "description": "If not specified, will return all the stats_names.", "type": "string" }, "objectiveType": { "description": "One of the supported monitoring objectives: `raw-feature-drift` `prediction-output-drift` `feature-attribution`", "type": "string" }, "modelMonitoringJob": { "description": "From a particular monitoring job.", "type": "string" }, "modelMonitoringSchedule": { "description": "From a particular monitoring schedule.", "type": "string" }, "algorithm": { "description": "Specify the algorithm type used for distance calculation, eg: jensen_shannon_divergence, l_infinity.", "type": "string" } }, "description": "Tabular statistics filter." }, "GoogleCloudAiplatformV1beta1Explanation": { "id": "GoogleCloudAiplatformV1beta1Explanation", "type": "object", "properties": { "attributions": { "description": "Output only. Feature attributions grouped by predicted outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. Attribution.output_index can be used to identify which output this attribution is explaining. By default, we provide Shapley values for the predicted class. However, you can configure the explanation request to generate Shapley values for any other classes too. For example, if a model predicts a probability of `0.4` for approving a loan application, the model's decision is to reject the application since `p(reject) = 0.6 \u003e p(approve) = 0.4`, and the default Shapley values would be computed for rejection decision and not approval, even though the latter might be the positive class. If users set ExplanationParameters.top_k, the attributions are sorted by instance_output_value in descending order. If ExplanationParameters.output_indices is specified, the attributions are stored by Attribution.output_index in the same order as they appear in the output_indices.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Attribution" } }, "neighbors": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Neighbor" }, "description": "Output only. List of the nearest neighbors for example-based explanations. For models deployed with the examples explanations feature enabled, the attributions field is empty and instead the neighbors field is populated." } }, "description": "Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance." }, "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableAutoScaling": { "properties": { "minNodeCount": { "type": "integer", "format": "int32", "description": "Required. The minimum number of nodes to scale down to. Must be greater than or equal to 1." }, "maxNodeCount": { "format": "int32", "description": "Required. The maximum number of nodes to scale up to. Must be greater than or equal to min_node_count, and less than or equal to 10 times of 'min_node_count'.", "type": "integer" }, "cpuUtilizationTarget": { "type": "integer", "format": "int32", "description": "Optional. A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%." } }, "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableAutoScaling", "type": "object" }, "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec": { "id": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec", "type": "object", "properties": { "maxFailedTrialCount": { "type": "integer", "description": "The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.", "format": "int32" }, "maxParallelTrialCount": { "description": "Required. The maximum number of trials to run in parallel.", "format": "int32", "type": "integer" }, "searchTrialJobSpec": { "description": "Required. The spec of a search trial job. The same spec applies to all search trials.", "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec" }, "maxTrialCount": { "description": "Required. The maximum number of Neural Architecture Search (NAS) trials to run.", "format": "int32", "type": "integer" } }, "description": "Represent spec for search trials." }, "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataResponse": { "description": "Response message for TensorboardService.WriteTensorboardExperimentData.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecReferenceSentencePairList": { "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecReferenceSentencePairList", "type": "object", "properties": { "referenceSentencePairs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecReferenceSentencePair" }, "description": "Reference sentence pairs." } }, "description": "A list of reference sentence pairs." }, "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigTreeAHConfig": { "properties": { "leafNodeEmbeddingCount": { "description": "Optional. Number of embeddings on each leaf node. The default value is 1000 if not set.", "format": "int64", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigTreeAHConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentsResponse": { "description": "Response message for SandboxEnvironmentService.ListSandboxEnvironments.", "properties": { "sandboxEnvironments": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironment" }, "description": "The SandboxEnvironments matching the request." }, "nextPageToken": { "description": "A token, which can be sent as ListSandboxEnvironmentsRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfig": { "properties": { "authProvider": { "description": "Defines the authentication provider that the DeployedIndex uses.", "$ref": "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfigAuthProvider" } }, "description": "Used to set up the auth on the DeployedIndex's private endpoint.", "id": "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchResults": { "id": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchResults", "type": "object", "properties": { "toolParameterKeyMatchMetricValues": { "description": "Output only. Tool parameter key match metric values.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchMetricValue" }, "readOnly": true } }, "description": "Results for tool parameter key match metric." }, "GoogleCloudAiplatformV1beta1DeployRequestCustomModel": { "properties": { "modelId": { "description": "Optional. Deprecated. Use ModelConfig.model_user_id instead.", "type": "string", "deprecated": true }, "gcsUri": { "description": "Immutable. The Google Cloud Storage URI of the custom model, storing weights and config files (which can be used to infer the base model).", "type": "string" } }, "description": "The custom model to deploy from model weights in a Google Cloud Storage URI or Model Registry model.", "id": "GoogleCloudAiplatformV1beta1DeployRequestCustomModel", "type": "object" }, "GoogleCloudAiplatformV1beta1LLMBasedMetricSpec": { "description": "Specification for an LLM based metric.", "properties": { "rubricGenerationSpec": { "description": "Dynamically generate rubrics using this specification.", "$ref": "GoogleCloudAiplatformV1beta1RubricGenerationSpec" }, "rubricGroupKey": { "description": "Use a pre-defined group of rubrics associated with the input. Refers to a key in the rubric_groups map of EvaluationInstance.", "type": "string" }, "additionalConfig": { "description": "Optional. Optional additional configuration for the metric.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "predefinedRubricGenerationSpec": { "$ref": "GoogleCloudAiplatformV1beta1PredefinedMetricSpec", "description": "Dynamically generate rubrics using a predefined spec." }, "metricPromptTemplate": { "description": "Required. Template for the prompt sent to the judge model.", "type": "string" }, "judgeAutoraterConfig": { "$ref": "GoogleCloudAiplatformV1beta1AutoraterConfig", "description": "Optional. Optional configuration for the judge LLM (Autorater)." }, "systemInstruction": { "description": "Optional. System instructions for the judge model.", "type": "string" }, "resultParserConfig": { "description": "Optional. The parser config for the metric result.", "$ref": "GoogleCloudAiplatformV1beta1EvaluationParserConfig" } }, "id": "GoogleCloudAiplatformV1beta1LLMBasedMetricSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1CountTokensResponse": { "properties": { "totalBillableCharacters": { "description": "The total number of billable characters counted across all instances from the request.", "format": "int32", "type": "integer" }, "promptTokensDetails": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" }, "description": "Output only. List of modalities that were processed in the request input." }, "totalTokens": { "type": "integer", "format": "int32", "description": "The total number of tokens counted across all instances from the request." } }, "description": "Response message for PredictionService.CountTokens.", "id": "GoogleCloudAiplatformV1beta1CountTokensResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateContentResponse": { "properties": { "promptFeedback": { "description": "Output only. Content filter results for a prompt sent in the request. Note: Sent only in the first stream chunk. Only happens when no candidates were generated due to content violations.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback" }, "candidates": { "description": "Output only. Generated candidates.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Candidate" }, "readOnly": true }, "modelVersion": { "type": "string", "readOnly": true, "description": "Output only. The model version used to generate the response." }, "responseId": { "description": "Output only. response_id is used to identify each response. It is the encoding of the event_id.", "type": "string", "readOnly": true }, "createTime": { "description": "Output only. Timestamp when the request is made to the server.", "format": "google-datetime", "type": "string", "readOnly": true }, "usageMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata", "description": "Usage metadata about the response(s)." } }, "description": "Response message for [PredictionService.GenerateContent].", "id": "GoogleCloudAiplatformV1beta1GenerateContentResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfigTrafficSplitManualTarget": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfigTrafficSplitManualTarget", "type": "object", "description": "A single target for the traffic split, specifying a Runtime Revision and the percentage of traffic to send to it.", "properties": { "runtimeRevisionName": { "description": "Required. The Runtime Revision name to which to send this portion of traffic, if traffic allocation is by Runtime Revision.", "type": "string" }, "percent": { "type": "integer", "format": "int32", "description": "Required. Specifies percent of the traffic to this Runtime Revision." } } }, "GoogleCloudAiplatformV1beta1SchemaTimeSegment": { "id": "GoogleCloudAiplatformV1beta1SchemaTimeSegment", "type": "object", "description": "A time period inside of a DataItem that has a time dimension (e.g. video).", "properties": { "endTimeOffset": { "format": "google-duration", "description": "End of the time segment (exclusive), represented as the duration since the start of the DataItem.", "type": "string" }, "startTimeOffset": { "type": "string", "format": "google-duration", "description": "Start of the time segment (inclusive), represented as the duration since the start of the DataItem." } } }, "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig": { "description": "The API secret.", "properties": { "apiKeySecretVersion": { "description": "Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}", "type": "string" }, "apiKeyString": { "description": "The API key string. Either this or `api_key_secret_version` must be set.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation": { "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding.", "properties": { "columnName": { "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation", "type": "object" }, "GoogleCloudAiplatformV1beta1DeleteMetadataStoreOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1DeleteMetadataStoreOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "Operation metadata for deleting a MetadataStore.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Details of operations that perform MetadataService.DeleteMetadataStore." }, "GoogleCloudAiplatformV1beta1AssessDataRequestTuningValidationAssessmentConfig": { "description": "Configuration for the tuning validation assessment.", "properties": { "datasetUsage": { "description": "Required. The dataset usage (e.g. training/validation).", "enum": [ "DATASET_USAGE_UNSPECIFIED", "SFT_TRAINING", "SFT_VALIDATION" ], "type": "string", "enumDescriptions": [ "Default value. Should not be used.", "Supervised fine-tuning training dataset.", "Supervised fine-tuning validation dataset." ] }, "modelName": { "description": "Required. The name of the model used for tuning.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1AssessDataRequestTuningValidationAssessmentConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1MetadataValue": { "id": "GoogleCloudAiplatformV1beta1MetadataValue", "type": "object", "description": "Value of Metadata, including all types available in data schema.", "properties": { "datetimeValue": { "description": "Value of date time type metadata.", "type": "string" }, "boolValue": { "description": "Value of boolean type metadata.", "type": "boolean" }, "listValue": { "$ref": "GoogleCloudAiplatformV1beta1MetadataList", "description": "Value of list type metadata." }, "intValue": { "format": "int64", "description": "Value of int type metadata.", "type": "string" }, "floatValue": { "type": "number", "description": "Value of float type metadata.", "format": "float" }, "strValue": { "description": "Value of string type metadata.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSources": { "description": "The sources that were used to generate the place answer. This includes review snippets and photos that were used to generate the answer, as well as URIs to flag content.", "properties": { "reviewSnippets": { "description": "Snippets of reviews that were used to generate the answer.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet" } } }, "id": "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSources", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob": { "id": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob", "type": "object", "properties": { "labels": { "description": "The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", "type": "object", "additionalProperties": { "type": "string" } }, "logTtl": { "description": "The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.", "format": "google-duration", "type": "string" }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.", "format": "google-datetime" }, "analysisInstanceSchemaUri": { "description": "YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.", "type": "string" }, "scheduleState": { "readOnly": true, "type": "string", "enumDescriptions": [ "Unspecified state.", "The pipeline is picked up and wait to run.", "The pipeline is offline and will be scheduled for next run.", "The pipeline is running." ], "enum": [ "MONITORING_SCHEDULE_STATE_UNSPECIFIED", "PENDING", "OFFLINE", "RUNNING" ], "description": "Output only. Schedule state when the monitoring job is in Running state." }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this ModelDeploymentMonitoringJob was created.", "format": "google-datetime" }, "modelDeploymentMonitoringScheduleConfig": { "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringScheduleConfig", "description": "Required. Schedule config for running the monitoring job." }, "nextScheduleTime": { "description": "Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.", "format": "google-datetime", "type": "string", "readOnly": true }, "latestMonitoringPipelineMetadata": { "description": "Output only. Latest triggered monitoring pipeline metadata.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata" }, "bigqueryTables": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringBigQueryTable" }, "description": "Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum: 1. Training data logging predict request/response 2. Serving data logging predict request/response" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key." }, "modelDeploymentMonitoringObjectiveConfigs": { "description": "Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringObjectiveConfig" } }, "name": { "type": "string", "readOnly": true, "description": "Output only. Resource name of a ModelDeploymentMonitoringJob." }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "displayName": { "description": "Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.", "type": "string" }, "error": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. Only populated when the job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`." }, "modelMonitoringAlertConfig": { "description": "Alert config for model monitoring.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig" }, "enableMonitoringPipelineLogs": { "description": "If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging#pricing).", "type": "boolean" }, "samplePredictInstance": { "description": "Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.", "type": "any" }, "statsAnomaliesBaseDirectory": { "description": "Stats anomalies base folder path.", "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" }, "satisfiesPzs": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "endpoint": { "description": "Required. Endpoint resource name. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string" }, "state": { "readOnly": true, "type": "string", "enumDescriptions": [ "The job state is unspecified.", "The job has been just created or resumed and processing has not yet begun.", "The service is preparing to run the job.", "The job is in progress.", "The job completed successfully.", "The job failed.", "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "The job has been cancelled.", "The job has been stopped, and can be resumed.", "The job has expired.", "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", "The job is partially succeeded, some results may be missing due to errors." ], "enum": [ "JOB_STATE_UNSPECIFIED", "JOB_STATE_QUEUED", "JOB_STATE_PENDING", "JOB_STATE_RUNNING", "JOB_STATE_SUCCEEDED", "JOB_STATE_FAILED", "JOB_STATE_CANCELLING", "JOB_STATE_CANCELLED", "JOB_STATE_PAUSED", "JOB_STATE_EXPIRED", "JOB_STATE_UPDATING", "JOB_STATE_PARTIALLY_SUCCEEDED" ], "description": "Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'." }, "predictInstanceSchemaUri": { "description": "YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.", "type": "string" }, "loggingSamplingStrategy": { "$ref": "GoogleCloudAiplatformV1beta1SamplingStrategy", "description": "Required. Sample Strategy for logging." } }, "description": "Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors." }, "GoogleCloudAiplatformV1beta1ExecuteExtensionRequest": { "id": "GoogleCloudAiplatformV1beta1ExecuteExtensionRequest", "type": "object", "properties": { "operationId": { "description": "Required. The desired ID of the operation to be executed in this extension as defined in ExtensionOperation.operation_id.", "type": "string" }, "operationParams": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. Request parameters that will be used for executing this operation. The struct should be in a form of map with param name as the key and actual param value as the value. E.g. If this operation requires a param \"name\" to be set to \"abc\". you can set this to something like {\"name\": \"abc\"}." }, "runtimeAuthConfig": { "description": "Optional. Auth config provided at runtime to override the default value in Extension.manifest.auth_config. The AuthConfig.auth_type should match the value in Extension.manifest.auth_config.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfig" } }, "description": "Request message for ExtensionExecutionService.ExecuteExtension." }, "GoogleCloudAiplatformV1beta1SpecialistPool": { "description": "SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console.", "properties": { "specialistManagerEmails": { "type": "array", "items": { "type": "string" }, "description": "The email addresses of the managers in the SpecialistPool." }, "displayName": { "description": "Required. The user-defined name of the SpecialistPool. The name can be up to 128 characters long and can consist of any UTF-8 characters. This field should be unique on project-level.", "type": "string" }, "pendingDataLabelingJobs": { "type": "array", "items": { "type": "string" }, "readOnly": true, "description": "Output only. The resource name of the pending data labeling jobs." }, "specialistWorkerEmails": { "type": "array", "items": { "type": "string" }, "description": "The email addresses of workers in the SpecialistPool." }, "specialistManagersCount": { "type": "integer", "readOnly": true, "description": "Output only. The number of managers in this SpecialistPool.", "format": "int32" }, "name": { "description": "Required. The resource name of the SpecialistPool.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SpecialistPool", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySourceFeatureGroup": { "description": "Features belonging to a single feature group that will be synced to Online Store.", "properties": { "featureGroupId": { "description": "Required. Identifier of the feature group.", "type": "string" }, "featureIds": { "type": "array", "items": { "type": "string" }, "description": "Required. Identifiers of features under the feature group." } }, "id": "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySourceFeatureGroup", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchNearestEntitiesResponse": { "id": "GoogleCloudAiplatformV1beta1SearchNearestEntitiesResponse", "type": "object", "properties": { "nearestNeighbors": { "$ref": "GoogleCloudAiplatformV1beta1NearestNeighbors", "description": "The nearest neighbors of the query entity." } }, "description": "Response message for FeatureOnlineStoreService.SearchNearestEntities" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics": { "description": "Metrics for a single confidence threshold.", "properties": { "confidenceThreshold": { "type": "number", "format": "float", "description": "The confidence threshold value used to compute the metrics." }, "precision": { "type": "number", "description": "Precision under the given confidence threshold.", "format": "float" }, "f1Score": { "format": "float", "description": "The harmonic mean of recall and precision.", "type": "number" }, "recall": { "type": "number", "format": "float", "description": "Recall under the given confidence threshold." } }, "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecImageSpec": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecImageSpec", "type": "object", "description": "The image spec for building an image (within a single build step), based on the config file (i.e. Dockerfile) in the source directory.", "properties": { "buildArgs": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. Build arguments to be used. They will be passed through --build-arg flags." } } }, "GoogleCloudAiplatformV1beta1BatchMigrateResourcesResponse": { "id": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesResponse", "type": "object", "description": "Response message for MigrationService.BatchMigrateResources.", "properties": { "migrateResourceResponses": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MigrateResourceResponse" }, "description": "Successfully migrated resources." } } }, "GoogleCloudAiplatformV1beta1FeatureViewDataKey": { "description": "Lookup key for a feature view.", "properties": { "key": { "description": "String key to use for lookup.", "type": "string" }, "compositeKey": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKeyCompositeKey", "description": "The actual Entity ID will be composed from this struct. This should match with the way ID is defined in the FeatureView spec." } }, "id": "GoogleCloudAiplatformV1beta1FeatureViewDataKey", "type": "object" }, "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataRequest": { "properties": { "writeRunDataRequests": { "description": "Required. Requests containing per-run TensorboardTimeSeries data to write.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataRequest" } } }, "description": "Request message for TensorboardService.WriteTensorboardExperimentData.", "id": "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1RebaseTunedModelRequest": { "id": "GoogleCloudAiplatformV1beta1RebaseTunedModelRequest", "type": "object", "properties": { "tunedModelRef": { "$ref": "GoogleCloudAiplatformV1beta1TunedModelRef", "description": "Required. A reference to the tuned model to rebase." }, "deployToSameEndpoint": { "description": "Optional. By default, rebasing a model creates a new endpoint for the new model. If this flag is set to true, the new model will be deployed to the same endpoint as the original model. WARNING: If you deploy to the same endpoint, the original model will be un-deployed and replaced by the new model.", "type": "boolean" }, "tuningJob": { "description": "Optional. The tuning job to be updated. Users can use this field to overwrite tuning configs.", "$ref": "GoogleCloudAiplatformV1beta1TuningJob" }, "artifactDestination": { "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", "description": "Optional. The Google Cloud Storage location to write the artifacts to." } }, "description": "Request message for GenAiTuningService.RebaseTunedModel." }, "GoogleCloudAiplatformV1beta1ListTensorboardRunsResponse": { "id": "GoogleCloudAiplatformV1beta1ListTensorboardRunsResponse", "type": "object", "description": "Response message for TensorboardService.ListTensorboardRuns.", "properties": { "nextPageToken": { "description": "A token, which can be sent as ListTensorboardRunsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" }, "tensorboardRuns": { "description": "The TensorboardRuns mathching the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" } } } }, "GoogleCloudAiplatformV1beta1ModelOriginalModelInfo": { "id": "GoogleCloudAiplatformV1beta1ModelOriginalModelInfo", "type": "object", "description": "Contains information about the original Model if this Model is a copy.", "properties": { "model": { "type": "string", "readOnly": true, "description": "Output only. The resource name of the Model this Model is a copy of, including the revision. Format: `projects/{project}/locations/{location}/models/{model_id}@{version_id}`" } } }, "GoogleCloudAiplatformV1beta1RougeResults": { "properties": { "rougeMetricValues": { "description": "Output only. Rouge metric values.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RougeMetricValue" } } }, "description": "Results for rouge metric.", "id": "GoogleCloudAiplatformV1beta1RougeResults", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateFeatureViewOperationMetadata": { "description": "Details of operations that perform create FeatureView.", "properties": { "genericMetadata": { "description": "Operation metadata for FeatureView Create.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1beta1CreateFeatureViewOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics", "type": "object", "description": "Metrics for general pairwise text generation evaluation results.", "properties": { "precision": { "description": "Fraction of cases where the autorater and humans thought the model had a better response out of all cases where the autorater thought the model had a better response. True positive divided by all positive.", "format": "float", "type": "number" }, "humanPreferenceModelWinRate": { "type": "number", "format": "float", "description": "Percentage of time humans decided the model had the better response." }, "modelWinRate": { "type": "number", "format": "float", "description": "Percentage of time the autorater decided the model had the better response." }, "cohensKappa": { "type": "number", "description": "A measurement of agreement between the autorater and human raters that takes the likelihood of random agreement into account.", "format": "float" }, "accuracy": { "format": "float", "description": "Fraction of cases where the autorater agreed with the human raters.", "type": "number" }, "falseNegativeCount": { "type": "string", "description": "Number of examples where the autorater chose the baseline model, but humans preferred the model.", "format": "int64" }, "falsePositiveCount": { "type": "string", "description": "Number of examples where the autorater chose the model, but humans preferred the baseline model.", "format": "int64" }, "f1Score": { "type": "number", "description": "Harmonic mean of precision and recall.", "format": "float" }, "trueNegativeCount": { "format": "int64", "description": "Number of examples where both the autorater and humans decided that the model had the worse response.", "type": "string" }, "humanPreferenceBaselineModelWinRate": { "format": "float", "description": "Percentage of time humans decided the baseline model had the better response.", "type": "number" }, "truePositiveCount": { "description": "Number of examples where both the autorater and humans decided that the model had the better response.", "format": "int64", "type": "string" }, "baselineModelWinRate": { "description": "Percentage of time the autorater decided the baseline model had the better response.", "format": "float", "type": "number" }, "recall": { "format": "float", "description": "Fraction of cases where the autorater and humans thought the model had a better response out of all cases where the humans thought the model had a better response.", "type": "number" } } }, "GoogleCloudAiplatformV1beta1AppendA2aTaskEventsResponse": { "id": "GoogleCloudAiplatformV1beta1AppendA2aTaskEventsResponse", "type": "object", "description": "Response message for AgentEngineTaskStoreService.AppendA2aTaskEvents.", "properties": {} }, "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet": { "properties": { "googleMapsUri": { "description": "A link to show the review on Google Maps.", "type": "string" }, "reviewId": { "description": "The ID of the review that is being referenced.", "type": "string" }, "title": { "description": "The title of the review.", "type": "string" } }, "description": "A review snippet that is used to generate the answer.", "id": "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet", "type": "object" }, "GoogleCloudAiplatformV1beta1CorroborateContentRequest": { "id": "GoogleCloudAiplatformV1beta1CorroborateContentRequest", "type": "object", "properties": { "parameters": { "$ref": "GoogleCloudAiplatformV1beta1CorroborateContentRequestParameters", "description": "Optional. Parameters that can be set to override default settings per request." }, "facts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Fact" }, "description": "Optional. Facts used to generate the text can also be used to corroborate the text." }, "content": { "description": "Optional. Input content to corroborate, only text format is supported for now.", "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "description": "Request message for CorroborateContent." }, "GoogleCloudAiplatformV1beta1VeoHyperParameters": { "id": "GoogleCloudAiplatformV1beta1VeoHyperParameters", "type": "object", "description": "Hyperparameters for Veo.", "properties": { "learningRateMultiplier": { "type": "number", "format": "double", "description": "Optional. Multiplier for adjusting the default learning rate." }, "epochCount": { "description": "Optional. Number of complete passes the model makes over the entire training dataset during training.", "format": "int64", "type": "string" }, "veoDataMixtureRatio": { "type": "number", "description": "Optional. The ratio of Google internal dataset to use in the training mixture, in range of `[0, 1)`. If `0.2`, it means 20% of Google internal dataset and 80% of user dataset will be used for training. If not set, the default value is 0.1.", "format": "double" }, "adapterSize": { "enum": [ "ADAPTER_SIZE_UNSPECIFIED", "ADAPTER_SIZE_EIGHT", "ADAPTER_SIZE_SIXTEEN", "ADAPTER_SIZE_THIRTY_TWO" ], "description": "Optional. The adapter size for LoRA tuning.", "type": "string", "enumDescriptions": [ "Adapter size is unspecified.", "Adapter size 8. This is the default adapter size for Veo LoRA tuning.", "Adapter size 16.", "Adapter size 32." ] }, "tuningTask": { "description": "The tuning task for Veo.", "enum": [ "TUNING_TASK_UNSPECIFIED", "TUNING_TASK_I2V", "TUNING_TASK_T2V", "TUNING_TASK_R2V" ], "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "Tuning task for image to video.", "Tuning task for text to video.", "Tuning task for reference to video." ] }, "tuningSpeed": { "description": "The speed of the tuning job. Only supported for Veo 3.0 models.", "enum": [ "TUNING_SPEED_UNSPECIFIED", "REGULAR", "FAST" ], "type": "string", "enumDescriptions": [ "The default / unset value. For Veo 3.0 models, this defaults to FAST.", "Regular tuning speed.", "Fast tuning speed." ] } } }, "GoogleCloudAiplatformV1beta1VertexAiSearchConfig": { "id": "GoogleCloudAiplatformV1beta1VertexAiSearchConfig", "type": "object", "description": "Config for the Vertex AI Search.", "properties": { "servingConfig": { "description": "Vertex AI Search Serving Config resource full name. For example, `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}/servingConfigs/{serving_config}` or `projects/{project}/locations/{location}/collections/{collection}/dataStores/{data_store}/servingConfigs/{serving_config}`.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1UsageMetadata": { "properties": { "promptTokensDetails": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" }, "description": "Output only. A detailed breakdown of the token count for each modality in the prompt." }, "thoughtsTokenCount": { "type": "integer", "readOnly": true, "description": "Output only. The number of tokens that were part of the model's generated \"thoughts\" output, if applicable.", "format": "int32" }, "candidatesTokensDetails": { "description": "Output only. A detailed breakdown of the token count for each modality in the generated candidates.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" } }, "toolUsePromptTokensDetails": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" }, "readOnly": true, "description": "Output only. A detailed breakdown by modality of the token counts from the results of tool executions, which are provided back to the model as input." }, "candidatesTokenCount": { "type": "integer", "description": "The total number of tokens in the generated candidates.", "format": "int32" }, "promptTokenCount": { "format": "int32", "description": "The total number of tokens in the prompt. This includes any text, images, or other media provided in the request. When `cached_content` is set, this also includes the number of tokens in the cached content.", "type": "integer" }, "totalTokenCount": { "format": "int32", "description": "The total number of tokens for the entire request. This is the sum of `prompt_token_count`, `candidates_token_count`, `tool_use_prompt_token_count`, and `thoughts_token_count`.", "type": "integer" }, "cachedContentTokenCount": { "readOnly": true, "type": "integer", "format": "int32", "description": "Output only. The number of tokens in the cached content that was used for this request." }, "trafficType": { "readOnly": true, "type": "string", "enumDescriptions": [ "Unspecified request traffic type.", "Type for Pay-As-You-Go traffic.", "Type for Priority Pay-As-You-Go traffic.", "Type for Flex traffic.", "Type for Provisioned Throughput traffic." ], "enum": [ "TRAFFIC_TYPE_UNSPECIFIED", "ON_DEMAND", "ON_DEMAND_PRIORITY", "ON_DEMAND_FLEX", "PROVISIONED_THROUGHPUT" ], "description": "Output only. The traffic type for this request." }, "toolUsePromptTokenCount": { "format": "int32", "description": "Output only. The number of tokens in the results from tool executions, which are provided back to the model as input, if applicable.", "readOnly": true, "type": "integer" }, "cacheTokensDetails": { "description": "Output only. A detailed breakdown of the token count for each modality in the cached content.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" } } }, "description": "Usage metadata about the content generation request and response. This message provides a detailed breakdown of token usage and other relevant metrics.", "id": "GoogleCloudAiplatformV1beta1UsageMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequest": { "description": "Request message for FeaturestoreService.DeleteFeatureValues.", "properties": { "selectEntity": { "$ref": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectEntity", "description": "Select feature values to be deleted by specifying entities." }, "selectTimeRangeAndFeature": { "$ref": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectTimeRangeAndFeature", "description": "Select feature values to be deleted by specifying time range and features." } }, "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectoryRecallInput": { "properties": { "metricSpec": { "description": "Required. Spec for TrajectoryRecall metric.", "$ref": "GoogleCloudAiplatformV1beta1TrajectoryRecallSpec" }, "instances": { "description": "Required. Repeated TrajectoryRecall instance.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectoryRecallInstance" } } }, "description": "Instances and metric spec for TrajectoryRecall metric.", "id": "GoogleCloudAiplatformV1beta1TrajectoryRecallInput", "type": "object" }, "GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethodLastEntry": { "properties": {}, "description": "Configuration for using only the last entry of the conversation history as the search key.", "id": "GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethodLastEntry", "type": "object" }, "GoogleCloudAiplatformV1beta1RagFileMetadataConfig": { "id": "GoogleCloudAiplatformV1beta1RagFileMetadataConfig", "type": "object", "description": "Metadata config for RagFile.", "properties": { "gcsMetadataSource": { "description": "Google Cloud Storage location. Supports importing individual files as well as entire Google Cloud Storage directories. Sample formats: - `gs://bucket_name/my_directory/object_name/metadata.json` - `gs://bucket_name/my_directory` If the user provides a directory, the metadata will be read from the files that ends with \"metadata.json\" in the directory.", "$ref": "GoogleCloudAiplatformV1beta1GcsSource" }, "googleDriveMetadataSource": { "description": "Google Drive location. Supports importing individual files as well as Google Drive folders. If the user provides a directory, the metadata will be read from the files that ends with \"metadata.json\" in the directory.", "$ref": "GoogleCloudAiplatformV1beta1GoogleDriveSource" }, "inlineMetadataSource": { "description": "Inline metadata source. Must be a JSON string.", "type": "string" }, "gcsMetadataSchemaSource": { "description": "Google Cloud Storage location. Supports importing individual files as well as entire Google Cloud Storage directories. Sample formats: - `gs://bucket_name/my_directory/object_name/metadata_schema.json` - `gs://bucket_name/my_directory` If the user provides a directory, the metadata schema will be read from the files that ends with \"metadata_schema.json\" in the directory.", "$ref": "GoogleCloudAiplatformV1beta1GcsSource" }, "inlineMetadataSchemaSource": { "description": "Inline metadata schema source. Must be a JSON string.", "type": "string" }, "googleDriveMetadataSchemaSource": { "description": "Google Drive location. Supports importing individual files as well as Google Drive folders. If the user provides a folder, the metadata schema will be read from the files that ends with \"metadata_schema.json\" in the directory.", "$ref": "GoogleCloudAiplatformV1beta1GoogleDriveSource" } } }, "CloudAiLargeModelsVisionGenerateVideoExperimentsConditioningFrame": { "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsConditioningFrame", "type": "object", "properties": { "image": { "description": "The image data for this conditioning frame.", "$ref": "CloudAiLargeModelsVisionGenerateVideoRequestImage" }, "frameNum": { "description": "The index of the frame, starts with zero and must be a multiple of 8.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1beta1CandidateResult": { "properties": { "candidate": { "description": "Required. The candidate that is being evaluated. The value is the same as the candidate name in the EvaluationRequest.", "type": "string" }, "explanation": { "description": "Optional. The explanation for the metric.", "type": "string" }, "additionalResults": { "description": "Optional. Additional results for the metric.", "type": "any" }, "rubricVerdicts": { "description": "Optional. The rubric verdicts for the metric.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RubricVerdict" } }, "score": { "format": "float", "description": "Optional. The score for the metric.", "type": "number" }, "metric": { "description": "Required. The metric that was evaluated.", "type": "string" } }, "description": "Result for a single candidate.", "id": "GoogleCloudAiplatformV1beta1CandidateResult", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry": { "properties": { "observedQuantile": { "type": "number", "description": "This is a custom metric that calculates the percentage of true values that were less than the predicted value for that quantile. Only populated when optimization_objective is minimize-quantile-loss and each entry corresponds to an entry in quantiles The percent value can be used to compare with the quantile value, which is the target value.", "format": "double" }, "quantile": { "type": "number", "description": "The quantile for this entry.", "format": "double" }, "scaledPinballLoss": { "type": "number", "format": "float", "description": "The scaled pinball loss of this quantile." } }, "description": "Entry for the Quantiles loss type optimization objective.", "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtable": { "properties": { "autoScaling": { "description": "Required. Autoscaling config applied to Bigtable Instance.", "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableAutoScaling" }, "bigtableMetadata": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableBigtableMetadata", "description": "Output only. Metadata of the Bigtable instance. Output only." }, "zone": { "description": "Optional. The zone where the underlying Bigtable cluster for the primary Bigtable instance will be provisioned. Only the zone must be provided. For example, only \"us-central1-a\" should be provided.", "type": "string" }, "enableDirectBigtableAccess": { "description": "Optional. It true, enable direct access to the Bigtable instance.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtable", "type": "object" }, "GoogleCloudAiplatformV1beta1AuthConfigOidcConfig": { "id": "GoogleCloudAiplatformV1beta1AuthConfigOidcConfig", "type": "object", "description": "Config for user OIDC auth.", "properties": { "serviceAccount": { "description": "The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).", "type": "string" }, "idToken": { "description": "OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoClassificationPredictionResult": { "description": "Prediction output format for Video Classification.", "properties": { "id": { "description": "The resource ID of the AnnotationSpec that had been identified.", "type": "string" }, "displayName": { "description": "The display name of the AnnotationSpec that had been identified.", "type": "string" }, "timeSegmentStart": { "description": "The beginning, inclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end. Note that for 'segment-classification' prediction type, this equals the original 'timeSegmentStart' from the input instance, for other types it is the start of a shot or a 1 second interval respectively.", "format": "google-duration", "type": "string" }, "confidence": { "format": "float", "description": "The Model's confidence in correction of this prediction, higher value means higher confidence.", "type": "number" }, "type": { "description": "The type of the prediction. The requested types can be configured via parameters. This will be one of - segment-classification - shot-classification - one-sec-interval-classification", "type": "string" }, "timeSegmentEnd": { "type": "string", "format": "google-duration", "description": "The end, exclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end. Note that for 'segment-classification' prediction type, this equals the original 'timeSegmentEnd' from the input instance, for other types it is the end of a shot or a 1 second interval respectively." } }, "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoClassificationPredictionResult", "type": "object" }, "GoogleCloudAiplatformV1beta1PartialArg": { "description": "Partial argument value of the function call.", "properties": { "stringValue": { "description": "Optional. Represents a string value.", "type": "string" }, "willContinue": { "description": "Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.", "type": "boolean" }, "numberValue": { "type": "number", "format": "double", "description": "Optional. Represents a double value." }, "boolValue": { "description": "Optional. Represents a boolean value.", "type": "boolean" }, "jsonPath": { "description": "Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. \"$.foo.bar[0].data\".", "type": "string" }, "nullValue": { "type": "string", "enumDescriptions": [ "Null value." ], "enum": [ "NULL_VALUE" ], "description": "Optional. Represents a null value." } }, "id": "GoogleCloudAiplatformV1beta1PartialArg", "type": "object" }, "GoogleCloudAiplatformV1beta1FluencyResult": { "description": "Spec for fluency result.", "properties": { "explanation": { "description": "Output only. Explanation for fluency score.", "type": "string", "readOnly": true }, "confidence": { "description": "Output only. Confidence for fluency score.", "format": "float", "type": "number", "readOnly": true }, "score": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Fluency score." } }, "id": "GoogleCloudAiplatformV1beta1FluencyResult", "type": "object" }, "GoogleCloudAiplatformV1beta1AggregationResult": { "properties": { "exactMatchMetricValue": { "$ref": "GoogleCloudAiplatformV1beta1ExactMatchMetricValue", "description": "Results for exact match metric." }, "customCodeExecutionResult": { "$ref": "GoogleCloudAiplatformV1beta1CustomCodeExecutionResult", "description": "Result for code execution metric." }, "rougeMetricValue": { "$ref": "GoogleCloudAiplatformV1beta1RougeMetricValue", "description": "Results for rouge metric." }, "aggregationMetric": { "type": "string", "enumDescriptions": [ "Unspecified aggregation metric.", "Average aggregation metric. Not supported for Pairwise metric.", "Mode aggregation metric.", "Standard deviation aggregation metric. Not supported for pairwise metric.", "Variance aggregation metric. Not supported for pairwise metric.", "Minimum aggregation metric. Not supported for pairwise metric.", "Maximum aggregation metric. Not supported for pairwise metric.", "Median aggregation metric. Not supported for pairwise metric.", "90th percentile aggregation metric. Not supported for pairwise metric.", "95th percentile aggregation metric. Not supported for pairwise metric.", "99th percentile aggregation metric. Not supported for pairwise metric." ], "enum": [ "AGGREGATION_METRIC_UNSPECIFIED", "AVERAGE", "MODE", "STANDARD_DEVIATION", "VARIANCE", "MINIMUM", "MAXIMUM", "MEDIAN", "PERCENTILE_P90", "PERCENTILE_P95", "PERCENTILE_P99" ], "description": "Aggregation metric." }, "pointwiseMetricResult": { "$ref": "GoogleCloudAiplatformV1beta1PointwiseMetricResult", "description": "Result for pointwise metric." }, "bleuMetricValue": { "$ref": "GoogleCloudAiplatformV1beta1BleuMetricValue", "description": "Results for bleu metric." }, "pairwiseMetricResult": { "$ref": "GoogleCloudAiplatformV1beta1PairwiseMetricResult", "description": "Result for pairwise metric." } }, "description": "The aggregation result for a single metric.", "id": "GoogleCloudAiplatformV1beta1AggregationResult", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigGenerationConfig": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigGenerationConfig", "type": "object", "description": "Configuration for how to generate memories.", "properties": { "model": { "description": "Optional. The model used to generate memories. Format: `projects/{project}/locations/{location}/publishers/google/models/{model}`.", "type": "string" }, "generationTriggerConfig": { "$ref": "GoogleCloudAiplatformV1beta1MemoryGenerationTriggerConfig", "description": "Optional. Specifies the default trigger configuration for generating memories using `IngestEvents`." } } }, "GoogleCloudLocationListLocationsResponse": { "properties": { "locations": { "description": "A list of locations that matches the specified filter in the request.", "type": "array", "items": { "$ref": "GoogleCloudLocationLocation" } }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "description": "The response message for Locations.ListLocations.", "id": "GoogleCloudLocationListLocationsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureValueMetadata": { "id": "GoogleCloudAiplatformV1beta1FeatureValueMetadata", "type": "object", "description": "Metadata of feature value.", "properties": { "generateTime": { "type": "string", "format": "google-datetime", "description": "Feature generation timestamp. Typically, it is provided by user at feature ingestion time. If not, feature store will use the system timestamp when the data is ingested into feature store. Legacy Feature Store: For streaming ingestion, the time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future." } } }, "GoogleCloudAiplatformV1beta1FulfillmentSpec": { "description": "Spec for fulfillment metric.", "properties": { "version": { "format": "int32", "description": "Optional. Which version to use for evaluation.", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1FulfillmentSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1TaskStateChange": { "id": "GoogleCloudAiplatformV1beta1TaskStateChange", "type": "object", "properties": { "newState": { "enum": [ "STATE_UNSPECIFIED", "SUBMITTED", "WORKING", "COMPLETED", "CANCELLED", "FAILED", "REJECTED", "INPUT_REQUIRED", "AUTH_REQUIRED", "PAUSED" ], "description": "Required. The new state of the task.", "type": "string", "enumDescriptions": [ "Task state unspecified. Default value if not set.", "Task is submitted and waiting to be processed.", "Task is actively being processed.", "Task is finished.", "Task is cancelled.", "Task has failed.", "Task is rejected by the system.", "Task requires input from the user.", "Task requires auth (e.g. OAuth) from the user.", "Task is paused." ] } }, "description": "A message representing a change in a task's state." }, "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInput": { "properties": { "metricSpec": { "description": "Required. Spec for tool parameter key match metric.", "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchSpec" }, "instances": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInstance" }, "description": "Required. Repeated tool parameter key match instances." } }, "description": "Input for tool parameter key match metric.", "id": "GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInput", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequest": { "id": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequest", "type": "object", "description": "Request message for FeatureOnlineStoreService.FeatureViewDirectWrite.", "properties": { "dataKeyAndFeatureValues": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValues" }, "description": "Required. The data keys and associated feature values." } } }, "GoogleCloudAiplatformV1beta1EvaluateDatasetRun": { "id": "GoogleCloudAiplatformV1beta1EvaluateDatasetRun", "type": "object", "description": "Evaluate Dataset Run Result for Tuning Job.", "properties": { "evaluationRun": { "description": "Output only. The resource name of the evaluation run. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run_id}`.", "readOnly": true, "type": "string" }, "operationName": { "type": "string", "readOnly": true, "deprecated": true, "description": "Output only. Deprecated: The updated architecture uses evaluation_run instead." }, "checkpointId": { "type": "string", "readOnly": true, "description": "Output only. The checkpoint id used in the evaluation run. Only populated when evaluating checkpoints." }, "error": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. The error of the evaluation run if any." }, "evaluateDatasetResponse": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1EvaluateDatasetResponse", "description": "Output only. Results for EvaluationService." } } }, "GoogleCloudAiplatformV1beta1MemoryConjunctionFilter": { "id": "GoogleCloudAiplatformV1beta1MemoryConjunctionFilter", "type": "object", "description": "A conjunction of filters that will be combined using AND logic.", "properties": { "filters": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryFilter" }, "description": "Represents filters that will be combined using AND logic." } } }, "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenFineTuningPipelines": { "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenFineTuningPipelines", "type": "object", "description": "Open fine tuning pipelines.", "properties": { "fineTuningPipelines": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences" }, "description": "Required. Regional resource references to fine tuning pipelines." } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation", "type": "object", "properties": { "columnName": { "type": "string" } }, "description": "Treats the column as categorical array and performs following transformation functions. * For each element in the array, convert the category name to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean. * Empty arrays treated as an embedding of zeroes." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation", "type": "object", "properties": { "columnName": { "type": "string" } }, "description": "Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the \"unknown\" category. The \"unknown\" category gets its own special lookup index and resulting embedding." }, "GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig": { "description": "Config for Google Service Account Authentication.", "properties": { "serviceAccount": { "description": "Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1AutoscalingMetricSpec": { "description": "The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.", "properties": { "metricName": { "description": "Required. The resource metric name. Supported metrics: * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle` * `aiplatform.googleapis.com/prediction/online/cpu/utilization` * `aiplatform.googleapis.com/prediction/online/request_count` * `pubsub.googleapis.com/subscription/num_undelivered_messages` * `prometheus.googleapis.com/vertex_dcgm_fi_dev_gpu_util` * `prometheus.googleapis.com/vertex_vllm_gpu_cache_usage_perc` * `prometheus.googleapis.com/vertex_vllm_num_requests_waiting`", "type": "string" }, "target": { "type": "integer", "format": "int32", "description": "The target resource utilization in percentage (1% - 100%) for the given metric; once the real usage deviates from the target by a certain percentage, the machine replicas change. The default value is 60 (representing 60%) if not provided." }, "monitoredResourceLabels": { "description": "Optional. The Cloud Monitoring monitored resource labels as key value pairs used for metrics filtering. See Cloud Monitoring Labels https://cloud.google.com/monitoring/api/v3/metric-model#generic-label-info", "type": "object", "additionalProperties": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1beta1AutoscalingMetricSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateModelMonitoringJobRequest": { "properties": { "parent": { "description": "Required. The parent of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMoniitors/{model_monitor}`", "type": "string" }, "modelMonitoringJob": { "description": "Required. The ModelMonitoringJob to create", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJob" }, "modelMonitoringJobId": { "description": "Optional. The ID to use for the Model Monitoring Job, which will become the final component of the model monitoring job resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.", "type": "string" } }, "description": "Request message for ModelMonitoringService.CreateModelMonitoringJob.", "id": "GoogleCloudAiplatformV1beta1CreateModelMonitoringJobRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfigTrafficSplitManual": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfigTrafficSplitManual", "type": "object", "description": "Manual traffic distribution configuration, where the user specifies the Runtime Revision IDs and the percentage of traffic to send to each.", "properties": { "targets": { "description": "A list of traffic targets for the Runtimes Revisions. The sum of percentages must equal to 100.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineTrafficConfigTrafficSplitManualTarget" } } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig": { "description": "Configuration for exporting test set predictions to a BigQuery table.", "properties": { "destinationBigqueryUri": { "description": "URI of desired destination BigQuery table. Expected format: `bq://{project_id}:{dataset_id}:{table}` If not specified, then results are exported to the following auto-created BigQuery table: `{project_id}:export_evaluated_examples_{model_name}_{yyyy_MM_dd'T'HH_mm_ss_SSS'Z'}.evaluated_examples`", "type": "string" }, "overrideExistingTable": { "description": "If true and an export destination is specified, then the contents of the destination are overwritten. Otherwise, if the export destination already exists, then the export operation fails.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1GroundednessInstance": { "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "context": { "description": "Required. Background information provided in context used to compare against the prediction.", "type": "string" } }, "description": "Spec for groundedness instance.", "id": "GoogleCloudAiplatformV1beta1GroundednessInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectMemoriesSourceDirectMemory": { "id": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectMemoriesSourceDirectMemory", "type": "object", "properties": { "fact": { "description": "Required. The fact to consolidate with existing memories.", "type": "string" }, "topics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryTopicId" }, "description": "Optional. The topics that the consolidated memories should be associated with." } }, "description": "A direct memory to upload to Memory Bank." }, "GoogleCloudAiplatformV1beta1ModelMonitoringInputVertexEndpointLogs": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInputVertexEndpointLogs", "type": "object", "description": "Data from Vertex AI Endpoint request response logging.", "properties": { "endpoints": { "description": "List of endpoint resource names. The endpoints must enable the logging with the [Endpoint].[request_response_logging_config], and must contain the deployed model corresponding to the model version specified in [ModelMonitor].[model_monitoring_target].", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1ListTuningJobsResponse": { "properties": { "tuningJobs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TuningJob" }, "description": "The tuning jobs that match the request." }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass this token in a subsequent [GenAiTuningService.ListTuningJobs] call to retrieve the next page of results.", "type": "string" } }, "description": "Response message for GenAiTuningService.ListTuningJobs", "id": "GoogleCloudAiplatformV1beta1ListTuningJobsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation", "type": "object", "description": "Treats the column as numerical array and performs following transformation functions. * All transformations for Numerical types applied to the average of the all elements. * The average of empty arrays is treated as zero.", "properties": { "columnName": { "type": "string" }, "invalidValuesAllowed": { "description": "If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySource": { "properties": { "featureGroups": { "description": "Required. List of features that need to be synced to Online Store.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySourceFeatureGroup" } }, "projectNumber": { "description": "Optional. The project number of the parent project of the Feature Groups.", "format": "int64", "type": "string" } }, "description": "A Feature Registry source for features that need to be synced to Online Store.", "id": "GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySource", "type": "object" }, "GoogleCloudAiplatformV1beta1LossCluster": { "properties": { "taxonomyEntry": { "$ref": "GoogleCloudAiplatformV1beta1LossTaxonomyEntry", "description": "The structured definition of the loss taxonomy for this cluster." }, "itemCount": { "type": "integer", "description": "The total number of EvaluationItems falling into this cluster.", "format": "int32" }, "examples": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LossExample" }, "description": "A list of examples that belong to this cluster. This links the cluster back to the specific EvaluationItems and Rubrics." }, "clusterId": { "description": "Unique identifier for the loss cluster within the scope of the analysis result.", "type": "string" } }, "description": "Represents a semantic grouping of failures (e.g., \"Hallucination of Action\").", "id": "GoogleCloudAiplatformV1beta1LossCluster", "type": "object" }, "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfig": { "id": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfig", "type": "object", "properties": { "snapshotAnalysis": { "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigSnapshotAnalysis", "description": "The config for Snapshot Analysis Based Feature Monitoring." }, "importFeaturesAnalysis": { "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigImportFeaturesAnalysis", "description": "The config for ImportFeatures Analysis Based Feature Monitoring." }, "numericalThresholdConfig": { "description": "Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).", "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigThresholdConfig" }, "categoricalThresholdConfig": { "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigThresholdConfig", "description": "Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING)." } }, "description": "Configuration of how features in Featurestore are monitored." }, "GoogleCloudAiplatformV1beta1StoredContentsExampleFilter": { "description": "The metadata filters that will be used to remove or fetch StoredContentsExamples. If a field is unspecified, then no filtering for that field will be applied.", "properties": { "searchKeys": { "type": "array", "items": { "type": "string" }, "description": "Optional. The search keys for filtering. Only examples with one of the specified search keys (StoredContentsExample.search_key) are eligible to be returned." }, "functionNames": { "$ref": "GoogleCloudAiplatformV1beta1ExamplesArrayFilter", "description": "Optional. The function names for filtering." } }, "id": "GoogleCloudAiplatformV1beta1StoredContentsExampleFilter", "type": "object" }, "GoogleCloudAiplatformV1beta1PscAutomatedEndpoints": { "id": "GoogleCloudAiplatformV1beta1PscAutomatedEndpoints", "type": "object", "properties": { "projectId": { "description": "Corresponding project_id in pscAutomationConfigs", "type": "string" }, "matchAddress": { "description": "Ip Address created by the automated forwarding rule.", "type": "string" }, "network": { "description": "Corresponding network in pscAutomationConfigs.", "type": "string" } }, "description": "PscAutomatedEndpoints defines the output of the forwarding rule automatically created by each PscAutomationConfig." }, "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfig": { "id": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfig", "type": "object", "description": "Config for the embedding model to use for RAG.", "properties": { "hybridSearchConfig": { "description": "Configuration for hybrid search.", "$ref": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigHybridSearchConfig" }, "vertexPredictionEndpoint": { "description": "The Vertex AI Prediction Endpoint that either refers to a publisher model or an endpoint that is hosting a 1P fine-tuned text embedding model. Endpoints hosting non-1P fine-tuned text embedding models are currently not supported. This is used for dense vector search.", "$ref": "GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigVertexPredictionEndpoint" } } }, "GoogleCloudAiplatformV1beta1NotebookExecutionJob": { "properties": { "displayName": { "description": "The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "scheduleResourceName": { "description": "The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`", "type": "string" }, "serviceAccount": { "description": "The service account to run the execution as.", "type": "string" }, "jobState": { "type": "string", "enumDescriptions": [ "The job state is unspecified.", "The job has been just created or resumed and processing has not yet begun.", "The service is preparing to run the job.", "The job is in progress.", "The job completed successfully.", "The job failed.", "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "The job has been cancelled.", "The job has been stopped, and can be resumed.", "The job has expired.", "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", "The job is partially succeeded, some results may be missing due to errors." ], "readOnly": true, "description": "Output only. The state of the NotebookExecutionJob.", "enum": [ "JOB_STATE_UNSPECIFIED", "JOB_STATE_QUEUED", "JOB_STATE_PENDING", "JOB_STATE_RUNNING", "JOB_STATE_SUCCEEDED", "JOB_STATE_FAILED", "JOB_STATE_CANCELLING", "JOB_STATE_CANCELLED", "JOB_STATE_PAUSED", "JOB_STATE_EXPIRED", "JOB_STATE_UPDATING", "JOB_STATE_PARTIALLY_SUCCEEDED" ] }, "gcsNotebookSource": { "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJobGcsNotebookSource", "description": "The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`" }, "customEnvironmentSpec": { "description": "The custom compute configuration for an execution job.", "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJobCustomEnvironmentSpec" }, "notebookRuntimeTemplateResourceName": { "description": "The NotebookRuntimeTemplate to source compute configuration from.", "type": "string" }, "executionTimeout": { "type": "string", "description": "Max running time of the execution job in seconds (default 86400s / 24 hrs).", "format": "google-duration" }, "directNotebookSource": { "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJobDirectNotebookSource", "description": "The contents of an input notebook file." }, "name": { "description": "Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`", "type": "string", "readOnly": true }, "encryptionSpec": { "description": "Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookRuntimeTemplate has an encryption spec.", "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" }, "executionUser": { "description": "The user email to run the execution as. Only supported by Colab runtimes.", "type": "string" }, "dataformRepositorySource": { "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJobDataformRepositorySource", "description": "The Dataform Repository pointing to a single file notebook repository." }, "gcsOutputUri": { "description": "The Cloud Storage location to upload the result to. Format: `gs://bucket-name`", "type": "string" }, "workbenchRuntime": { "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJobWorkbenchRuntime", "description": "The Workbench runtime configuration to use for the notebook execution." }, "kernelName": { "description": "The name of the kernel to use during notebook execution. If unset, the default kernel is used.", "type": "string" }, "status": { "description": "Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this NotebookExecutionJob was created." }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this NotebookExecutionJob was most recently updated.", "format": "google-datetime" } }, "description": "NotebookExecutionJob represents an instance of a notebook execution.", "id": "GoogleCloudAiplatformV1beta1NotebookExecutionJob", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation", "type": "object", "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index.", "properties": { "columnName": { "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoActionRecognitionPredictionResult": { "description": "Prediction output format for Video Action Recognition.", "properties": { "timeSegmentStart": { "type": "string", "format": "google-duration", "description": "The beginning, inclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end." }, "confidence": { "type": "number", "description": "The Model's confidence in correction of this prediction, higher value means higher confidence.", "format": "float" }, "id": { "description": "The resource ID of the AnnotationSpec that had been identified.", "type": "string" }, "displayName": { "description": "The display name of the AnnotationSpec that had been identified.", "type": "string" }, "timeSegmentEnd": { "type": "string", "description": "The end, exclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end.", "format": "google-duration" } }, "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoActionRecognitionPredictionResult", "type": "object" }, "GoogleCloudAiplatformV1beta1MigrateResourceResponse": { "id": "GoogleCloudAiplatformV1beta1MigrateResourceResponse", "type": "object", "properties": { "dataset": { "description": "Migrated Dataset's resource name.", "type": "string" }, "migratableResource": { "$ref": "GoogleCloudAiplatformV1beta1MigratableResource", "description": "Before migration, the identifier in ml.googleapis.com, automl.googleapis.com or datalabeling.googleapis.com." }, "model": { "description": "Migrated Model's resource name.", "type": "string" } }, "description": "Describes a successfully migrated resource." }, "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecMetricSpec": { "properties": { "metricId": { "description": "Required. The ID of the metric. Must not contain whitespaces.", "type": "string" }, "goal": { "type": "string", "enumDescriptions": [ "Goal Type will default to maximize.", "Maximize the goal metric.", "Minimize the goal metric." ], "enum": [ "GOAL_TYPE_UNSPECIFIED", "MAXIMIZE", "MINIMIZE" ], "description": "Required. The optimization goal of the metric." } }, "description": "Represents a metric to optimize.", "id": "GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecMetricSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeploy": { "properties": { "largeModelReference": { "description": "Optional. Large model reference. When this is set, model_artifact_spec is not needed.", "$ref": "GoogleCloudAiplatformV1beta1LargeModelReference" }, "title": { "description": "Required. The title of the regional resource reference.", "type": "string" }, "dedicatedResources": { "description": "A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.", "$ref": "GoogleCloudAiplatformV1beta1DedicatedResources" }, "containerSpec": { "description": "Optional. The specification of the container that is to be used when deploying this Model in Vertex AI. Not present for Large Models.", "$ref": "GoogleCloudAiplatformV1beta1ModelContainerSpec" }, "automaticResources": { "description": "A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.", "$ref": "GoogleCloudAiplatformV1beta1AutomaticResources" }, "sharedResources": { "description": "The resource name of the shared DeploymentResourcePool to deploy on. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", "type": "string" }, "deployTaskName": { "description": "Optional. The name of the deploy task (e.g., \"text to image generation\").", "type": "string" }, "deployMetadata": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployDeployMetadata", "description": "Optional. Metadata information about this deployment config." }, "publicArtifactUri": { "description": "Optional. The signed URI for ephemeral Cloud Storage access to model artifact.", "type": "string" }, "modelDisplayName": { "description": "Optional. Default model display name.", "type": "string" }, "artifactUri": { "description": "Optional. The path to the directory containing the Model artifact and any of its supporting files.", "type": "string" } }, "description": "Model metadata that is needed for UploadModel or DeployModel/CreateEndpoint requests.", "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeploy", "type": "object" }, "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate": { "id": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate", "type": "object", "description": "A template that specifies runtime configurations such as machine type, runtime version, network configurations, etc. Multiple runtimes can be created from a runtime template.", "properties": { "softwareConfig": { "$ref": "GoogleCloudAiplatformV1beta1NotebookSoftwareConfig", "description": "Optional. The notebook software configuration of the notebook runtime." }, "name": { "description": "The resource name of the NotebookRuntimeTemplate.", "type": "string" }, "shieldedVmConfig": { "description": "Optional. Immutable. Runtime Shielded VM spec.", "$ref": "GoogleCloudAiplatformV1beta1ShieldedVmConfig" }, "serviceAccount": { "type": "string", "deprecated": true, "description": "Deprecated: This field is ignored and the \"Vertex AI Notebook Service Account\" (service-PROJECT_NUMBER@gcp-sa-aiplatform-vm.iam.gserviceaccount.com) is used for the runtime workload identity. See https://cloud.google.com/iam/docs/service-agents#vertex-ai-notebook-service-account for more details. For NotebookExecutionJob, use NotebookExecutionJob.service_account instead. The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used." }, "displayName": { "description": "Required. The display name of the NotebookRuntimeTemplate. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "networkSpec": { "$ref": "GoogleCloudAiplatformV1beta1NetworkSpec", "description": "Optional. Network spec." }, "reservationAffinity": { "$ref": "GoogleCloudAiplatformV1beta1NotebookReservationAffinity", "description": "Optional. Reservation Affinity of the notebook runtime template." }, "description": { "description": "The description of the NotebookRuntimeTemplate.", "type": "string" }, "notebookRuntimeType": { "type": "string", "enumDescriptions": [ "Unspecified notebook runtime type, NotebookRuntimeType will default to USER_DEFINED.", "runtime or template with coustomized configurations from user.", "runtime or template with system defined configurations." ], "enum": [ "NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED", "USER_DEFINED", "ONE_CLICK" ], "description": "Optional. Immutable. The type of the notebook runtime template." }, "createTime": { "description": "Output only. Timestamp when this NotebookRuntimeTemplate was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "isDefault": { "type": "boolean", "readOnly": true, "deprecated": true, "description": "Output only. Deprecated: This field has no behavior. Use notebook_runtime_type = 'ONE_CLICK' instead. The default template to use if not specified." }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this NotebookRuntimeTemplate was most recently updated.", "readOnly": true, "type": "string" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize the NotebookRuntimeTemplates. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." }, "idleShutdownConfig": { "$ref": "GoogleCloudAiplatformV1beta1NotebookIdleShutdownConfig", "description": "The idle shutdown configuration of NotebookRuntimeTemplate. This config will only be set when idle shutdown is enabled." }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key spec for the notebook runtime." }, "networkTags": { "type": "array", "items": { "type": "string" }, "description": "Optional. The Compute Engine tags to add to runtime (see [Tagging instances](https://cloud.google.com/vpc/docs/add-remove-network-tags))." }, "dataPersistentDiskSpec": { "description": "Optional. The specification of persistent disk attached to the runtime as data disk storage.", "$ref": "GoogleCloudAiplatformV1beta1PersistentDiskSpec" }, "machineSpec": { "description": "Optional. Immutable. The specification of a single machine for the template.", "$ref": "GoogleCloudAiplatformV1beta1MachineSpec" }, "eucConfig": { "$ref": "GoogleCloudAiplatformV1beta1NotebookEucConfig", "description": "EUC configuration of the NotebookRuntimeTemplate." } } }, "GoogleCloudAiplatformV1beta1ArtifactTypeSchema": { "properties": { "schemaUri": { "description": "Points to a YAML file stored on Cloud Storage describing the format. Deprecated. Use PipelineArtifactTypeSchema.schema_title or PipelineArtifactTypeSchema.instance_schema instead.", "type": "string", "deprecated": true }, "instanceSchema": { "description": "Contains a raw YAML string, describing the format of the properties of the type.", "type": "string" }, "schemaVersion": { "description": "The schema version of the artifact. If the value is not set, it defaults to the latest version in the system.", "type": "string" }, "schemaTitle": { "description": "The name of the type. The format of the title must be: `.`. Examples: - `aiplatform.Model` - `acme.CustomModel` When this field is set, the type must be pre-registered in the MLMD store.", "type": "string" } }, "description": "The definition of a artifact type in MLMD.", "id": "GoogleCloudAiplatformV1beta1ArtifactTypeSchema", "type": "object" }, "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectEntity": { "id": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectEntity", "type": "object", "description": "Response message if the request uses the SelectEntity option.", "properties": { "offlineStorageDeletedEntityRowCount": { "format": "int64", "description": "The count of deleted entity rows in the offline storage. Each row corresponds to the combination of an entity ID and a timestamp. One entity ID can have multiple rows in the offline storage.", "type": "string" }, "onlineStorageDeletedEntityCount": { "format": "int64", "description": "The count of deleted entities in the online storage. Each entity ID corresponds to one entity.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ExportModelRequest": { "description": "Request message for ModelService.ExportModel.", "properties": { "outputConfig": { "description": "Required. The desired output location and configuration.", "$ref": "GoogleCloudAiplatformV1beta1ExportModelRequestOutputConfig" } }, "id": "GoogleCloudAiplatformV1beta1ExportModelRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateEgressControlConfig": { "properties": { "internetAccess": { "description": "Optional. Whether to allow internet access.", "type": "boolean" } }, "description": "Configuration for egress control of sandbox instances.", "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplateEgressControlConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageObjectDetectionPredictionInstance": { "properties": { "content": { "description": "The image bytes or Cloud Storage URI to make the prediction on.", "type": "string" }, "mimeType": { "description": "The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon", "type": "string" } }, "description": "Prediction input format for Image Object Detection.", "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageObjectDetectionPredictionInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfig": { "properties": { "fixedNodeCount": { "description": "The number of nodes for the online store. The number of nodes doesn't scale automatically, but you can manually update the number of nodes. If set to 0, the featurestore will not have an online store and cannot be used for online serving.", "format": "int32", "type": "integer" }, "scaling": { "description": "Online serving scaling configuration. Only one of `fixed_node_count` and `scaling` can be set. Setting one will reset the other.", "$ref": "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfigScaling" } }, "description": "OnlineServingConfig specifies the details for provisioning online serving resources.", "id": "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchCreateFeaturesOperationMetadata": { "properties": { "genericMetadata": { "description": "Operation metadata for Feature.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Details of operations that perform batch create Features.", "id": "GoogleCloudAiplatformV1beta1BatchCreateFeaturesOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1OnlineEvaluatorConfig": { "id": "GoogleCloudAiplatformV1beta1OnlineEvaluatorConfig", "type": "object", "description": "Configuration for sampling behavior of the OnlineEvaluator. The OnlineEvaluator runs at a fixed interval of 10 minutes.", "properties": { "randomSampling": { "description": "Random sampling method.", "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluatorConfigRandomSampling" }, "maxEvaluatedSamplesPerRun": { "format": "int64", "description": "Optional. The maximum number of evaluations to perform per run. If set to 0, the number is unbounded.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1AssessDataRequest": { "id": "GoogleCloudAiplatformV1beta1AssessDataRequest", "type": "object", "properties": { "tuningValidationAssessmentConfig": { "$ref": "GoogleCloudAiplatformV1beta1AssessDataRequestTuningValidationAssessmentConfig", "description": "Optional. Configuration for the tuning validation assessment." }, "batchPredictionValidationAssessmentConfig": { "$ref": "GoogleCloudAiplatformV1beta1AssessDataRequestBatchPredictionValidationAssessmentConfig", "description": "Optional. Configuration for the batch prediction validation assessment." }, "tuningResourceUsageAssessmentConfig": { "$ref": "GoogleCloudAiplatformV1beta1AssessDataRequestTuningResourceUsageAssessmentConfig", "description": "Optional. Configuration for the tuning resource usage assessment." }, "batchPredictionResourceUsageAssessmentConfig": { "$ref": "GoogleCloudAiplatformV1beta1AssessDataRequestBatchPredictionResourceUsageAssessmentConfig", "description": "Optional. Configuration for the batch prediction resource usage assessment." }, "geminiRequestReadConfig": { "$ref": "GoogleCloudAiplatformV1beta1GeminiRequestReadConfig", "description": "Optional. The Gemini request read config for the dataset." } }, "description": "Request message for DatasetService.AssessData. Used only for MULTIMODAL datasets." }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetrics", "type": "object", "description": "Metrics for forecasting evaluation results.", "properties": { "meanAbsoluteError": { "type": "number", "format": "float", "description": "Mean Absolute Error (MAE)." }, "rootMeanSquaredLogError": { "format": "float", "description": "Root mean squared log error. Undefined when there are negative ground truth values or predictions.", "type": "number" }, "weightedAbsolutePercentageError": { "type": "number", "format": "float", "description": "Weighted Absolute Percentage Error. Does not use weights, this is just what the metric is called. Undefined if actual values sum to zero. Will be very large if actual values sum to a very small number." }, "rootMeanSquaredError": { "type": "number", "format": "float", "description": "Root Mean Squared Error (RMSE)." }, "meanAbsolutePercentageError": { "type": "number", "description": "Mean absolute percentage error. Infinity when there are zeros in the ground truth.", "format": "float" }, "rSquared": { "format": "float", "description": "Coefficient of determination as Pearson correlation coefficient. Undefined when ground truth or predictions are constant or near constant.", "type": "number" }, "rootMeanSquaredPercentageError": { "type": "number", "format": "float", "description": "Root Mean Square Percentage Error. Square root of MSPE. Undefined/imaginary when MSPE is negative." }, "quantileMetrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry" }, "description": "The quantile metrics entries for each quantile." } } }, "GoogleCloudAiplatformV1beta1ReadIndexDatapointsRequest": { "id": "GoogleCloudAiplatformV1beta1ReadIndexDatapointsRequest", "type": "object", "description": "The request message for MatchService.ReadIndexDatapoints.", "properties": { "deployedIndexId": { "description": "The ID of the DeployedIndex that will serve the request.", "type": "string" }, "ids": { "type": "array", "items": { "type": "string" }, "description": "IDs of the datapoints to be searched for." } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig", "type": "object", "description": "The alert config for model monitoring.", "properties": { "emailAlertConfig": { "description": "Email alert config.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfigEmailAlertConfig" }, "notificationChannels": { "description": "Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`", "type": "array", "items": { "type": "string" } }, "enableLogging": { "description": "Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto ModelMonitoringStatsAnomalies. This can be further synced to Pub/Sub or any other services supported by Cloud Logging.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailContainerDetail": { "description": "The detail of a container execution. It contains the job names of the lifecycle of a container execution.", "properties": { "mainJob": { "description": "Output only. The name of the CustomJob for the main container execution.", "readOnly": true, "type": "string" }, "failedMainJobs": { "type": "array", "items": { "type": "string" }, "readOnly": true, "description": "Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order." }, "failedPreCachingCheckJobs": { "description": "Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.", "readOnly": true, "type": "array", "items": { "type": "string" } }, "preCachingCheckJob": { "description": "Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.", "type": "string", "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailContainerDetail", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputs": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputs", "type": "object", "properties": { "transformations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformation" }, "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter." }, "validationOptions": { "description": "Validation options for the data validation component. The available options are: * \"fail-pipeline\" - default, will validate against the validation and fail the pipeline if it fails. * \"ignore-validation\" - ignore the results of the validation and continue", "type": "string" }, "timeSeriesIdentifierColumn": { "description": "The name of the column that identifies the time series.", "type": "string" }, "timeColumn": { "description": "The name of the column that identifies time order in the time series. This column must be available at forecast.", "type": "string" }, "optimizationObjective": { "description": "Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). * \"minimize-mae\" - Minimize mean-absolute error (MAE). * \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE). * \"minimize-rmspe\" - Minimize root-mean-squared percentage error (RMSPE). * \"minimize-wape-mae\" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * \"minimize-quantile-loss\" - Minimize the quantile loss at the quantiles defined in `quantiles`. * \"minimize-mape\" - Minimize the mean absolute percentage error.", "type": "string" }, "exportEvaluatedDataItemsConfig": { "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig" }, "timeSeriesAttributeColumns": { "type": "array", "items": { "type": "string" }, "description": "Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color." }, "hierarchyConfig": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig", "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies." }, "holidayRegions": { "type": "array", "items": { "type": "string" }, "description": "The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option." }, "availableAtForecastColumns": { "description": "Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day.", "type": "array", "items": { "type": "string" } }, "contextWindow": { "description": "The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field.", "format": "int64", "type": "string" }, "trainBudgetMilliNodeHours": { "type": "string", "format": "int64", "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive." }, "weightColumn": { "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1. This column must be available at forecast.", "type": "string" }, "forecastHorizon": { "type": "string", "description": "The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field.", "format": "int64" }, "targetColumn": { "description": "The name of the column that the Model is to predict values for. This column must be unavailable at forecast.", "type": "string" }, "windowConfig": { "description": "Config containing strategy for generating sliding windows.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig" }, "additionalExperiments": { "type": "array", "items": { "type": "string" }, "description": "Additional experiment flags for the time series forcasting training." }, "unavailableAtForecastColumns": { "type": "array", "items": { "type": "string" }, "description": "Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day." }, "dataGranularity": { "description": "Expected difference in time granularity between rows in the data.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsGranularity" }, "quantiles": { "description": "Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique.", "type": "array", "items": { "type": "number", "format": "double" } } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation", "type": "object", "properties": { "timestamp": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation" }, "text": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation" }, "auto": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation" }, "numeric": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation" }, "categorical": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation" } } }, "GoogleCloudAiplatformV1beta1ExamplesArrayFilter": { "id": "GoogleCloudAiplatformV1beta1ExamplesArrayFilter", "type": "object", "properties": { "arrayOperator": { "type": "string", "enumDescriptions": [ "Not specified. This value should not be used.", "The metadata array field in the example must contain at least one of the values.", "The metadata array field in the example must contain all of the values." ], "description": "Required. The operator logic to use for filtering.", "enum": [ "ARRAY_OPERATOR_UNSPECIFIED", "CONTAINS_ANY", "CONTAINS_ALL" ] }, "values": { "type": "array", "items": { "type": "string" }, "description": "Required. The values by which to filter examples." } }, "description": "Filters for examples' array metadata fields. An array field is example metadata where multiple values are attributed to a single example." }, "GoogleCloudAiplatformV1beta1ToolCall": { "id": "GoogleCloudAiplatformV1beta1ToolCall", "type": "object", "properties": { "toolName": { "description": "Required. Spec for tool name", "type": "string" }, "toolInput": { "description": "Optional. Spec for tool input", "type": "string" } }, "description": "Spec for tool call." }, "GoogleCloudAiplatformV1beta1RagVectorDbConfigWeaviate": { "description": "The config for the Weaviate.", "properties": { "collectionName": { "description": "The corresponding collection this corpus maps to. This value cannot be changed after it's set.", "type": "string" }, "httpEndpoint": { "description": "Weaviate DB instance HTTP endpoint. e.g. 34.56.78.90:8080 Vertex RAG only supports HTTP connection to Weaviate. This value cannot be changed after it's set.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1RagVectorDbConfigWeaviate", "type": "object" }, "GoogleCloudAiplatformV1beta1StreamingPredictRequest": { "properties": { "inputs": { "description": "The prediction input.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tensor" } }, "parameters": { "description": "The parameters that govern the prediction.", "$ref": "GoogleCloudAiplatformV1beta1Tensor" } }, "description": "Request message for PredictionService.StreamingPredict. The first message must contain endpoint field and optionally input. The subsequent messages must contain input.", "id": "GoogleCloudAiplatformV1beta1StreamingPredictRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1MetadataStoreDataplexConfig": { "description": "Represents Dataplex integration settings.", "properties": { "enabledPipelinesLineage": { "description": "Optional. Whether or not Data Lineage synchronization is enabled for Vertex Pipelines.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1MetadataStoreDataplexConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchMigratableResourcesRequest": { "id": "GoogleCloudAiplatformV1beta1SearchMigratableResourcesRequest", "type": "object", "properties": { "filter": { "description": "A filter for your search. You can use the following types of filters: * Resource type filters. The following strings filter for a specific type of MigratableResource: * `ml_engine_model_version:*` * `automl_model:*` * `automl_dataset:*` * `data_labeling_dataset:*` * \"Migrated or not\" filters. The following strings filter for resources that either have or have not already been migrated: * `last_migrate_time:*` filters for migrated resources. * `NOT last_migrate_time:*` filters for not yet migrated resources.", "type": "string" }, "pageSize": { "type": "integer", "description": "The standard page size. The default and maximum value is 100.", "format": "int32" }, "pageToken": { "description": "The standard page token.", "type": "string" } }, "description": "Request message for MigrationService.SearchMigratableResources." }, "GoogleCloudAiplatformV1beta1FunctionCallingConfig": { "id": "GoogleCloudAiplatformV1beta1FunctionCallingConfig", "type": "object", "description": "Function calling config.", "properties": { "streamFunctionCallArguments": { "description": "Optional. When set to true, arguments of a single function call will be streamed out in multiple parts/contents/responses. Partial parameter results will be returned in the `FunctionCall.partial_args` field.", "type": "boolean" }, "mode": { "type": "string", "enumDescriptions": [ "Unspecified function calling mode. This value should not be used.", "Default model behavior, model decides to predict either function calls or natural language response.", "Model is constrained to always predicting function calls only. If \"allowed_function_names\" are set, the predicted function calls will be limited to any one of \"allowed_function_names\", else the predicted function calls will be any one of the provided \"function_declarations\".", "Model will not predict any function calls. Model behavior is same as when not passing any function declarations.", "Model is constrained to predict either function calls or natural language response. If \"allowed_function_names\" are set, the predicted function calls will be limited to any one of \"allowed_function_names\", else the predicted function calls will be any one of the provided \"function_declarations\"." ], "description": "Optional. Function calling mode.", "enum": [ "MODE_UNSPECIFIED", "AUTO", "ANY", "NONE", "VALIDATED" ] }, "allowedFunctionNames": { "description": "Optional. Function names to call. Only set when the Mode is ANY. Function names should match FunctionDeclaration.name. With mode set to ANY, model will predict a function call from the set of function names provided.", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1FindNeighborsResponse": { "id": "GoogleCloudAiplatformV1beta1FindNeighborsResponse", "type": "object", "description": "The response message for MatchService.FindNeighbors.", "properties": { "nearestNeighbors": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsResponseNearestNeighbors" }, "description": "The nearest neighbors of the query datapoints." } } }, "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfig": { "description": "Defines the configuration for a candidate model or agent being evaluated. `InferenceConfig` encapsulates all the necessary information to invoke or scrape the candidate during the evaluation run. This includes direct model inference parameters, agent execution settings, and multi-turn scraping configurations (such as user simulators). It serves as the primary representation of the candidate across different stages of the evaluation process.", "properties": { "agentRunConfig": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigAgentRunConfig", "description": "Optional. Agent run config." }, "parallelism": { "format": "int32", "description": "Optional. The parallelism of the evaluation run for the inference step. If not specified, the default parallelism will be used.", "type": "integer" }, "agents": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1AgentConfig" }, "description": "Optional. Contains the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent." }, "generationConfig": { "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig", "description": "Optional. Generation config." }, "agentConfig": { "description": "Optional. Deprecated: Use `agents` instead. Agent config used to generate responses.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigInferenceAgentConfig" }, "model": { "description": "Optional. The fully qualified name of the publisher model or endpoint to use. Anthropic and Llama third-party models are also supported through Model Garden. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Third-party model formats: `projects/{project}/locations/{location}/publishers/anthropic/models/{model}` or `projects/{project}/locations/{location}/publishers/llama/models/{model}` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ExplanationMetadataOutputMetadata": { "id": "GoogleCloudAiplatformV1beta1ExplanationMetadataOutputMetadata", "type": "object", "description": "Metadata of the prediction output to be explained.", "properties": { "displayNameMappingKey": { "description": "Specify a field name in the prediction to look for the display name. Use this if the prediction contains the display names for the outputs. The display names in the prediction must have the same shape of the outputs, so that it can be located by Attribution.output_index for a specific output.", "type": "string" }, "outputTensorName": { "description": "Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.", "type": "string" }, "indexDisplayNameMapping": { "description": "Static mapping between the index and display name. Use this if the outputs are a deterministic n-dimensional array, e.g. a list of scores of all the classes in a pre-defined order for a multi-classification Model. It's not feasible if the outputs are non-deterministic, e.g. the Model produces top-k classes or sort the outputs by their values. The shape of the value must be an n-dimensional array of strings. The number of dimensions must match that of the outputs to be explained. The Attribution.output_display_name is populated by locating in the mapping with Attribution.output_index.", "type": "any" } } }, "GoogleCloudAiplatformV1beta1RemoveExamplesRequest": { "description": "Request message for ExampleStoreService.RemoveExamples.", "properties": { "storedContentsExampleFilter": { "$ref": "GoogleCloudAiplatformV1beta1StoredContentsExampleFilter", "description": "The metadata filters for StoredContentsExamples." }, "exampleIds": { "type": "array", "items": { "type": "string" }, "description": "Optional. Example IDs to remove. If both metadata filters and Example IDs are specified, the metadata filters will be applied to the specified examples in order to identify which should be removed." } }, "id": "GoogleCloudAiplatformV1beta1RemoveExamplesRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageObjectDetectionEvaluationMetrics": { "properties": { "evaluatedBoundingBoxCount": { "type": "integer", "description": "The total number of bounding boxes (i.e. summed over all images) the ground truth used to create this evaluation had.", "format": "int32" }, "boundingBoxMetrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetrics" }, "description": "The bounding boxes match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair." }, "boundingBoxMeanAveragePrecision": { "description": "The single metric for bounding boxes evaluation: the `meanAveragePrecision` averaged over all `boundingBoxMetricsEntries`.", "format": "float", "type": "number" } }, "description": "Metrics for image object detection evaluation results.", "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageObjectDetectionEvaluationMetrics", "type": "object" }, "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingResult": { "description": "Result for RubricBasedInstructionFollowing metric.", "properties": { "rubricCritiqueResults": { "description": "Output only. List of per rubric critique results.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RubricCritiqueResult" }, "readOnly": true }, "score": { "type": "number", "readOnly": true, "description": "Output only. Overall score for the instruction following.", "format": "float" } }, "id": "GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingResult", "type": "object" }, "GoogleCloudAiplatformV1beta1StopTrialRequest": { "id": "GoogleCloudAiplatformV1beta1StopTrialRequest", "type": "object", "properties": {}, "description": "Request message for VizierService.StopTrial." }, "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpec": { "properties": { "parentIntValues": { "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecIntValueCondition", "description": "The spec for matching values from a parent parameter of `INTEGER` type." }, "parentCategoricalValues": { "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition", "description": "The spec for matching values from a parent parameter of `CATEGORICAL` type." }, "parentDiscreteValues": { "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition", "description": "The spec for matching values from a parent parameter of `DISCRETE` type." }, "parameterSpec": { "description": "Required. The spec for a conditional parameter.", "$ref": "GoogleCloudAiplatformV1beta1StudySpecParameterSpec" } }, "description": "Represents a parameter spec with condition from its parent parameter.", "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1TensorboardTimeSeriesMetadata": { "id": "GoogleCloudAiplatformV1beta1TensorboardTimeSeriesMetadata", "type": "object", "description": "Describes metadata for a TensorboardTimeSeries.", "properties": { "maxStep": { "type": "string", "readOnly": true, "description": "Output only. Max step index of all data points within a TensorboardTimeSeries.", "format": "int64" }, "maxBlobSequenceLength": { "description": "Output only. The largest blob sequence length (number of blobs) of all data points in this time series, if its ValueType is BLOB_SEQUENCE.", "format": "int64", "type": "string", "readOnly": true }, "maxWallTime": { "description": "Output only. Max wall clock timestamp of all data points within a TensorboardTimeSeries.", "format": "google-datetime", "type": "string", "readOnly": true } } }, "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectContentsSourceEvent": { "id": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectContentsSourceEvent", "type": "object", "description": "A single piece of conversation from which to generate memories.", "properties": { "content": { "$ref": "GoogleCloudAiplatformV1beta1Content", "description": "Required. A single piece of content from which to generate memories." } } }, "GoogleCloudAiplatformV1beta1TaskMetadataChange": { "id": "GoogleCloudAiplatformV1beta1TaskMetadataChange", "type": "object", "properties": { "newMetadata": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Required. The complete state of the metadata object *after* the change." }, "updateMask": { "type": "string", "description": "Optional. A field mask indicating which paths in the Struct were changed. If not set, all fields will be updated. go/aip-internal/cloud-standard/2412", "format": "google-fieldmask" } }, "description": "An event representing a change to the task's top-level metadata. example: metadata_change: { new_metadata: { \"name\": \"My task\", } update_mask: { paths: \"name\" } }" }, "GoogleCloudAiplatformV1beta1RubricContent": { "id": "GoogleCloudAiplatformV1beta1RubricContent", "type": "object", "description": "Content of the rubric, defining the testable criteria.", "properties": { "property": { "$ref": "GoogleCloudAiplatformV1beta1RubricContentProperty", "description": "Evaluation criteria based on a specific property." } } }, "GoogleCloudAiplatformV1beta1VideoMetadata": { "id": "GoogleCloudAiplatformV1beta1VideoMetadata", "type": "object", "description": "Provides metadata for a video, including the start and end offsets for clipping and the frame rate.", "properties": { "endOffset": { "type": "string", "format": "google-duration", "description": "Optional. The end offset of the video." }, "fps": { "description": "Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].", "format": "double", "type": "number" }, "startOffset": { "format": "google-duration", "description": "Optional. The start offset of the video.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInstance": { "properties": { "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" }, "context": { "description": "Optional. Text provided as context to answer the question.", "type": "string" }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "instruction": { "description": "Required. The question asked and other instruction in the inference prompt.", "type": "string" } }, "description": "Spec for question answering relevance instance.", "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1TFRecordDestination": { "id": "GoogleCloudAiplatformV1beta1TFRecordDestination", "type": "object", "description": "The storage details for TFRecord output content.", "properties": { "gcsDestination": { "$ref": "GoogleCloudAiplatformV1beta1GcsDestination", "description": "Required. Google Cloud Storage location." } } }, "GoogleCloudAiplatformV1beta1Port": { "id": "GoogleCloudAiplatformV1beta1Port", "type": "object", "description": "Represents a network port in a container.", "properties": { "containerPort": { "format": "int32", "description": "The number of the port to expose on the pod's IP address. Must be a valid port number, between 1 and 65535 inclusive.", "type": "integer" } } }, "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInput": { "id": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInput", "type": "object", "properties": { "metricSpec": { "description": "Required. Spec for summarization helpfulness score metric.", "$ref": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessSpec" }, "instance": { "$ref": "GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInstance", "description": "Required. Summarization helpfulness instance." } }, "description": "Input for summarization helpfulness metric." }, "GoogleCloudAiplatformV1beta1ListNotebookRuntimeTemplatesResponse": { "description": "Response message for NotebookService.ListNotebookRuntimeTemplates.", "properties": { "notebookRuntimeTemplates": { "description": "List of NotebookRuntimeTemplates in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate" } }, "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListNotebookRuntimeTemplatesRequest.page_token to obtain that page.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListNotebookRuntimeTemplatesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognition": { "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs" } }, "description": "A TrainingJob that trains and uploads an AutoML Video Action Recognition Model.", "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognition", "type": "object" }, "GoogleCloudAiplatformV1beta1ReadTensorboardTimeSeriesDataResponse": { "properties": { "timeSeriesData": { "$ref": "GoogleCloudAiplatformV1beta1TimeSeriesData", "description": "The returned time series data." } }, "description": "Response message for TensorboardService.ReadTensorboardTimeSeriesData.", "id": "GoogleCloudAiplatformV1beta1ReadTensorboardTimeSeriesDataResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1StoredContentsExampleParameters": { "id": "GoogleCloudAiplatformV1beta1StoredContentsExampleParameters", "type": "object", "properties": { "searchKey": { "description": "The exact search key to use for retrieval.", "type": "string" }, "contentSearchKey": { "$ref": "GoogleCloudAiplatformV1beta1StoredContentsExampleParametersContentSearchKey", "description": "The chat history to use to generate the search key for retrieval." }, "functionNames": { "description": "Optional. The function names for filtering.", "$ref": "GoogleCloudAiplatformV1beta1ExamplesArrayFilter" } }, "description": "The metadata filters that will be used to search StoredContentsExamples. If a field is unspecified, then no filtering for that field will be applied" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs", "type": "object", "properties": { "modelType": { "enum": [ "MODEL_TYPE_UNSPECIFIED", "CLOUD", "MOBILE_VERSATILE_1", "MOBILE_JETSON_VERSATILE_1" ], "type": "string", "enumDescriptions": [ "Should not be set.", "A model best tailored to be used within Google Cloud, and which cannot be exported. Default.", "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards.", "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) to a Jetson device afterwards." ] } } }, "GoogleCloudAiplatformV1beta1FulfillmentResult": { "properties": { "explanation": { "type": "string", "readOnly": true, "description": "Output only. Explanation for fulfillment score." }, "score": { "format": "float", "description": "Output only. Fulfillment score.", "readOnly": true, "type": "number" }, "confidence": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Confidence for fulfillment score." } }, "description": "Spec for fulfillment result.", "id": "GoogleCloudAiplatformV1beta1FulfillmentResult", "type": "object" }, "GoogleCloudAiplatformV1beta1DiskSpec": { "properties": { "bootDiskType": { "description": "Type of the boot disk. For non-A3U machines, the default value is \"pd-ssd\", for A3U machines, the default value is \"hyperdisk-balanced\". Valid values: \"pd-ssd\" (Persistent Disk Solid State Drive), \"pd-standard\" (Persistent Disk Hard Disk Drive) or \"hyperdisk-balanced\".", "type": "string" }, "bootDiskSizeGb": { "type": "integer", "format": "int32", "description": "Size in GB of the boot disk (default is 100GB)." } }, "description": "Represents the spec of disk options.", "id": "GoogleCloudAiplatformV1beta1DiskSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitor": { "description": "Vertex AI Model Monitoring Service serves as a central hub for the analysis and visualization of data quality and performance related to models. ModelMonitor stands as a top level resource for overseeing your model monitoring tasks.", "properties": { "satisfiesPzi": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" }, "satisfiesPzs": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "tabularObjective": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective", "description": "Optional default tabular model monitoring objective." }, "trainingDataset": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInput", "description": "Optional training dataset used to train the model. It can serve as a reference dataset to identify changes in production." }, "modelMonitoringSchema": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringSchema", "description": "Monitoring Schema is to specify the model's features, prediction outputs and ground truth properties. It is used to extract pertinent data from the dataset and to process features based on their properties. Make sure that the schema aligns with your dataset, if it does not, we will be unable to extract data from the dataset. It is required for most models, but optional for Vertex AI AutoML Tables unless the schem information is not available." }, "name": { "description": "Immutable. Resource name of the ModelMonitor. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`.", "type": "string" }, "outputSpec": { "description": "Optional default monitoring metrics/logs export spec, it can be overridden in the ModelMonitoringJob output spec. If not specified, a default Google Cloud Storage bucket will be created under your project.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringOutputSpec" }, "explanationSpec": { "description": "Optional model explanation spec. It is used for feature attribution monitoring.", "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec" }, "displayName": { "description": "The display name of the ModelMonitor. The name can be up to 128 characters long and can consist of any UTF-8.", "type": "string" }, "notificationSpec": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpec", "description": "Optional default notification spec, it can be overridden in the ModelMonitoringJob notification spec." }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this ModelMonitor was created." }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this ModelMonitor was updated most recently.", "format": "google-datetime" }, "modelMonitoringTarget": { "description": "The entity that is subject to analysis. Currently only models in Vertex AI Model Registry are supported. If you want to analyze the model which is outside the Vertex AI, you could register a model in Vertex AI Model Registry using just a display name.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTarget" }, "encryptionSpec": { "description": "Customer-managed encryption key spec for a ModelMonitor. If set, this ModelMonitor and all sub-resources of this ModelMonitor will be secured by this key.", "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" } }, "id": "GoogleCloudAiplatformV1beta1ModelMonitor", "type": "object" }, "GoogleCloudAiplatformV1beta1ExactMatchResults": { "id": "GoogleCloudAiplatformV1beta1ExactMatchResults", "type": "object", "properties": { "exactMatchMetricValues": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ExactMatchMetricValue" }, "description": "Output only. Exact match metric values." } }, "description": "Results for exact match metric." }, "GoogleCloudAiplatformV1beta1Value": { "id": "GoogleCloudAiplatformV1beta1Value", "type": "object", "properties": { "intValue": { "format": "int64", "description": "An integer value.", "type": "string" }, "stringValue": { "description": "A string value.", "type": "string" }, "doubleValue": { "type": "number", "format": "double", "description": "A double value." } }, "description": "Value is the value of the field." }, "GoogleCloudAiplatformV1beta1FluencyInput": { "id": "GoogleCloudAiplatformV1beta1FluencyInput", "type": "object", "properties": { "instance": { "description": "Required. Fluency instance.", "$ref": "GoogleCloudAiplatformV1beta1FluencyInstance" }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1FluencySpec", "description": "Required. Spec for fluency score metric." } }, "description": "Input for fluency metric." }, "GoogleCloudAiplatformV1beta1AuthConfig": { "properties": { "oidcConfig": { "description": "Config for user OIDC auth.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfigOidcConfig" }, "httpBasicAuthConfig": { "description": "Config for HTTP Basic auth.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig" }, "oauthConfig": { "$ref": "GoogleCloudAiplatformV1beta1AuthConfigOauthConfig", "description": "Config for user oauth." }, "apiKeyConfig": { "$ref": "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig", "description": "Config for API key auth." }, "googleServiceAccountConfig": { "$ref": "GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig", "description": "Config for Google Service Account auth." }, "authType": { "type": "string", "enumDescriptions": [ "", "No Auth.", "API Key Auth.", "HTTP Basic Auth.", "Google Service Account Auth.", "OAuth auth.", "OpenID Connect (OIDC) Auth." ], "enum": [ "AUTH_TYPE_UNSPECIFIED", "NO_AUTH", "API_KEY_AUTH", "HTTP_BASIC_AUTH", "GOOGLE_SERVICE_ACCOUNT_AUTH", "OAUTH", "OIDC_AUTH" ], "description": "Type of auth scheme." } }, "description": "Auth configuration to run the extension.", "id": "GoogleCloudAiplatformV1beta1AuthConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecDeveloperConnectConfig": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecDeveloperConnectConfig", "type": "object", "properties": { "gitRepositoryLink": { "description": "Required. The Developer Connect Git repository link, formatted as `projects/*/locations/*/connections/*/gitRepositoryLink/*`.", "type": "string" }, "revision": { "description": "Required. The revision to fetch from the Git repository such as a branch, a tag, a commit SHA, or any Git ref.", "type": "string" }, "dir": { "description": "Required. Directory, relative to the source root, in which to run the build.", "type": "string" } }, "description": "Specifies the configuration for fetching source code from a Git repository that is managed by Developer Connect. This includes the repository, revision, and directory to use." }, "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDiscreteValueSpec": { "id": "GoogleCloudAiplatformV1beta1StudySpecParameterSpecDiscreteValueSpec", "type": "object", "properties": { "defaultValue": { "type": "number", "format": "double", "description": "A default value for a `DISCRETE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. It automatically rounds to the nearest feasible discrete point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline." }, "values": { "type": "array", "items": { "format": "double", "type": "number" }, "description": "Required. A list of possible values. The list should be in increasing order and at least 1e-10 apart. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values." } }, "description": "Value specification for a parameter in `DISCRETE` type." }, "GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfigDocumentCorpus": { "id": "GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfigDocumentCorpus", "type": "object", "properties": {}, "description": "Config for the document corpus." }, "GoogleCloudAiplatformV1beta1NotebookSoftwareConfig": { "id": "GoogleCloudAiplatformV1beta1NotebookSoftwareConfig", "type": "object", "properties": { "colabImage": { "description": "Optional. Google-managed NotebookRuntime colab image.", "$ref": "GoogleCloudAiplatformV1beta1ColabImage" }, "env": { "description": "Optional. Environment variables to be passed to the container. Maximum limit is 100.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EnvVar" } }, "postStartupScriptConfig": { "description": "Optional. Post startup script config.", "$ref": "GoogleCloudAiplatformV1beta1PostStartupScriptConfig" } }, "description": "Notebook Software Config. This is passed to the backend when user makes software configurations in UI." }, "GoogleCloudAiplatformV1beta1StartNotebookRuntimeRequest": { "description": "Request message for NotebookService.StartNotebookRuntime.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1StartNotebookRuntimeRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseResults": { "properties": { "trajectorySingleToolUseMetricValues": { "description": "Output only. TrajectorySingleToolUse metric values.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseMetricValue" } } }, "description": "Results for TrajectorySingleToolUse metric.", "id": "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseResults", "type": "object" }, "GoogleCloudAiplatformV1beta1Presets": { "id": "GoogleCloudAiplatformV1beta1Presets", "type": "object", "description": "Preset configuration for example-based explanations", "properties": { "modality": { "description": "The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type.", "enum": [ "MODALITY_UNSPECIFIED", "IMAGE", "TEXT", "TABULAR" ], "type": "string", "enumDescriptions": [ "Should not be set. Added as a recommended best practice for enums", "IMAGE modality", "TEXT modality", "TABULAR modality" ] }, "query": { "type": "string", "enumDescriptions": [ "More precise neighbors as a trade-off against slower response.", "Faster response as a trade-off against less precise neighbors." ], "enum": [ "PRECISE", "FAST" ], "description": "Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`." } } }, "GoogleCloudLocationLocation": { "properties": { "labels": { "description": "Cross-service attributes for the location. For example {\"cloud.googleapis.com/region\": \"us-east1\"}", "type": "object", "additionalProperties": { "type": "string" } }, "metadata": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." }, "description": "Service-specific metadata. For example the available capacity at the given location." }, "name": { "description": "Resource name for the location, which may vary between implementations. For example: `\"projects/example-project/locations/us-east1\"`", "type": "string" }, "locationId": { "description": "The canonical id for this location. For example: `\"us-east1\"`.", "type": "string" }, "displayName": { "description": "The friendly name for this location, typically a nearby city name. For example, \"Tokyo\".", "type": "string" } }, "description": "A resource that represents a Google Cloud location.", "id": "GoogleCloudLocationLocation", "type": "object" }, "GoogleCloudAiplatformV1beta1NasTrial": { "id": "GoogleCloudAiplatformV1beta1NasTrial", "type": "object", "properties": { "id": { "description": "Output only. The identifier of the NasTrial assigned by the service.", "type": "string", "readOnly": true }, "finalMeasurement": { "description": "Output only. The final measurement containing the objective value.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1Measurement" }, "startTime": { "format": "google-datetime", "description": "Output only. Time when the NasTrial was started.", "readOnly": true, "type": "string" }, "state": { "description": "Output only. The detailed state of the NasTrial.", "enum": [ "STATE_UNSPECIFIED", "REQUESTED", "ACTIVE", "STOPPING", "SUCCEEDED", "INFEASIBLE" ], "type": "string", "enumDescriptions": [ "The NasTrial state is unspecified.", "Indicates that a specific NasTrial has been requested, but it has not yet been suggested by the service.", "Indicates that the NasTrial has been suggested.", "Indicates that the NasTrial should stop according to the service.", "Indicates that the NasTrial is completed successfully.", "Indicates that the NasTrial should not be attempted again. The service will set a NasTrial to INFEASIBLE when it's done but missing the final_measurement." ], "readOnly": true }, "endTime": { "description": "Output only. Time when the NasTrial's status changed to `SUCCEEDED` or `INFEASIBLE`.", "format": "google-datetime", "type": "string", "readOnly": true } }, "description": "Represents a uCAIP NasJob trial." }, "GoogleCloudAiplatformV1beta1ExactMatchMetricValue": { "id": "GoogleCloudAiplatformV1beta1ExactMatchMetricValue", "type": "object", "description": "Exact match metric value for an instance.", "properties": { "score": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. Exact match score." } } }, "GoogleCloudAiplatformV1beta1RemoveDatapointsResponse": { "id": "GoogleCloudAiplatformV1beta1RemoveDatapointsResponse", "type": "object", "properties": {}, "description": "Response message for IndexService.RemoveDatapoints" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsGeneralTextGenerationEvaluationMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsGeneralTextGenerationEvaluationMetrics", "type": "object", "properties": { "rougeLSum": { "type": "number", "format": "float", "description": "ROUGE-L (Longest Common Subsequence) scoring at summary level." }, "bleu": { "type": "number", "description": "BLEU (bilingual evaluation understudy) scores based on sacrebleu implementation.", "format": "float" } } }, "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigOutputConfig": { "description": "The output config for the evaluation run.", "properties": { "gcsDestination": { "description": "Cloud Storage destination for evaluation output.", "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" }, "bigqueryDestination": { "description": "BigQuery destination for evaluation output.", "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination" } }, "id": "GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigOutputConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeRequest": { "description": "Request message for NotebookService.UpgradeNotebookRuntime.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsSummarizationEvaluationMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsSummarizationEvaluationMetrics", "type": "object", "properties": { "rougeLSum": { "format": "float", "description": "ROUGE-L (Longest Common Subsequence) scoring at summary level.", "type": "number" } } }, "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsRequest": { "id": "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsRequest", "type": "object", "properties": { "statsName": { "description": "If non-empty, returns the alerts of this stats_name.", "type": "string" }, "objectiveType": { "description": "If non-empty, returns the alerts of this objective type. Supported monitoring objectives: `raw-feature-drift` `prediction-output-drift` `feature-attribution`", "type": "string" }, "pageToken": { "description": "A page token received from a previous ModelMonitoringService.SearchModelMonitoringAlerts call.", "type": "string" }, "modelMonitoringJob": { "description": "If non-empty, returns the alerts of this model monitoring job.", "type": "string" }, "alertTimeInterval": { "$ref": "GoogleTypeInterval", "description": "If non-empty, returns the alerts in this time interval." }, "pageSize": { "type": "integer", "description": "The standard list page size.", "format": "int32" } }, "description": "Request message for ModelMonitoringService.SearchModelMonitoringAlerts." }, "GoogleCloudAiplatformV1beta1ExportPublisherModelResponse": { "properties": { "destinationUri": { "description": "The destination uri of the model weights.", "type": "string" }, "publisherModel": { "description": "The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}@{version_id}`", "type": "string" } }, "description": "Response message for ModelGardenService.ExportPublisherModel.", "id": "GoogleCloudAiplatformV1beta1ExportPublisherModelResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ListTensorboardTimeSeriesResponse": { "properties": { "tensorboardTimeSeries": { "description": "The TensorboardTimeSeries mathching the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" } }, "nextPageToken": { "description": "A token, which can be sent as ListTensorboardTimeSeriesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "description": "Response message for TensorboardService.ListTensorboardTimeSeries.", "id": "GoogleCloudAiplatformV1beta1ListTensorboardTimeSeriesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1XraiAttribution": { "id": "GoogleCloudAiplatformV1beta1XraiAttribution", "type": "object", "description": "An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Supported only by image Models.", "properties": { "blurBaselineConfig": { "description": "Config for XRAI with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383", "$ref": "GoogleCloudAiplatformV1beta1BlurBaselineConfig" }, "smoothGradConfig": { "description": "Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf", "$ref": "GoogleCloudAiplatformV1beta1SmoothGradConfig" }, "stepCount": { "type": "integer", "description": "Required. The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range. Valid range of its value is [1, 100], inclusively.", "format": "int32" } } }, "GoogleCloudAiplatformV1beta1SecretEnvVar": { "id": "GoogleCloudAiplatformV1beta1SecretEnvVar", "type": "object", "description": "Represents an environment variable where the value is a secret in Cloud Secret Manager.", "properties": { "name": { "description": "Required. Name of the secret environment variable.", "type": "string" }, "secretRef": { "description": "Required. Reference to a secret stored in the Cloud Secret Manager that will provide the value for this environment variable.", "$ref": "GoogleCloudAiplatformV1beta1SecretRef" } } }, "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataContentValidationStats": { "id": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataContentValidationStats", "type": "object", "properties": { "validRecordCount": { "format": "int64", "description": "Number of records in this file that were successfully processed.", "type": "string" }, "partialErrors": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataRecordError" }, "description": "The detail information of the partial failures encountered for those invalid records that couldn't be parsed. Up to 50 partial errors will be reported." }, "invalidRecordCount": { "type": "string", "description": "Number of records in this file we skipped due to validate errors.", "format": "int64" }, "sourceGcsUri": { "description": "Cloud Storage URI pointing to the original file in user's bucket.", "type": "string" }, "validSparseRecordCount": { "format": "int64", "description": "Number of sparse records in this file that were successfully processed.", "type": "string" }, "invalidSparseRecordCount": { "type": "string", "format": "int64", "description": "Number of sparse records in this file we skipped due to validate errors." } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecNotificationChannelConfig": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecNotificationChannelConfig", "type": "object", "properties": { "notificationChannel": { "description": "Resource names of the NotificationChannels. Must be of the format `projects//notificationChannels/`", "type": "string" } }, "description": "Google Cloud Notification Channel config." }, "GoogleCloudAiplatformV1beta1ListTrainingPipelinesResponse": { "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListTrainingPipelinesRequest.page_token to obtain that page.", "type": "string" }, "trainingPipelines": { "description": "List of TrainingPipelines in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrainingPipeline" } } }, "description": "Response message for PipelineService.ListTrainingPipelines", "id": "GoogleCloudAiplatformV1beta1ListTrainingPipelinesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1TensorboardExperiment": { "id": "GoogleCloudAiplatformV1beta1TensorboardExperiment", "type": "object", "description": "A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard.", "properties": { "displayName": { "description": "User provided name of this TensorboardExperiment.", "type": "string" }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "description": { "description": "Description of this TensorboardExperiment.", "type": "string" }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this TensorboardExperiment was created.", "format": "google-datetime" }, "source": { "description": "Immutable. Source of the TensorboardExperiment. Example: a custom training job.", "type": "string" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize your TensorboardExperiment. Label keys and values cannot be longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with `aiplatform.googleapis.com/` and are immutable. The following system labels exist for each Dataset: * `aiplatform.googleapis.com/dataset_metadata_schema`: output only. Its value is the metadata_schema's title." }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this TensorboardExperiment was last updated.", "readOnly": true, "type": "string" }, "name": { "type": "string", "readOnly": true, "description": "Output only. Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`" } } }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics": { "properties": { "recallAt1": { "type": "number", "format": "float", "description": "The Recall (True Positive Rate) when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem." }, "confusionMatrix": { "description": "Confusion matrix of the evaluation for this confidence_threshold.", "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix" }, "confidenceThreshold": { "type": "number", "format": "float", "description": "Metrics are computed with an assumption that the Model never returns predictions with score lower than this value." }, "f1ScoreAt1": { "description": "The harmonic mean of recallAt1 and precisionAt1.", "format": "float", "type": "number" }, "precision": { "description": "Precision for the given confidence threshold.", "format": "float", "type": "number" }, "precisionAt1": { "description": "The precision when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem.", "format": "float", "type": "number" }, "truePositiveCount": { "description": "The number of Model created labels that match a ground truth label.", "format": "int64", "type": "string" }, "recall": { "type": "number", "description": "Recall (True Positive Rate) for the given confidence threshold.", "format": "float" }, "falsePositiveRate": { "description": "False Positive Rate for the given confidence threshold.", "format": "float", "type": "number" }, "trueNegativeCount": { "description": "The number of labels that were not created by the Model, but if they would, they would not match a ground truth label.", "format": "int64", "type": "string" }, "f1ScoreMicro": { "type": "number", "description": "Micro-averaged F1 Score.", "format": "float" }, "f1Score": { "format": "float", "description": "The harmonic mean of recall and precision. For summary metrics, it computes the micro-averaged F1 score.", "type": "number" }, "f1ScoreMacro": { "type": "number", "description": "Macro-averaged F1 Score.", "format": "float" }, "falsePositiveRateAt1": { "type": "number", "format": "float", "description": "The False Positive Rate when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem." }, "falseNegativeCount": { "type": "string", "description": "The number of ground truth labels that are not matched by a Model created label.", "format": "int64" }, "maxPredictions": { "type": "integer", "description": "Metrics are computed with an assumption that the Model always returns at most this many predictions (ordered by their score, descendingly), but they all still need to meet the `confidenceThreshold`.", "format": "int32" }, "falsePositiveCount": { "format": "int64", "description": "The number of Model created labels that do not match a ground truth label.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics", "type": "object" }, "GoogleLongrunningListOperationsResponse": { "id": "GoogleLongrunningListOperationsResponse", "type": "object", "properties": { "operations": { "description": "A list of operations that matches the specified filter in the request.", "type": "array", "items": { "$ref": "GoogleLongrunningOperation" } }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" }, "unreachable": { "description": "Unordered list. Unreachable resources. Populated when the request sets `ListOperationsRequest.return_partial_success` and reads across collections. For example, when attempting to list all resources across all supported locations.", "type": "array", "items": { "type": "string" } } }, "description": "The response message for Operations.ListOperations." }, "GoogleCloudAiplatformV1beta1NotebookRuntime": { "id": "GoogleCloudAiplatformV1beta1NotebookRuntime", "type": "object", "description": "A runtime is a virtual machine allocated to a particular user for a particular Notebook file on temporary basis with lifetime. Default runtimes have a lifetime of 18 hours, while custom runtimes last for 6 months from their creation or last upgrade.", "properties": { "reservationAffinity": { "description": "Output only. Reservation Affinity of the notebook runtime.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1NotebookReservationAffinity" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" }, "softwareConfig": { "description": "Output only. Software config of the notebook runtime.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1NotebookSoftwareConfig" }, "runtimeUser": { "description": "Required. The user email of the NotebookRuntime.", "type": "string" }, "expirationTime": { "description": "Output only. Timestamp when this NotebookRuntime will be expired: 1. System Predefined NotebookRuntime: 24 hours after creation. After expiration, system predifined runtime will be deleted. 2. User created NotebookRuntime: 6 months after last upgrade. After expiration, user created runtime will be stopped and allowed for upgrade.", "format": "google-datetime", "type": "string", "readOnly": true }, "idleShutdownConfig": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1NotebookIdleShutdownConfig", "description": "Output only. The idle shutdown configuration of the notebook runtime." }, "dataPersistentDiskSpec": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1PersistentDiskSpec", "description": "Output only. The specification of persistent disk attached to the notebook runtime as data disk storage." }, "machineSpec": { "description": "Output only. The specification of a single machine used by the notebook runtime.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1MachineSpec" }, "runtimeState": { "enum": [ "RUNTIME_STATE_UNSPECIFIED", "RUNNING", "BEING_STARTED", "BEING_STOPPED", "STOPPED", "BEING_UPGRADED", "ERROR", "INVALID" ], "description": "Output only. The runtime (instance) state of the NotebookRuntime.", "readOnly": true, "type": "string", "enumDescriptions": [ "Unspecified runtime state.", "NotebookRuntime is in running state.", "NotebookRuntime is in starting state. This is when the runtime is being started from a stopped state.", "NotebookRuntime is in stopping state.", "NotebookRuntime is in stopped state.", "NotebookRuntime is in upgrading state. It is in the middle of upgrading process.", "NotebookRuntime was unable to start/stop properly.", "NotebookRuntime is in invalid state. Cannot be recovered." ] }, "notebookRuntimeType": { "readOnly": true, "type": "string", "enumDescriptions": [ "Unspecified notebook runtime type, NotebookRuntimeType will default to USER_DEFINED.", "runtime or template with coustomized configurations from user.", "runtime or template with system defined configurations." ], "enum": [ "NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED", "USER_DEFINED", "ONE_CLICK" ], "description": "Output only. The type of the notebook runtime." }, "proxyUri": { "readOnly": true, "type": "string", "description": "Output only. The proxy endpoint used to access the NotebookRuntime." }, "healthState": { "type": "string", "enumDescriptions": [ "Unspecified health state.", "NotebookRuntime is in healthy state. Applies to ACTIVE state.", "NotebookRuntime is in unhealthy state. Applies to ACTIVE state." ], "readOnly": true, "description": "Output only. The health state of the NotebookRuntime.", "enum": [ "HEALTH_STATE_UNSPECIFIED", "HEALTHY", "UNHEALTHY" ] }, "displayName": { "description": "Required. The display name of the NotebookRuntime. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "networkSpec": { "description": "Output only. Network spec of the notebook runtime.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1NetworkSpec" }, "isUpgradable": { "description": "Output only. Whether NotebookRuntime is upgradable.", "type": "boolean", "readOnly": true }, "shieldedVmConfig": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ShieldedVmConfig", "description": "Output only. Runtime Shielded VM spec." }, "serviceAccount": { "description": "Output only. Deprecated: This field is no longer used and the \"Vertex AI Notebook Service Account\" (service-PROJECT_NUMBER@gcp-sa-aiplatform-vm.iam.gserviceaccount.com) is used for the runtime workload identity. See https://cloud.google.com/iam/docs/service-agents#vertex-ai-notebook-service-account for more details. The service account that the NotebookRuntime workload runs as.", "readOnly": true, "type": "string" }, "notebookRuntimeTemplateRef": { "description": "Output only. The pointer to NotebookRuntimeTemplate this NotebookRuntime is created from.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplateRef" }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "name": { "description": "Output only. The resource name of the NotebookRuntime.", "readOnly": true, "type": "string" }, "encryptionSpec": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Output only. Customer-managed encryption key spec for the notebook runtime." }, "eucConfig": { "description": "Output only. EUC configuration of the notebook runtime.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1NotebookEucConfig" }, "version": { "readOnly": true, "type": "string", "description": "Output only. The VM os image version of NotebookRuntime." }, "networkTags": { "type": "array", "items": { "type": "string" }, "description": "Optional. The Compute Engine tags to add to runtime (see [Tagging instances](https://cloud.google.com/vpc/docs/add-remove-network-tags))." }, "description": { "description": "The description of the NotebookRuntime.", "type": "string" }, "createTime": { "description": "Output only. Timestamp when this NotebookRuntime was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "labels": { "description": "The labels with user-defined metadata to organize your NotebookRuntime. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one NotebookRuntime (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for NotebookRuntime: * \"aiplatform.googleapis.com/notebook_runtime_gce_instance_id\": output only, its value is the Compute Engine instance id. * \"aiplatform.googleapis.com/colab_enterprise_entry_service\": its value is either \"bigquery\" or \"vertex\"; if absent, it should be \"vertex\". This is to describe the entry service, either BigQuery or Vertex.", "type": "object", "additionalProperties": { "type": "string" } }, "updateTime": { "description": "Output only. Timestamp when this NotebookRuntime was most recently updated.", "format": "google-datetime", "type": "string", "readOnly": true } } }, "GoogleCloudAiplatformV1beta1EvaluationPromptUserScenario": { "id": "GoogleCloudAiplatformV1beta1EvaluationPromptUserScenario", "type": "object", "description": "User scenario to help simulate multi-turn agent running results.", "properties": { "conversationPlan": { "description": "Required. The plan for the conversation, used to drive the multi-turn agent run and generate the simulated agent evaluation dataset.", "type": "string" }, "startingPrompt": { "description": "Required. The prompt that starts the conversation between the simulated user and the agent under test.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1NotebookReservationAffinity": { "id": "GoogleCloudAiplatformV1beta1NotebookReservationAffinity", "type": "object", "description": "Notebook Reservation Affinity for consuming Zonal reservation.", "properties": { "consumeReservationType": { "enum": [ "RESERVATION_AFFINITY_TYPE_UNSPECIFIED", "RESERVATION_NONE", "RESERVATION_ANY", "RESERVATION_SPECIFIC" ], "description": "Required. Specifies the type of reservation from which this instance can consume resources: RESERVATION_ANY (default), RESERVATION_SPECIFIC, or RESERVATION_NONE. See Consuming reserved instances for examples.", "type": "string", "enumDescriptions": [ "Default type.", "Do not consume from any allocated capacity.", "Consume any reservation available.", "Must consume from a specific reservation. Must specify key value fields for specifying the reservations." ] }, "key": { "description": "Optional. Corresponds to the label key of a reservation resource. To target a RESERVATION_SPECIFIC by name, use compute.googleapis.com/reservation-name as the key and specify the name of your reservation as its value.", "type": "string" }, "values": { "description": "Optional. Corresponds to the label values of a reservation resource. This must be the full path name of Reservation.", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigBruteForceConfig": { "id": "GoogleCloudAiplatformV1beta1FeatureViewIndexConfigBruteForceConfig", "type": "object", "description": "Configuration options for using brute force search.", "properties": {} }, "GoogleCloudAiplatformV1beta1SchemaImageDatasetMetadata": { "properties": { "dataItemSchemaUri": { "description": "Points to a YAML file stored on Google Cloud Storage describing payload of the Image DataItems that belong to this Dataset.", "type": "string" }, "gcsBucket": { "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset.", "type": "string" } }, "description": "The metadata of Datasets that contain Image DataItems.", "id": "GoogleCloudAiplatformV1beta1SchemaImageDatasetMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1MetricxResult": { "id": "GoogleCloudAiplatformV1beta1MetricxResult", "type": "object", "properties": { "score": { "readOnly": true, "type": "number", "format": "float", "description": "Output only. MetricX score. Range depends on version." } }, "description": "Spec for MetricX result - calculates the MetricX score for the given instance using the version specified in the spec." }, "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfig": { "description": "The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name.", "properties": { "manualMode": { "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigManualRoutingMode", "description": "In this mode, the model is specified manually." }, "autoMode": { "description": "In this mode, the model is selected automatically based on the content of the request.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigAutoRoutingMode" } }, "id": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1ListEndpointsResponse": { "properties": { "endpoints": { "description": "List of Endpoints in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Endpoint" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListEndpointsRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for EndpointService.ListEndpoints.", "id": "GoogleCloudAiplatformV1beta1ListEndpointsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1FetchFeatureValuesRequest": { "properties": { "format": { "deprecated": true, "description": "Specify response data format. If not set, KeyValue format will be used. Deprecated. Use FetchFeatureValuesRequest.data_format.", "enum": [ "FORMAT_UNSPECIFIED", "KEY_VALUE", "PROTO_STRUCT" ], "type": "string", "enumDescriptions": [ "Not set. Will be treated as the KeyValue format.", "Return response data in key-value format.", "Return response data in proto Struct format." ] }, "dataFormat": { "description": "Optional. Response data format. If not set, FeatureViewDataFormat.KEY_VALUE will be used.", "enum": [ "FEATURE_VIEW_DATA_FORMAT_UNSPECIFIED", "KEY_VALUE", "PROTO_STRUCT" ], "type": "string", "enumDescriptions": [ "Not set. Will be treated as the KeyValue format.", "Return response data in key-value format.", "Return response data in proto Struct format." ] }, "dataKey": { "description": "Optional. The request key to fetch feature values for.", "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKey" }, "id": { "type": "string", "deprecated": true, "description": "Simple ID. The whole string will be used as is to identify Entity to fetch feature values for." } }, "description": "Request message for FeatureOnlineStoreService.FetchFeatureValues. All the features under the requested feature view will be returned.", "id": "GoogleCloudAiplatformV1beta1FetchFeatureValuesRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1RougeSpec": { "description": "Spec for rouge score metric - calculates the recall of n-grams in prediction as compared to reference - returns a score ranging between 0 and 1.", "properties": { "splitSummaries": { "description": "Optional. Whether to split summaries while using rougeLsum.", "type": "boolean" }, "useStemmer": { "description": "Optional. Whether to use stemmer to compute rouge score.", "type": "boolean" }, "rougeType": { "description": "Optional. Supported rouge types are rougen[1-9], rougeL, and rougeLsum.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1RougeSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1CancelTrainingPipelineRequest": { "id": "GoogleCloudAiplatformV1beta1CancelTrainingPipelineRequest", "type": "object", "description": "Request message for PipelineService.CancelTrainingPipeline.", "properties": {} }, "GoogleCloudAiplatformV1beta1CorroborateContentRequestParameters": { "properties": { "citationThreshold": { "format": "double", "description": "Optional. Only return claims with citation score larger than the threshold.", "type": "number" } }, "description": "Parameters that can be overrided per request.", "id": "GoogleCloudAiplatformV1beta1CorroborateContentRequestParameters", "type": "object" }, "GoogleCloudAiplatformV1beta1EnvVar": { "properties": { "name": { "description": "Required. Name of the environment variable. Must be a valid C identifier.", "type": "string" }, "value": { "description": "Required. Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.", "type": "string" } }, "description": "Represents an environment variable present in a Container or Python Module.", "id": "GoogleCloudAiplatformV1beta1EnvVar", "type": "object" }, "GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest": { "properties": { "input": { "description": "Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "classMethod": { "description": "Optional. Class method to be used for the query. It is optional and defaults to \"query\" if unspecified.", "type": "string" } }, "description": "Request message for ReasoningEngineExecutionService.Query.", "id": "GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest", "type": "object" }, "CloudAiLargeModelsVisionHumanPose": { "id": "CloudAiLargeModelsVisionHumanPose", "type": "object", "properties": { "bodyLandmarksGcsUri": { "deprecated": true, "type": "string", "description": "GCS URI of the human pose video to condition video generation." }, "perfMeshGcsUri": { "description": "GCS URI of the performance mesh to condition video generation.", "type": "string" }, "faceLandmarksGcsUri": { "type": "string", "deprecated": true, "description": "GCS URI of the face landmarks video to condition video generation." } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig": { "properties": { "maxCount": { "type": "string", "format": "int64", "description": "Maximum number of windows that should be generated across all time series." }, "column": { "description": "Name of the column that should be used to generate sliding windows. The column should contain either booleans or string booleans; if the value of the row is True, generate a sliding window with the horizon starting at that row. The column will not be used as a feature in training.", "type": "string" }, "strideLength": { "type": "string", "description": "Stride length used to generate input examples. Within one time series, every {$STRIDE_LENGTH} rows will be used to generate a sliding window.", "format": "int64" } }, "description": "Config that contains the strategy used to generate sliding windows in time series training. A window is a series of rows that comprise the context up to the time of prediction, and the horizon following. The corresponding row for each window marks the start of the forecast horizon. Each window is used as an input example for training/evaluation.", "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1RetrieveMemoriesRequestSimpleRetrievalParams": { "id": "GoogleCloudAiplatformV1beta1RetrieveMemoriesRequestSimpleRetrievalParams", "type": "object", "description": "Parameters for simple (non-similarity search) retrieval.", "properties": { "pageToken": { "description": "Optional. A page token, received from a previous `RetrieveMemories` call. Provide this to retrieve the subsequent page.", "type": "string" }, "pageSize": { "type": "integer", "description": "Optional. The maximum number of memories to return. The service may return fewer than this value. If unspecified, at most 3 memories will be returned. The maximum value is 100; values above 100 will be coerced to 100.", "format": "int32" } } }, "GoogleCloudAiplatformV1beta1Segment": { "id": "GoogleCloudAiplatformV1beta1Segment", "type": "object", "description": "A segment of the content.", "properties": { "startIndex": { "readOnly": true, "type": "integer", "format": "int32", "description": "Output only. The start index of the segment in the `Part`, measured in bytes. This marks the beginning of the segment and is inclusive, meaning the byte at this index is the first byte of the segment." }, "partIndex": { "type": "integer", "readOnly": true, "description": "Output only. The index of the `Part` object that this segment belongs to. This is useful for associating the segment with a specific part of the content.", "format": "int32" }, "text": { "readOnly": true, "type": "string", "description": "Output only. The text of the segment." }, "endIndex": { "readOnly": true, "type": "integer", "format": "int32", "description": "Output only. The end index of the segment in the `Part`, measured in bytes. This marks the end of the segment and is exclusive, meaning the segment includes content up to, but not including, the byte at this index." } } }, "GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadata", "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The common part of the operation metadata." }, "partialResults": { "description": "Partial results that reflect the latest migration operation progress.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadataPartialResult" } } }, "description": "Runtime operation information for MigrationService.BatchMigrateResources." }, "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataAgentEvent": { "description": "A single event in the execution trace.", "properties": { "eventTime": { "type": "string", "format": "google-datetime", "description": "Optional. The timestamp when the event occurred." }, "activeTools": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" }, "description": "Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set." }, "author": { "description": "Required. The ID of the agent or entity that generated this event.", "type": "string" }, "stateDelta": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event." }, "content": { "$ref": "GoogleCloudAiplatformV1beta1Content", "description": "Required. The content of the event (e.g., text response, tool call, tool response)." } }, "id": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataAgentEvent", "type": "object" }, "GoogleCloudAiplatformV1beta1CopyModelResponse": { "id": "GoogleCloudAiplatformV1beta1CopyModelResponse", "type": "object", "properties": { "model": { "description": "The name of the copied Model resource. Format: `projects/{project}/locations/{location}/models/{model}`", "type": "string" }, "modelVersionId": { "description": "Output only. The version ID of the model that is copied.", "type": "string", "readOnly": true } }, "description": "Response message of ModelService.CopyModel operation." }, "GoogleCloudAiplatformV1beta1ToolGoogleSearchSearchTypes": { "properties": { "webSearch": { "$ref": "GoogleCloudAiplatformV1beta1ToolGoogleSearchWebSearch", "description": "Optional. Setting this field enables web search. Only text results are returned." }, "imageSearch": { "description": "Optional. Setting this field enables image search. Image bytes are returned.", "$ref": "GoogleCloudAiplatformV1beta1ToolGoogleSearchImageSearch" } }, "description": "Different types of search that can be enabled on the GoogleSearch tool.", "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearchSearchTypes", "type": "object" }, "GoogleCloudAiplatformV1beta1TaskEventData": { "description": "Data for a TaskEvent.", "properties": { "outputChange": { "$ref": "GoogleCloudAiplatformV1beta1TaskOutputChange", "description": "Optional. A change to the task's final outputs." }, "stateChange": { "description": "Optional. A change in the task's state.", "$ref": "GoogleCloudAiplatformV1beta1TaskStateChange" }, "statusDetailsChange": { "$ref": "GoogleCloudAiplatformV1beta1TaskStatusDetailsChange", "description": "Optional. A change to the framework-specific status details." }, "metadataChange": { "description": "Optional. A change to the task's metadata.", "$ref": "GoogleCloudAiplatformV1beta1TaskMetadataChange" } }, "id": "GoogleCloudAiplatformV1beta1TaskEventData", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaImageBoundingBoxAnnotation": { "id": "GoogleCloudAiplatformV1beta1SchemaImageBoundingBoxAnnotation", "type": "object", "properties": { "yMin": { "format": "double", "description": "The topmost coordinate of the bounding box.", "type": "number" }, "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "xMax": { "description": "The rightmost coordinate of the bounding box.", "format": "double", "type": "number" }, "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "xMin": { "format": "double", "description": "The leftmost coordinate of the bounding box.", "type": "number" }, "yMax": { "type": "number", "description": "The bottommost coordinate of the bounding box.", "format": "double" } }, "description": "Annotation details specific to image object detection." }, "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeatureFeatureValueAndTimestamp": { "id": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeatureFeatureValueAndTimestamp", "type": "object", "properties": { "value": { "$ref": "GoogleCloudAiplatformV1beta1FeatureValue", "description": "The feature value." }, "timestamp": { "type": "string", "description": "The feature timestamp to store with this value. If not set, then the Feature Store server will generate a timestamp when it receives the write request.", "format": "google-datetime" } }, "description": "Feature value and timestamp." }, "GoogleCloudAiplatformV1beta1ListSchedulesResponse": { "description": "Response message for ScheduleService.ListSchedules", "properties": { "schedules": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Schedule" }, "description": "List of Schedules in the requested page." }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListSchedulesRequest.page_token to obtain that page.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListSchedulesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateLossClustersOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1GenerateLossClustersOperationMetadata", "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Generic operation metadata." } }, "description": "Operation metadata for EvaluationAnalyticsService.GenerateLossClusters." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassification": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassification", "type": "object", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs" } }, "description": "A TrainingJob that trains and uploads an AutoML Text Classification Model." }, "CloudAiLargeModelsVisionGenerateVideoRequestImage": { "id": "CloudAiLargeModelsVisionGenerateVideoRequestImage", "type": "object", "description": "The image bytes or Cloud Storage URI to make the prediction on.", "properties": { "gcsUri": { "type": "string" }, "mimeType": { "description": "The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/png", "type": "string" }, "bytesBase64Encoded": { "description": "Base64 encoded bytes string representing the image.", "type": "string" }, "blobId": { "description": "Blob ID of the image. This is used for storing the large images in the request.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ListContextsResponse": { "id": "GoogleCloudAiplatformV1beta1ListContextsResponse", "type": "object", "properties": { "nextPageToken": { "description": "A token, which can be sent as ListContextsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages.", "type": "string" }, "contexts": { "description": "The Contexts retrieved from the MetadataStore.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Context" } } }, "description": "Response message for MetadataService.ListContexts." }, "GoogleCloudAiplatformV1beta1VertexAISearchDataStoreSpec": { "id": "GoogleCloudAiplatformV1beta1VertexAISearchDataStoreSpec", "type": "object", "properties": { "dataStore": { "description": "Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`", "type": "string" }, "filter": { "description": "Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)", "type": "string" } }, "description": "Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec" }, "GoogleCloudAiplatformV1beta1JiraSource": { "id": "GoogleCloudAiplatformV1beta1JiraSource", "type": "object", "description": "The Jira source for the ImportRagFilesRequest.", "properties": { "jiraQueries": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1JiraSourceJiraQueries" }, "description": "Required. The Jira queries." } } }, "GoogleCloudAiplatformV1beta1PairwiseMetricSpec": { "description": "Spec for pairwise metric.", "properties": { "baselineResponseFieldName": { "description": "Optional. The field name of the baseline response.", "type": "string" }, "metricPromptTemplate": { "description": "Required. Metric prompt template for pairwise metric.", "type": "string" }, "systemInstruction": { "description": "Optional. System instructions for pairwise metric.", "type": "string" }, "customOutputFormatConfig": { "$ref": "GoogleCloudAiplatformV1beta1CustomOutputFormatConfig", "description": "Optional. CustomOutputFormatConfig allows customization of metric output. When this config is set, the default output is replaced with the raw output string. If a custom format is chosen, the `pairwise_choice` and `explanation` fields in the corresponding metric result will be empty." }, "candidateResponseFieldName": { "description": "Optional. The field name of the candidate response.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1PairwiseMetricSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1GroundingMetadataSourceFlaggingUri": { "id": "GoogleCloudAiplatformV1beta1GroundingMetadataSourceFlaggingUri", "type": "object", "description": "A URI that can be used to flag a place or review for inappropriate content. This is populated only when the grounding source is Google Maps.", "properties": { "sourceId": { "description": "The ID of the place or review.", "type": "string" }, "flagContentUri": { "description": "The URI that can be used to flag the content.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1DatasetVersion": { "properties": { "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this DatasetVersion was created.", "format": "google-datetime" }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "modelReference": { "readOnly": true, "type": "string", "description": "Output only. Reference to the public base model last used by the dataset version. Only set for prompt dataset versions." }, "bigQueryDatasetName": { "description": "Output only. Name of the associated BigQuery dataset.", "type": "string", "readOnly": true }, "satisfiesPzs": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "name": { "description": "Output only. Identifier. The resource name of the DatasetVersion. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "readOnly": true, "type": "string" }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this DatasetVersion was last updated." }, "metadata": { "description": "Required. Output only. Additional information about the DatasetVersion.", "type": "any", "readOnly": true }, "displayName": { "description": "The user-defined name of the DatasetVersion. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" } }, "description": "Describes the dataset version.", "id": "GoogleCloudAiplatformV1beta1DatasetVersion", "type": "object" }, "GoogleCloudAiplatformV1beta1ComputeTokensRequest": { "id": "GoogleCloudAiplatformV1beta1ComputeTokensRequest", "type": "object", "properties": { "instances": { "description": "Optional. The instances that are the input to token computing API call. Schema is identical to the prediction schema of the text model, even for the non-text models, like chat models, or Codey models.", "type": "array", "items": { "type": "any" } }, "contents": { "description": "Optional. Input content.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "model": { "description": "Optional. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers/*/models/*", "type": "string" } }, "description": "Request message for ComputeTokens RPC call." }, "GoogleCloudAiplatformV1beta1MetricxSpec": { "description": "Spec for MetricX metric.", "properties": { "sourceLanguage": { "description": "Optional. Source language in BCP-47 format.", "type": "string" }, "version": { "enum": [ "METRICX_VERSION_UNSPECIFIED", "METRICX_24_REF", "METRICX_24_SRC", "METRICX_24_SRC_REF" ], "description": "Required. Which version to use for evaluation.", "type": "string", "enumDescriptions": [ "MetricX version unspecified.", "MetricX 2024 (2.6) for translation + reference (reference-based).", "MetricX 2024 (2.6) for translation + source (QE).", "MetricX 2024 (2.6) for translation + source + reference (source-reference-combined)." ] }, "targetLanguage": { "description": "Optional. Target language in BCP-47 format. Covers both prediction and reference.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1MetricxSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolCallValidMetricValue": { "id": "GoogleCloudAiplatformV1beta1ToolCallValidMetricValue", "type": "object", "properties": { "score": { "type": "number", "readOnly": true, "description": "Output only. Tool call valid score.", "format": "float" } }, "description": "Tool call valid metric value for an instance." }, "GoogleCloudAiplatformV1beta1NasTrialDetail": { "description": "Represents a NasTrial details along with its parameters. If there is a corresponding train NasTrial, the train NasTrial is also returned.", "properties": { "name": { "type": "string", "readOnly": true, "description": "Output only. Resource name of the NasTrialDetail." }, "parameters": { "description": "The parameters for the NasJob NasTrial.", "type": "string" }, "searchTrial": { "description": "The requested search NasTrial.", "$ref": "GoogleCloudAiplatformV1beta1NasTrial" }, "trainTrial": { "$ref": "GoogleCloudAiplatformV1beta1NasTrial", "description": "The train NasTrial corresponding to search_trial. Only populated if search_trial is used for training." } }, "id": "GoogleCloudAiplatformV1beta1NasTrialDetail", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesResponse": { "id": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesResponse", "type": "object", "description": "Response message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.", "properties": { "monitoringStats": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies" }, "description": "Stats retrieved for requested objectives. There are at most 1000 ModelMonitoringStatsAnomalies.FeatureHistoricStatsAnomalies.prediction_stats in the response." }, "nextPageToken": { "description": "The page token that can be used by the next JobService.SearchModelDeploymentMonitoringStatsAnomalies call.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1IngestionDirectContentsSourceEvent": { "id": "GoogleCloudAiplatformV1beta1IngestionDirectContentsSourceEvent", "type": "object", "description": "A single event to ingest.", "properties": { "content": { "description": "Required. The content of the event.", "$ref": "GoogleCloudAiplatformV1beta1Content" }, "eventId": { "description": "Optional. A unique identifier for the event. If an event with the same event_id is ingested multiple times, it will be de-duplicated.", "type": "string" }, "eventTime": { "format": "google-datetime", "description": "Optional. The time at which the event occurred. If provided, this timestamp will be used for ordering events within a stream. If not provided, the server-side ingestion time will be used.", "type": "string" } } }, "CloudAiLargeModelsVisionGenerateVideoResponseVideo": { "properties": { "bytesBase64Encoded": { "description": "Base64 encoded bytes string representing the video.", "type": "string" }, "experimentsMetadata": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperiments", "description": "Optional metadata returned from experimental requests. Likely only includes the rewritten prompt chunks." }, "mimeType": { "description": "The MIME type of the content of the video. - video/mp4", "type": "string" }, "gcsUri": { "description": "Cloud Storage URI where the generated video is written.", "type": "string" } }, "id": "CloudAiLargeModelsVisionGenerateVideoResponseVideo", "type": "object" }, "GoogleCloudAiplatformV1beta1StoredContentsExample": { "description": "A ContentsExample to be used with GenerateContent alongside information required for storage and retrieval with Example Store.", "properties": { "searchKeyGenerationMethod": { "description": "Optional. The method used to generate the search key from `contents_example.contents`. This is ignored when uploading an example if `search_key` is provided.", "$ref": "GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethod" }, "contentsExample": { "description": "Required. The example to be used with GenerateContent.", "$ref": "GoogleCloudAiplatformV1beta1ContentsExample" }, "searchKey": { "description": "Optional. (Optional) the search key used for retrieval. If not provided at upload-time, the search key will be generated from `contents_example.contents` using the method provided by `search_key_generation_method`. The generated search key will be included in retrieved examples.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1StoredContentsExample", "type": "object" }, "GoogleCloudAiplatformV1beta1RagManagedDbConfigSpanner": { "description": "Message to configure the Spanner database used by RagManagedDb.", "properties": { "basic": { "description": "Sets the RagManagedDb to the Basic tier. This is the default tier for Spanner mode if not explicitly chosen.", "$ref": "GoogleCloudAiplatformV1beta1RagManagedDbConfigBasic" }, "unprovisioned": { "$ref": "GoogleCloudAiplatformV1beta1RagManagedDbConfigUnprovisioned", "description": "Sets the RagManagedDb to the Unprovisioned tier." }, "scaled": { "description": "Sets the RagManagedDb to the Scaled tier.", "$ref": "GoogleCloudAiplatformV1beta1RagManagedDbConfigScaled" } }, "id": "GoogleCloudAiplatformV1beta1RagManagedDbConfigSpanner", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigAutoRoutingMode": { "properties": { "modelRoutingPreference": { "type": "string", "enumDescriptions": [ "Unspecified model routing preference.", "The model will be selected to prioritize the quality of the response.", "The model will be selected to balance quality and cost.", "The model will be selected to prioritize the cost of the request." ], "enum": [ "UNKNOWN", "PRIORITIZE_QUALITY", "BALANCED", "PRIORITIZE_COST" ], "description": "The model routing preference." } }, "description": "The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference.", "id": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigAutoRoutingMode", "type": "object" }, "GoogleCloudAiplatformV1beta1SafetySpec": { "description": "Spec for safety metric.", "properties": { "version": { "format": "int32", "description": "Optional. Which version to use for evaluation.", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1SafetySpec", "type": "object" }, "GoogleCloudAiplatformV1beta1ImportRagFilesConfig": { "properties": { "ragFileChunkingConfig": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1RagFileChunkingConfig", "description": "Specifies the size and overlap of chunks after importing RagFiles." }, "partialFailureBigquerySink": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination", "description": "The BigQuery destination to write partial failures to. It should be a bigquery table resource name (e.g. \"bq://projectId.bqDatasetId.bqTableId\"). The dataset must exist. If the table does not exist, it will be created with the expected schema. If the table exists, the schema will be validated and data will be added to this existing table. Deprecated. Prefer to use `import_result_bq_sink`." }, "partialFailureGcsSink": { "description": "The Cloud Storage path to write partial failures to. Deprecated. Prefer to use `import_result_gcs_sink`.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" }, "maxEmbeddingRequestsPerMin": { "type": "integer", "format": "int32", "description": "Optional. The max number of queries per minute that this job is allowed to make to the embedding model specified on the corpus. This value is specific to this job and not shared across other import jobs. Consult the Quotas page on the project to set an appropriate value here. If unspecified, a default value of 1,000 QPM would be used." }, "googleDriveSource": { "$ref": "GoogleCloudAiplatformV1beta1GoogleDriveSource", "description": "Google Drive location. Supports importing individual files as well as Google Drive folders." }, "ragFileTransformationConfig": { "$ref": "GoogleCloudAiplatformV1beta1RagFileTransformationConfig", "description": "Specifies the transformation config for RagFiles." }, "importResultGcsSink": { "description": "The Cloud Storage path to write import result to.", "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" }, "jiraSource": { "$ref": "GoogleCloudAiplatformV1beta1JiraSource", "description": "Jira queries with their corresponding authentication." }, "ragFileParsingConfig": { "$ref": "GoogleCloudAiplatformV1beta1RagFileParsingConfig", "description": "Optional. Specifies the parsing config for RagFiles. RAG will use the default parser if this field is not set." }, "gcsSource": { "$ref": "GoogleCloudAiplatformV1beta1GcsSource", "description": "Google Cloud Storage location. Supports importing individual files as well as entire Google Cloud Storage directories. Sample formats: - `gs://bucket_name/my_directory/object_name/my_file.txt` - `gs://bucket_name/my_directory`" }, "importResultBigquerySink": { "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination", "description": "The BigQuery destination to write import result to. It should be a bigquery table resource name (e.g. \"bq://projectId.bqDatasetId.bqTableId\"). The dataset must exist. If the table does not exist, it will be created with the expected schema. If the table exists, the schema will be validated and data will be added to this existing table." }, "ragFileMetadataConfig": { "description": "Specifies the metadata config for RagFiles. Including paths for metadata schema and metadata. Deprecated: Not in use.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1RagFileMetadataConfig" }, "globalMaxEmbeddingRequestsPerMin": { "format": "int32", "description": "Optional. The max number of queries per minute that the indexing pipeline job is allowed to make to the embedding model specified in the project. Please follow the quota usage guideline of the embedding model you use to set the value properly.If this value is not specified, max_embedding_requests_per_min will be used by indexing pipeline job as the global limit.", "type": "integer" }, "slackSource": { "description": "Slack channels with their corresponding access tokens.", "$ref": "GoogleCloudAiplatformV1beta1SlackSource" }, "sharePointSources": { "description": "SharePoint sources.", "$ref": "GoogleCloudAiplatformV1beta1SharePointSources" }, "rebuildAnnIndex": { "description": "Rebuilds the ANN index to optimize for recall on the imported data. Only applicable for RagCorpora running on RagManagedDb with `retrieval_strategy` set to `ANN`. The rebuild will be performed using the existing ANN config set on the RagCorpus. To change the ANN config, please use the UpdateRagCorpus API. Default is false, i.e., index is not rebuilt.", "type": "boolean" } }, "description": "Config for importing RagFiles.", "id": "GoogleCloudAiplatformV1beta1ImportRagFilesConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateOnlineEvaluatorOperationMetadata": { "properties": { "genericMetadata": { "description": "Generic operation metadata.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Metadata for the UpdateOnlineEvaluator operation.", "id": "GoogleCloudAiplatformV1beta1UpdateOnlineEvaluatorOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1EnableModelResponse": { "description": "Response message for ModelGardenService.EnableModel.", "properties": { "publisherEndpoint": { "readOnly": true, "type": "string", "description": "Output only. The publisher endpoint that the project is enabled for. Format: `projects/{project}/locations/{location}/publishers/{publisher}/models/{publisher_model}`" }, "enablementState": { "readOnly": true, "type": "string", "enumDescriptions": [ "The PublisherModel enable status is unclear. The API will default to this value.", "The PublisherModel is enabled successfully.", "The PublisherModel is failed to enable" ], "enum": [ "ENABLEMENT_STATE_UNSPECIFIED", "ENABLEMENT_STATE_SUCCEEDED", "ENABLEMENT_STATE_FAILED" ], "description": "Output only. The result of the model enablement." } }, "id": "GoogleCloudAiplatformV1beta1EnableModelResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingMetadata", "type": "object", "description": "Model metadata specific to TFT Forecasting.", "properties": { "trainCostMilliNodeHours": { "type": "string", "format": "int64", "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget." }, "evaluatedDataItemsBigqueryUri": { "description": "BigQuery destination uri for exported evaluated examples.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ListNasJobsResponse": { "id": "GoogleCloudAiplatformV1beta1ListNasJobsResponse", "type": "object", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListNasJobsRequest.page_token to obtain that page.", "type": "string" }, "nasJobs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NasJob" }, "description": "List of NasJobs in the requested page. NasJob.nas_job_output of the jobs will not be returned." } }, "description": "Response message for JobService.ListNasJobs" }, "GoogleCloudAiplatformV1beta1DeployedModelStatus": { "id": "GoogleCloudAiplatformV1beta1DeployedModelStatus", "type": "object", "properties": { "message": { "description": "Output only. The latest deployed model's status message (if any).", "readOnly": true, "type": "string" }, "availableReplicaCount": { "readOnly": true, "type": "integer", "format": "int32", "description": "Output only. The number of available replicas of the deployed model." }, "lastUpdateTime": { "description": "Output only. The time at which the status was last updated.", "format": "google-datetime", "type": "string", "readOnly": true } }, "description": "Runtime status of the deployed model." }, "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerUserUsageData": { "description": "Per user usage data.", "properties": { "viewCount": { "description": "Number of times the user has read data within the Tensorboard.", "format": "int64", "type": "string" }, "username": { "description": "User's username", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerUserUsageData", "type": "object" }, "GoogleCloudAiplatformV1beta1AcceptPublisherModelEulaRequest": { "properties": { "publisherModel": { "description": "Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}`, or `publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}`", "type": "string" } }, "description": "Request message for ModelGardenService.AcceptPublisherModelEula.", "id": "GoogleCloudAiplatformV1beta1AcceptPublisherModelEulaRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies", "type": "object", "description": "Historical Stats (and Anomalies) for a specific Feature.", "properties": { "featureDisplayName": { "description": "Display Name of the Feature.", "type": "string" }, "predictionStats": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly" }, "description": "A list of historical stats generated by different time window's Prediction Dataset." }, "threshold": { "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig", "description": "Threshold for anomaly detection." }, "trainingStats": { "$ref": "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly", "description": "Stats calculated for the Training Dataset." } } }, "GoogleCloudAiplatformV1beta1SafetySetting": { "properties": { "method": { "type": "string", "enumDescriptions": [ "The harm block method is unspecified.", "The harm block method uses both probability and severity scores.", "The harm block method uses the probability score." ], "enum": [ "HARM_BLOCK_METHOD_UNSPECIFIED", "SEVERITY", "PROBABILITY" ], "description": "Optional. The method for blocking content. If not specified, the default behavior is to use the probability score." }, "threshold": { "type": "string", "enumDescriptions": [ "The harm block threshold is unspecified.", "Block content with a low harm probability or higher.", "Block content with a medium harm probability or higher.", "Block content with a high harm probability.", "Do not block any content, regardless of its harm probability.", "Turn off the safety filter entirely." ], "enum": [ "HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF" ], "description": "Required. The threshold for blocking content. If the harm probability exceeds this threshold, the content will be blocked." }, "category": { "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "Content that promotes violence or incites hatred against individuals or groups based on certain attributes.", "Content that promotes, facilitates, or enables dangerous activities.", "Abusive, threatening, or content intended to bully, torment, or ridicule.", "Content that contains sexually explicit material.", "Deprecated: Election filter is not longer supported. The harm category is civic integrity.", "Images that contain hate speech.", "Images that contain dangerous content.", "Images that contain harassment.", "Images that contain sexually explicit content.", "Prompts designed to bypass safety filters." ], "enumDeprecated": [ false, false, false, false, false, true, false, false, false, false, false ], "enum": [ "HARM_CATEGORY_UNSPECIFIED", "HARM_CATEGORY_HATE_SPEECH", "HARM_CATEGORY_DANGEROUS_CONTENT", "HARM_CATEGORY_HARASSMENT", "HARM_CATEGORY_SEXUALLY_EXPLICIT", "HARM_CATEGORY_CIVIC_INTEGRITY", "HARM_CATEGORY_IMAGE_HATE", "HARM_CATEGORY_IMAGE_DANGEROUS_CONTENT", "HARM_CATEGORY_IMAGE_HARASSMENT", "HARM_CATEGORY_IMAGE_SEXUALLY_EXPLICIT", "HARM_CATEGORY_JAILBREAK" ], "description": "Required. The harm category to be blocked." } }, "description": "A safety setting that affects the safety-blocking behavior. A SafetySetting consists of a harm category and a threshold for that category.", "id": "GoogleCloudAiplatformV1beta1SafetySetting", "type": "object" }, "GoogleCloudAiplatformV1beta1ReplicatedVoiceConfig": { "properties": { "mimeType": { "description": "Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.", "type": "string" }, "voiceSampleAudio": { "type": "string", "format": "byte", "description": "Optional. The sample of the custom voice." } }, "description": "The configuration for the replicated voice to use.", "id": "GoogleCloudAiplatformV1beta1ReplicatedVoiceConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1StructValue": { "id": "GoogleCloudAiplatformV1beta1StructValue", "type": "object", "properties": { "values": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1StructFieldValue" }, "description": "A list of field values." } }, "description": "Struct (or object) type feature value." }, "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseSpec": { "id": "GoogleCloudAiplatformV1beta1TrajectorySingleToolUseSpec", "type": "object", "properties": { "toolName": { "description": "Required. Spec for tool name to be checked for in the predicted trajectory.", "type": "string" } }, "description": "Spec for TrajectorySingleToolUse metric - returns 1 if tool is present in the predicted trajectory, else 0." }, "GoogleCloudAiplatformV1beta1NfsMount": { "properties": { "mountPoint": { "description": "Required. Destination mount path. The NFS will be mounted for the user under /mnt/nfs/", "type": "string" }, "server": { "description": "Required. IP address of the NFS server.", "type": "string" }, "path": { "description": "Required. Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of `server:path`", "type": "string" } }, "description": "Represents a mount configuration for Network File System (NFS) to mount.", "id": "GoogleCloudAiplatformV1beta1NfsMount", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchFeaturesResponse": { "description": "Response message for FeaturestoreService.SearchFeatures.", "properties": { "features": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Feature" }, "description": "The Features matching the request. Fields returned: * `name` * `description` * `labels` * `create_time` * `update_time`" }, "nextPageToken": { "description": "A token, which can be sent as SearchFeaturesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SearchFeaturesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchEntryPoint": { "id": "GoogleCloudAiplatformV1beta1SearchEntryPoint", "type": "object", "properties": { "renderedContent": { "description": "Optional. An HTML snippet that can be embedded in a web page or an application's webview. This snippet displays a search result, including the title, URL, and a brief description of the search result.", "type": "string" }, "sdkBlob": { "type": "string", "description": "Optional. A base64-encoded JSON object that contains a list of search queries and their corresponding search URLs. This information can be used to build a custom search UI.", "format": "byte" } }, "description": "An entry point for displaying Google Search results. A `SearchEntryPoint` is populated when the grounding source for a model's response is Google Search. It provides information that you can use to display the search results in your application." }, "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValue": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValue", "type": "object", "properties": { "doubleValue": { "format": "double", "description": "Double.", "type": "number" }, "distributionValue": { "description": "Distribution.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValueDistributionDataValue" } }, "description": "Typed value of the statistics." }, "GoogleCloudAiplatformV1beta1RagManagedDbConfig": { "id": "GoogleCloudAiplatformV1beta1RagManagedDbConfig", "type": "object", "properties": { "serverless": { "$ref": "GoogleCloudAiplatformV1beta1RagManagedDbConfigServerless", "description": "Sets the backend to be the serverless mode offered by RAG Engine." }, "spanner": { "description": "Sets the RAG Engine backend to be RagManagedDb, built on top of Spanner. NOTE: This is the default mode (w/ Basic Tier) if not explicitly chosen.", "$ref": "GoogleCloudAiplatformV1beta1RagManagedDbConfigSpanner" }, "enterprise": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1RagManagedDbConfigEnterprise", "description": "Sets the RagManagedDb to the Enterprise tier." }, "basic": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1RagManagedDbConfigBasic", "description": "Deprecated: Use `mode` instead to set the tier under Spanner. Sets the RagManagedDb to the Basic tier." }, "unprovisioned": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1RagManagedDbConfigUnprovisioned", "description": "Deprecated: Use `mode` instead to set the tier under Spanner. Sets the RagManagedDb to the Unprovisioned tier." }, "scaled": { "description": "Deprecated: Use `mode` instead to set the tier under Spanner. Sets the RagManagedDb to the Scaled tier.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1RagManagedDbConfigScaled" } }, "description": "Configuration message for RagManagedDb used by RagEngine." }, "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetail": { "id": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetail", "type": "object", "description": "The runtime detail of a pipeline executor.", "properties": { "containerDetail": { "description": "Output only. The detailed info for a container executor.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailContainerDetail" }, "customJobDetail": { "description": "Output only. The detailed info for a custom job executor.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailCustomJobDetail" } } }, "GoogleCloudAiplatformV1beta1ExplanationMetadata": { "properties": { "outputs": { "description": "Required. Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataOutputMetadata" } }, "inputs": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadata" }, "description": "Required. Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance." }, "featureAttributionsSchemaUri": { "description": "Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML tabular Models always have this field populated by Vertex AI. Note: The URI given on output may be different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", "type": "string" }, "latentSpaceSource": { "description": "Name of the source to generate embeddings for example based explanations.", "type": "string" } }, "description": "Metadata describing the Model's input and output for explanation.", "id": "GoogleCloudAiplatformV1beta1ExplanationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTargetVertexModelSource": { "properties": { "model": { "description": "Model resource name. Format: projects/{project}/locations/{location}/models/{model}.", "type": "string" }, "modelVersionId": { "description": "Model version id.", "type": "string" } }, "description": "Model in Vertex AI Model Registry.", "id": "GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTargetVertexModelSource", "type": "object" }, "GoogleCloudAiplatformV1beta1IndexDatapointCrowdingTag": { "id": "GoogleCloudAiplatformV1beta1IndexDatapointCrowdingTag", "type": "object", "description": "Crowding tag is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute.", "properties": { "crowdingAttribute": { "description": "The attribute value used for crowding. The maximum number of neighbors to return per crowding attribute value (per_crowding_attribute_num_neighbors) is configured per-query. This field is ignored if per_crowding_attribute_num_neighbors is larger than the total number of neighbors to return for a given query.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1MigratableResourceAutomlModel": { "id": "GoogleCloudAiplatformV1beta1MigratableResourceAutomlModel", "type": "object", "description": "Represents one Model in automl.googleapis.com.", "properties": { "model": { "description": "Full resource name of automl Model. Format: `projects/{project}/locations/{location}/models/{model}`.", "type": "string" }, "modelDisplayName": { "description": "The Model's display name in automl.googleapis.com.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SlackSourceSlackChannels": { "id": "GoogleCloudAiplatformV1beta1SlackSourceSlackChannels", "type": "object", "description": "SlackChannels contains the Slack channels and corresponding access token.", "properties": { "channels": { "description": "Required. The Slack channel IDs.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SlackSourceSlackChannelsSlackChannel" } }, "apiKeyConfig": { "description": "Required. The SecretManager secret version resource name (e.g. projects/{project}/secrets/{secret}/versions/{version}) storing the Slack channel access token that has access to the slack channel IDs. See: https://api.slack.com/tutorials/tracks/getting-a-token.", "$ref": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig" } } }, "GoogleCloudAiplatformV1beta1ImportRagFilesRequest": { "properties": { "importRagFilesConfig": { "description": "Required. The config for the RagFiles to be synced and imported into the RagCorpus. VertexRagDataService.ImportRagFiles.", "$ref": "GoogleCloudAiplatformV1beta1ImportRagFilesConfig" } }, "description": "Request message for VertexRagDataService.ImportRagFiles.", "id": "GoogleCloudAiplatformV1beta1ImportRagFilesRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureMonitorJob": { "id": "GoogleCloudAiplatformV1beta1FeatureMonitorJob", "type": "object", "description": "Vertex AI Feature Monitor Job.", "properties": { "driftBaseFeatureMonitorJobId": { "readOnly": true, "type": "string", "format": "int64", "description": "Output only. FeatureMonitorJob ID comparing to which the drift is calculated." }, "featureSelectionConfig": { "description": "Output only. Feature selection config used when creating FeatureMonitorJob.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1FeatureSelectionConfig" }, "jobSummary": { "description": "Output only. Summary from the FeatureMonitorJob.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1FeatureMonitorJobJobSummary" }, "driftBaseSnapshotTime": { "description": "Output only. Data snapshot time comparing to which the drift is calculated.", "format": "google-datetime", "type": "string", "readOnly": true }, "name": { "description": "Identifier. Name of the FeatureMonitorJob. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_job}`.", "type": "string" }, "labels": { "description": "Optional. The labels with user-defined metadata to organize your FeatureMonitorJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", "type": "object", "additionalProperties": { "type": "string" } }, "description": { "description": "Optional. Description of the FeatureMonitor.", "type": "string" }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when this FeatureMonitorJob was created. Creation of a FeatureMonitorJob means that the job is pending / waiting for sufficient resources but may not have started running yet.", "readOnly": true, "type": "string" }, "finalStatus": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. Final status of the FeatureMonitorJob." }, "triggerType": { "enum": [ "FEATURE_MONITOR_JOB_TRIGGER_UNSPECIFIED", "FEATURE_MONITOR_JOB_TRIGGER_PERIODIC", "FEATURE_MONITOR_JOB_TRIGGER_ON_DEMAND" ], "description": "Output only. Trigger type of the Feature Monitor Job.", "readOnly": true, "type": "string", "enumDescriptions": [ "Trigger type unspecified.", "Triggered by periodic schedule.", "Triggered on demand by CreateFeatureMonitorJob request." ] } } }, "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset": { "id": "GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset", "type": "object", "properties": { "annotatedDataset": { "description": "Full resource name of data labeling AnnotatedDataset. Format: `projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}`.", "type": "string" }, "annotatedDatasetDisplayName": { "description": "The AnnotatedDataset's display name in datalabeling.googleapis.com.", "type": "string" } }, "description": "Represents one AnnotatedDataset in datalabeling.googleapis.com." }, "GoogleCloudAiplatformV1beta1ListModelEvaluationSlicesResponse": { "id": "GoogleCloudAiplatformV1beta1ListModelEvaluationSlicesResponse", "type": "object", "properties": { "modelEvaluationSlices": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSlice" }, "description": "List of ModelEvaluations in the requested page." }, "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListModelEvaluationSlicesRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for ModelService.ListModelEvaluationSlices." }, "GoogleCloudAiplatformV1beta1ListMetadataSchemasResponse": { "id": "GoogleCloudAiplatformV1beta1ListMetadataSchemasResponse", "type": "object", "properties": { "metadataSchemas": { "description": "The MetadataSchemas found for the MetadataStore.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MetadataSchema" } }, "nextPageToken": { "description": "A token, which can be sent as ListMetadataSchemasRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages.", "type": "string" } }, "description": "Response message for MetadataService.ListMetadataSchemas." }, "GoogleCloudAiplatformV1beta1UpdateDeploymentResourcePoolOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1UpdateDeploymentResourcePoolOperationMetadata", "type": "object", "description": "Runtime operation information for UpdateDeploymentResourcePool method.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The operation generic information." } } }, "GoogleCloudAiplatformV1beta1Retrieval": { "id": "GoogleCloudAiplatformV1beta1Retrieval", "type": "object", "properties": { "externalApi": { "description": "Use data source powered by external API for grounding.", "$ref": "GoogleCloudAiplatformV1beta1ExternalApi" }, "disableAttribution": { "deprecated": true, "type": "boolean", "description": "Optional. Deprecated. This option is no longer supported." }, "vertexAiSearch": { "description": "Set to use data source powered by Vertex AI Search.", "$ref": "GoogleCloudAiplatformV1beta1VertexAISearch" }, "vertexRagStore": { "$ref": "GoogleCloudAiplatformV1beta1VertexRagStore", "description": "Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService." } }, "description": "Defines a retrieval tool that model can call to access external knowledge." }, "GoogleCloudAiplatformV1beta1FeatureMonitoringStatsAnomaly": { "id": "GoogleCloudAiplatformV1beta1FeatureMonitoringStatsAnomaly", "type": "object", "description": "A list of historical SnapshotAnalysis or ImportFeaturesAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending.", "properties": { "objective": { "type": "string", "enumDescriptions": [ "If it's OBJECTIVE_UNSPECIFIED, monitoring_stats will be empty.", "Stats are generated by Import Feature Analysis.", "Stats are generated by Snapshot Analysis." ], "readOnly": true, "description": "Output only. The objective for each stats.", "enum": [ "OBJECTIVE_UNSPECIFIED", "IMPORT_FEATURE_ANALYSIS", "SNAPSHOT_ANALYSIS" ] }, "featureStatsAnomaly": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1FeatureStatsAnomaly", "description": "Output only. The stats and anomalies generated at specific timestamp." } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation": { "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.", "properties": { "columnName": { "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateLossClustersRequest": { "properties": { "evaluationSet": { "description": "Reference to a persisted EvaluationSet. The service will read items from this set.", "type": "string" }, "inlineResults": { "$ref": "GoogleCloudAiplatformV1beta1GenerateLossClustersRequestEvaluationResultList", "description": "Inline evaluation results. Useful for ephemeral analysis in notebooks/SDKs where data isn't persisted." }, "configs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LossAnalysisConfig" }, "description": "Required. Configuration for the analysis algorithm. Analysis for multiple metrics and multiple candidates could be specified." } }, "description": "Request message for EvaluationAnalyticsService.GenerateLossClusters.", "id": "GoogleCloudAiplatformV1beta1GenerateLossClustersRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ListFeaturestoresResponse": { "id": "GoogleCloudAiplatformV1beta1ListFeaturestoresResponse", "type": "object", "description": "Response message for FeaturestoreService.ListFeaturestores.", "properties": { "featurestores": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Featurestore" }, "description": "The Featurestores matching the request." }, "nextPageToken": { "description": "A token, which can be sent as ListFeaturestoresRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ListExtensionsResponse": { "id": "GoogleCloudAiplatformV1beta1ListExtensionsResponse", "type": "object", "description": "Response message for ExtensionRegistryService.ListExtensions", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListExtensionsRequest.page_token to obtain that page.", "type": "string" }, "extensions": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Extension" }, "description": "List of Extension in the requested page." } } }, "GoogleCloudAiplatformV1beta1PurgeExecutionsResponse": { "id": "GoogleCloudAiplatformV1beta1PurgeExecutionsResponse", "type": "object", "description": "Response message for MetadataService.PurgeExecutions.", "properties": { "purgeCount": { "description": "The number of Executions that this request deleted (or, if `force` is false, the number of Executions that will be deleted). This can be an estimate.", "format": "int64", "type": "string" }, "purgeSample": { "description": "A sample of the Execution names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer).", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1RuntimeConfig": { "id": "GoogleCloudAiplatformV1beta1RuntimeConfig", "type": "object", "description": "Runtime configuration to run the extension.", "properties": { "codeInterpreterRuntimeConfig": { "$ref": "GoogleCloudAiplatformV1beta1RuntimeConfigCodeInterpreterRuntimeConfig", "description": "Code execution runtime configurations for code interpreter extension." }, "vertexAiSearchRuntimeConfig": { "description": "Runtime configuration for Vertex AI Search extension.", "$ref": "GoogleCloudAiplatformV1beta1RuntimeConfigVertexAISearchRuntimeConfig" }, "defaultParams": { "description": "Optional. Default parameters that will be set for all the execution of this extension. If specified, the parameter values can be overridden by values in [[ExecuteExtensionRequest.operation_params]] at request time. The struct should be in a form of map with param name as the key and actual param value as the value. E.g. If this operation requires a param \"name\" to be set to \"abc\". you can set this to something like {\"name\": \"abc\"}.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig", "type": "object", "properties": { "skewThresholds": { "description": "Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig" } }, "attributionScoreSkewThresholds": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig" }, "description": "Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature." }, "defaultSkewThreshold": { "description": "Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.", "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig" } }, "description": "The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters." }, "GoogleCloudAiplatformV1beta1StreamingReadFeatureValuesRequest": { "description": "Request message for FeaturestoreOnlineServingService.StreamingReadFeatureValues.", "properties": { "entityIds": { "description": "Required. IDs of entities to read Feature values of. The maximum number of IDs is 100. For example, for a machine learning model predicting user clicks on a website, an entity ID could be `user_123`.", "type": "array", "items": { "type": "string" } }, "featureSelector": { "description": "Required. Selector choosing Features of the target EntityType. Feature IDs will be deduplicated.", "$ref": "GoogleCloudAiplatformV1beta1FeatureSelector" } }, "id": "GoogleCloudAiplatformV1beta1StreamingReadFeatureValuesRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoClassificationPredictionParams": { "properties": { "segmentClassification": { "description": "Set to true to request segment-level classification. Vertex AI returns labels and their confidence scores for the entire time segment of the video that user specified in the input instance. Default value is true", "type": "boolean" }, "shotClassification": { "description": "Set to true to request shot-level classification. Vertex AI determines the boundaries for each camera shot in the entire time segment of the video that user specified in the input instance. Vertex AI then returns labels and their confidence scores for each detected shot, along with the start and end time of the shot. WARNING: Model evaluation is not done for this classification type, the quality of it depends on the training data, but there are no metrics provided to describe that quality. Default value is false", "type": "boolean" }, "oneSecIntervalClassification": { "description": "Set to true to request classification for a video at one-second intervals. Vertex AI returns labels and their confidence scores for each second of the entire time segment of the video that user specified in the input WARNING: Model evaluation is not done for this classification type, the quality of it depends on the training data, but there are no metrics provided to describe that quality. Default value is false", "type": "boolean" }, "confidenceThreshold": { "type": "number", "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", "format": "float" }, "maxPredictions": { "type": "integer", "description": "The Model only returns up to that many top, by confidence score, predictions per instance. If this number is very high, the Model may return fewer predictions. Default value is 10,000.", "format": "int32" } }, "description": "Prediction model parameters for Video Classification.", "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoClassificationPredictionParams", "type": "object" }, "GoogleCloudAiplatformV1beta1CountTokensRequest": { "description": "Request message for PredictionService.CountTokens.", "properties": { "model": { "description": "Optional. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", "type": "string" }, "generationConfig": { "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig", "description": "Optional. Generation config that the model will use to generate the response." }, "instances": { "type": "array", "items": { "type": "any" }, "description": "Optional. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model." }, "contents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "description": "Optional. Input content." }, "tools": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" }, "description": "Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model." }, "systemInstruction": { "$ref": "GoogleCloudAiplatformV1beta1Content", "description": "Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph." } }, "id": "GoogleCloudAiplatformV1beta1CountTokensRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1RagRetrievalConfig": { "properties": { "ranking": { "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking", "description": "Optional. Config for ranking and reranking." }, "filter": { "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter", "description": "Optional. Config for filters." }, "topK": { "type": "integer", "description": "Optional. The number of contexts to retrieve.", "format": "int32" }, "hybridSearch": { "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch", "description": "Optional. Config for Hybrid Search." } }, "description": "Specifies the context retrieval config.", "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfigMemoryCorpus": { "id": "GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfigMemoryCorpus", "type": "object", "description": "Config for the memory corpus.", "properties": { "llmParser": { "$ref": "GoogleCloudAiplatformV1beta1RagFileParsingConfigLlmParser", "description": "The LLM parser to use for the memory corpus." } } }, "GoogleCloudAiplatformV1beta1DeployModelRequest": { "description": "Request message for EndpointService.DeployModel.", "properties": { "trafficSplit": { "type": "object", "additionalProperties": { "type": "integer", "format": "int32" }, "description": "A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If this field is non-empty, then the Endpoint's traffic_split will be overwritten with it. To refer to the ID of the just being deployed Model, a \"0\" should be used, and the actual ID of the new DeployedModel will be filled in its place by this method. The traffic percentage values must add up to 100. If this field is empty, then the Endpoint's traffic_split is not updated." }, "deployedModel": { "description": "Required. The DeployedModel to be created within the Endpoint. Note that Endpoint.traffic_split must be updated for the DeployedModel to start receiving traffic, either as part of this call, or via EndpointService.UpdateEndpoint.", "$ref": "GoogleCloudAiplatformV1beta1DeployedModel" } }, "id": "GoogleCloudAiplatformV1beta1DeployModelRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedVertexVectorSearch": { "properties": { "collectionName": { "readOnly": true, "type": "string", "description": "Output only. The resource name of the Vector Search 2.0 Collection that RAG Created for the corpus. Only populated after the corpus is successfully created. Format: `projects/{project}/locations/{location}/collections/{collection_id}`" } }, "description": "The config for the RAG-managed Vertex Vector Search 2.0.", "id": "GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedVertexVectorSearch", "type": "object" }, "GoogleCloudAiplatformV1beta1RetrieveProfilesRequest": { "id": "GoogleCloudAiplatformV1beta1RetrieveProfilesRequest", "type": "object", "properties": { "scope": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Required. The scope of the profiles to retrieve." } }, "description": "Request message for MemoryBankService.RetrieveProfiles." }, "GoogleCloudAiplatformV1beta1ExecuteCodeResponse": { "id": "GoogleCloudAiplatformV1beta1ExecuteCodeResponse", "type": "object", "description": "Response message for SandboxEnvironmentExecutionService.ExecuteCode.", "properties": { "outputs": { "description": "The outputs from the sandbox environment.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Chunk" } } } }, "GoogleCloudAiplatformV1beta1UploadRagFileConfig": { "id": "GoogleCloudAiplatformV1beta1UploadRagFileConfig", "type": "object", "properties": { "ragFileTransformationConfig": { "description": "Specifies the transformation config for RagFiles.", "$ref": "GoogleCloudAiplatformV1beta1RagFileTransformationConfig" }, "ragFileMetadataConfig": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1RagFileMetadataConfig", "description": "Optional. Specifies the metadata config for RagFiles. Including paths for metadata schema and metadata. Alteratively, inline metadata schema and metadata can be provided. Deprecated: Not in use." }, "ragFileParsingConfig": { "description": "Optional. Specifies the parsing config for RagFiles. RAG will use the default parser if this field is not set.", "$ref": "GoogleCloudAiplatformV1beta1RagFileParsingConfig" }, "ragFileChunkingConfig": { "description": "Specifies the size and overlap of chunks after uploading RagFile.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1RagFileChunkingConfig" } }, "description": "Config for uploading RagFile." }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigClientToAgentConfig": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigClientToAgentConfig", "type": "object", "properties": { "agentGateway": { "description": "Required. The resource name of the Agent Gateway to use for inbound traffic. It must be set to a Google-managed gateway whose `governed_access_path` is `CLIENT_TO_AGENT`. Format: `projects/{project}/locations/{location}/agentGateways/{agent_gateway}`", "type": "string" } }, "description": "Configuration for traffic targeting a Reasoning Engine." }, "GoogleCloudAiplatformV1beta1ListModelsResponse": { "id": "GoogleCloudAiplatformV1beta1ListModelsResponse", "type": "object", "description": "Response message for ModelService.ListModels", "properties": { "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListModelsRequest.page_token to obtain that page.", "type": "string" }, "models": { "description": "List of Models in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Model" } } } }, "GoogleCloudAiplatformV1beta1RubricGroup": { "properties": { "groupId": { "description": "Unique identifier for the group.", "type": "string" }, "displayName": { "description": "Human-readable name for the group. This should be unique within a given context if used for display or selection. Example: \"Instruction Following V1\", \"Content Quality - Summarization Task\".", "type": "string" }, "rubrics": { "description": "Rubrics that are part of this group.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Rubric" } } }, "description": "A group of rubrics, used for grouping rubrics based on a metric or a version.", "id": "GoogleCloudAiplatformV1beta1RubricGroup", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity", "type": "object", "properties": { "quantity": { "description": "The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1.", "format": "int64", "type": "string" }, "unit": { "description": "The time granularity unit of this time period. The supported units are: * \"minute\" * \"hour\" * \"day\" * \"week\" * \"month\" * \"year\"", "type": "string" } }, "description": "A duration of time expressed in time granularity units." }, "GoogleCloudAiplatformV1beta1IngestionDirectContentsSource": { "id": "GoogleCloudAiplatformV1beta1IngestionDirectContentsSource", "type": "object", "properties": { "events": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1IngestionDirectContentsSourceEvent" }, "description": "Required. The events to ingest." } }, "description": "Ingest events directly from the request." }, "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigInferenceAgentConfig": { "properties": { "developerInstruction": { "$ref": "GoogleCloudAiplatformV1beta1Content", "description": "Optional. The developer instruction for the agent." }, "tools": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" }, "description": "Optional. The tools available to the agent." } }, "description": "Configuration that describes an agent.", "id": "GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigInferenceAgentConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1DeployModelOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1DeployModelOperationMetadata", "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The operation generic information." }, "deploymentStage": { "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "The deployment is initializing and setting up the environment.", "The deployment is preparing the model assets.", "The deployment is creating the underlying serving cluster.", "The deployment is adding nodes to the serving cluster.", "The deployment is getting the container image for the model server.", "The deployment is starting the model server.", "The deployment is performing finalization steps.", "The deployment has terminated.", "The deployment has succeeded.", "The deployment has failed." ], "readOnly": true, "description": "Output only. The deployment stage of the model.", "enum": [ "DEPLOYMENT_STAGE_UNSPECIFIED", "STARTING_DEPLOYMENT", "PREPARING_MODEL", "CREATING_SERVING_CLUSTER", "ADDING_NODES_TO_CLUSTER", "GETTING_CONTAINER_IMAGE", "STARTING_MODEL_SERVER", "FINISHING_UP", "DEPLOYMENT_TERMINATED", "SUCCESSFULLY_DEPLOYED", "FAILED_TO_DEPLOY" ] } }, "description": "Runtime operation information for EndpointService.DeployModel." }, "GoogleCloudAiplatformV1beta1OnlineEvaluator": { "properties": { "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when the OnlineEvaluator was last updated." }, "name": { "description": "Identifier. The resource name of the OnlineEvaluator. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}.", "type": "string" }, "createTime": { "description": "Output only. Timestamp when the OnlineEvaluator was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "metricSources": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MetricSource" }, "description": "Required. A list of metric sources to be used for evaluating samples. At least one MetricSource must be provided. Right now, only predefined metrics and registered metrics are supported. Every registered metric must have `display_name` (or `title`) and `score_range` defined. Otherwise, the evaluations will fail. The maximum number of `metric_sources` is 25." }, "agentResource": { "description": "Required. Immutable. The name of the agent that the OnlineEvaluator evaluates periodically. This value is used to filter the traces with a matching cloud.resource_id and link the evaluation results with relevant dashboards/UIs. This field is immutable. Once set, it cannot be changed.", "type": "string" }, "stateDetails": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluatorStateDetails" }, "description": "Output only. Contains additional information about the state of the OnlineEvaluator. This is used to provide more details in the event of a failure." }, "state": { "readOnly": true, "type": "string", "enumDescriptions": [ "Default value.", "Indicates that the OnlineEvaluator is active.", "Indicates that the OnlineEvaluator is suspended. In this state, the OnlineEvaluator will not evaluate any samples.", "Indicates that the OnlineEvaluator is in a failed state. This can happen if, for example, the `log_view` or `trace_view` set on the `CloudObservability` does not exist." ], "enum": [ "STATE_UNSPECIFIED", "ACTIVE", "SUSPENDED", "FAILED" ], "description": "Output only. The state of the OnlineEvaluator." }, "cloudObservability": { "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservability", "description": "Data source for the OnlineEvaluator, based on GCP Observability stack (Cloud Trace & Cloud Logging)." }, "config": { "description": "Required. Configuration for the OnlineEvaluator.", "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluatorConfig" }, "displayName": { "description": "Optional. Human-readable name for the `OnlineEvaluator`. The name doesn't have to be unique. The name can consist of any UTF-8 characters. The maximum length is `63` characters. If the display name exceeds max characters, an `INVALID_ARGUMENT` error is returned.", "type": "string" } }, "description": "An OnlineEvaluator contains the configuration for an Online Evaluation.", "id": "GoogleCloudAiplatformV1beta1OnlineEvaluator", "type": "object" }, "GoogleCloudAiplatformV1beta1ServiceAccountSpec": { "properties": { "enableCustomServiceAccount": { "description": "Required. If true, custom user-managed service account is enforced to run any workloads (for example, Vertex Jobs) on the resource. Otherwise, uses the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).", "type": "boolean" }, "serviceAccount": { "description": "Optional. Required when all below conditions are met * `enable_custom_service_account` is true; * any runtime is specified via `ResourceRuntimeSpec` on creation time, for example, Ray The users must have `iam.serviceAccounts.actAs` permission on this service account and then the specified runtime containers will run as it. Do not set this field if you want to submit jobs using custom service account to this PersistentResource after creation, but only specify the `service_account` inside the job.", "type": "string" } }, "description": "Configuration for the use of custom service account to run the workloads.", "id": "GoogleCloudAiplatformV1beta1ServiceAccountSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1GeminiExample": { "properties": { "generationConfig": { "description": "Optional. Generation config.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig" }, "cachedContent": { "description": "Optional. The name of the cached content used as context to serve the prediction. Note: only used in explicit caching, where users can have control over caching (e.g. what content to cache) and enjoy guaranteed cost savings. Format: `projects/{project}/locations/{location}/cachedContents/{cachedContent}`", "type": "string" }, "contents": { "description": "Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "tools": { "description": "Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" } }, "modelArmorConfig": { "description": "Optional. Settings for prompt and response sanitization using the Model Armor service. If supplied, safety_settings must not be supplied.", "$ref": "GoogleCloudAiplatformV1beta1ModelArmorConfig" }, "model": { "description": "Optional. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string" }, "safetySettings": { "description": "Optional. Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SafetySetting" } }, "toolConfig": { "description": "Optional. Tool config. This config is shared for all tools provided in the request.", "$ref": "GoogleCloudAiplatformV1beta1ToolConfig" }, "systemInstruction": { "description": "Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.", "$ref": "GoogleCloudAiplatformV1beta1Content" }, "labels": { "description": "Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter.", "type": "object", "additionalProperties": { "type": "string" } } }, "description": "Format for Gemini examples used for Vertex Multimodal datasets.", "id": "GoogleCloudAiplatformV1beta1GeminiExample", "type": "object" }, "GoogleCloudAiplatformV1beta1UpsertDatapointsResponse": { "description": "Response message for IndexService.UpsertDatapoints", "properties": {}, "id": "GoogleCloudAiplatformV1beta1UpsertDatapointsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1PreferenceOptimizationDataStats": { "properties": { "userOutputTokenDistribution": { "description": "Output only. Dataset distributions for the user output tokens.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1DatasetDistribution" }, "droppedExampleIndices": { "type": "array", "items": { "format": "int64", "type": "string" }, "readOnly": true, "description": "Output only. A partial sample of the indices (starting from 1) of the dropped examples." }, "droppedExampleReasons": { "readOnly": true, "type": "array", "items": { "type": "string" }, "description": "Output only. For each index in `dropped_example_indices`, the user-facing reason why the example was dropped." }, "scoresDistribution": { "description": "Output only. Dataset distributions for scores.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1DatasetDistribution" }, "totalBillableTokenCount": { "format": "int64", "description": "Output only. Number of billable tokens in the tuning dataset.", "readOnly": true, "type": "string" }, "tuningDatasetExampleCount": { "type": "string", "readOnly": true, "description": "Output only. Number of examples in the tuning dataset.", "format": "int64" }, "tuningStepCount": { "description": "Output only. Number of tuning steps for this Tuning Job.", "format": "int64", "type": "string", "readOnly": true }, "userInputTokenDistribution": { "description": "Output only. Dataset distributions for the user input tokens.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1DatasetDistribution" }, "scoreVariancePerExampleDistribution": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1DatasetDistribution", "description": "Output only. Dataset distributions for scores variance per example." }, "userDatasetExamples": { "description": "Output only. Sample user examples in the training dataset.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GeminiPreferenceExample" } } }, "description": "Statistics computed for datasets used for preference optimization.", "id": "GoogleCloudAiplatformV1beta1PreferenceOptimizationDataStats", "type": "object" }, "GoogleCloudAiplatformV1beta1ImportDataRequest": { "id": "GoogleCloudAiplatformV1beta1ImportDataRequest", "type": "object", "properties": { "importConfigs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ImportDataConfig" }, "description": "Required. The desired input locations. The contents of all input locations will be imported in one batch." } }, "description": "Request message for DatasetService.ImportData." }, "GoogleCloudAiplatformV1beta1PurgeContextsMetadata": { "description": "Details of operations that perform MetadataService.PurgeContexts.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for purging Contexts." } }, "id": "GoogleCloudAiplatformV1beta1PurgeContextsMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ResumeScheduleRequest": { "id": "GoogleCloudAiplatformV1beta1ResumeScheduleRequest", "type": "object", "description": "Request message for ScheduleService.ResumeSchedule.", "properties": { "catchUp": { "description": "Optional. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. This will also update Schedule.catch_up field. Default to false.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1PredefinedMetricSpec": { "id": "GoogleCloudAiplatformV1beta1PredefinedMetricSpec", "type": "object", "description": "The spec for a pre-defined metric.", "properties": { "metricSpecName": { "description": "Required. The name of a pre-defined metric, such as \"instruction_following_v1\" or \"text_quality_v1\".", "type": "string" }, "metricSpecParameters": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. The parameters needed to run the pre-defined metric." } } }, "GoogleCloudAiplatformV1beta1ImportFeatureValuesOperationMetadata": { "description": "Details of operations that perform import Feature values.", "properties": { "blockingOperationIds": { "type": "array", "items": { "type": "string", "format": "int64" }, "description": "List of ImportFeatureValues operations running under a single EntityType that are blocking this operation." }, "importedEntityCount": { "description": "Number of entities that have been imported by the operation.", "format": "int64", "type": "string" }, "importedFeatureValueCount": { "description": "Number of Feature values that have been imported by the operation.", "format": "int64", "type": "string" }, "sourceUris": { "type": "array", "items": { "type": "string" }, "description": "The source URI from where Feature values are imported." }, "invalidRowCount": { "type": "string", "description": "The number of rows in input source that weren't imported due to either * Not having any featureValues. * Having a null entityId. * Having a null timestamp. * Not being parsable (applicable for CSV sources).", "format": "int64" }, "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "Operation metadata for Featurestore import Feature values." }, "timestampOutsideRetentionRowsCount": { "type": "string", "format": "int64", "description": "The number rows that weren't ingested due to having timestamps outside the retention boundary." } }, "id": "GoogleCloudAiplatformV1beta1ImportFeatureValuesOperationMetadata", "type": "object" }, "GoogleTypeColor": { "description": "Represents a color in the RGBA color space. This representation is designed for simplicity of conversion to and from color representations in various languages over compactness. For example, the fields of this representation can be trivially provided to the constructor of `java.awt.Color` in Java; it can also be trivially provided to UIColor's `+colorWithRed:green:blue:alpha` method in iOS; and, with just a little work, it can be easily formatted into a CSS `rgba()` string in JavaScript. This reference page doesn't have information about the absolute color space that should be used to interpret the RGB value—for example, sRGB, Adobe RGB, DCI-P3, and BT.2020. By default, applications should assume the sRGB color space. When color equality needs to be decided, implementations, unless documented otherwise, treat two colors as equal if all their red, green, blue, and alpha values each differ by at most `1e-5`. Example (Java): import com.google.type.Color; // ... public static java.awt.Color fromProto(Color protocolor) { float alpha = protocolor.hasAlpha() ? protocolor.getAlpha().getValue() : 1.0; return new java.awt.Color( protocolor.getRed(), protocolor.getGreen(), protocolor.getBlue(), alpha); } public static Color toProto(java.awt.Color color) { float red = (float) color.getRed(); float green = (float) color.getGreen(); float blue = (float) color.getBlue(); float denominator = 255.0; Color.Builder resultBuilder = Color .newBuilder() .setRed(red / denominator) .setGreen(green / denominator) .setBlue(blue / denominator); int alpha = color.getAlpha(); if (alpha != 255) { result.setAlpha( FloatValue .newBuilder() .setValue(((float) alpha) / denominator) .build()); } return resultBuilder.build(); } // ... Example (iOS / Obj-C): // ... static UIColor* fromProto(Color* protocolor) { float red = [protocolor red]; float green = [protocolor green]; float blue = [protocolor blue]; FloatValue* alpha_wrapper = [protocolor alpha]; float alpha = 1.0; if (alpha_wrapper != nil) { alpha = [alpha_wrapper value]; } return [UIColor colorWithRed:red green:green blue:blue alpha:alpha]; } static Color* toProto(UIColor* color) { CGFloat red, green, blue, alpha; if (![color getRed:&red green:&green blue:&blue alpha:&alpha]) { return nil; } Color* result = [[Color alloc] init]; [result setRed:red]; [result setGreen:green]; [result setBlue:blue]; if (alpha \u003c= 0.9999) { [result setAlpha:floatWrapperWithValue(alpha)]; } [result autorelease]; return result; } // ... Example (JavaScript): // ... var protoToCssColor = function(rgb_color) { var redFrac = rgb_color.red || 0.0; var greenFrac = rgb_color.green || 0.0; var blueFrac = rgb_color.blue || 0.0; var red = Math.floor(redFrac * 255); var green = Math.floor(greenFrac * 255); var blue = Math.floor(blueFrac * 255); if (!('alpha' in rgb_color)) { return rgbToCssColor(red, green, blue); } var alphaFrac = rgb_color.alpha.value || 0.0; var rgbParams = [red, green, blue].join(','); return ['rgba(', rgbParams, ',', alphaFrac, ')'].join(''); }; var rgbToCssColor = function(red, green, blue) { var rgbNumber = new Number((red \u003c\u003c 16) | (green \u003c\u003c 8) | blue); var hexString = rgbNumber.toString(16); var missingZeros = 6 - hexString.length; var resultBuilder = ['#']; for (var i = 0; i \u003c missingZeros; i++) { resultBuilder.push('0'); } resultBuilder.push(hexString); return resultBuilder.join(''); }; // ...", "properties": { "alpha": { "format": "float", "description": "The fraction of this color that should be applied to the pixel. That is, the final pixel color is defined by the equation: `pixel color = alpha * (this color) + (1.0 - alpha) * (background color)` This means that a value of 1.0 corresponds to a solid color, whereas a value of 0.0 corresponds to a completely transparent color. This uses a wrapper message rather than a simple float scalar so that it is possible to distinguish between a default value and the value being unset. If omitted, this color object is rendered as a solid color (as if the alpha value had been explicitly given a value of 1.0).", "type": "number" }, "blue": { "description": "The amount of blue in the color as a value in the interval [0, 1].", "format": "float", "type": "number" }, "red": { "type": "number", "format": "float", "description": "The amount of red in the color as a value in the interval [0, 1]." }, "green": { "type": "number", "description": "The amount of green in the color as a value in the interval [0, 1].", "format": "float" } }, "id": "GoogleTypeColor", "type": "object" }, "GoogleCloudAiplatformV1beta1RecommendSpecResponseMachineAndModelContainerSpec": { "properties": { "machineSpec": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1MachineSpec", "description": "Output only. The machine spec." }, "containerSpec": { "description": "Output only. The model container spec.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ModelContainerSpec" } }, "description": "A machine and model container spec.", "id": "GoogleCloudAiplatformV1beta1RecommendSpecResponseMachineAndModelContainerSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1SpeculativeDecodingSpec": { "properties": { "draftModelSpeculation": { "$ref": "GoogleCloudAiplatformV1beta1SpeculativeDecodingSpecDraftModelSpeculation", "description": "draft model speculation." }, "ngramSpeculation": { "description": "N-Gram speculation.", "$ref": "GoogleCloudAiplatformV1beta1SpeculativeDecodingSpecNgramSpeculation" }, "speculativeTokenCount": { "format": "int32", "description": "The number of speculative tokens to generate at each step.", "type": "integer" } }, "description": "Configuration for Speculative Decoding.", "id": "GoogleCloudAiplatformV1beta1SpeculativeDecodingSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsRequest": { "properties": { "requests": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1CreateTensorboardRunRequest" }, "description": "Required. The request message specifying the TensorboardRuns to create. A maximum of 1000 TensorboardRuns can be created in a batch." } }, "description": "Request message for TensorboardService.BatchCreateTensorboardRuns.", "id": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1TensorboardTensor": { "properties": { "versionNumber": { "description": "Optional. Version number of TensorProto used to serialize value.", "format": "int32", "type": "integer" }, "value": { "format": "byte", "description": "Required. Serialized form of https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor.proto", "type": "string" } }, "description": "One point viewable on a tensor metric plot.", "id": "GoogleCloudAiplatformV1beta1TensorboardTensor", "type": "object" }, "GoogleCloudAiplatformV1beta1ContainerRegistryDestination": { "id": "GoogleCloudAiplatformV1beta1ContainerRegistryDestination", "type": "object", "properties": { "outputUri": { "description": "Required. Container Registry URI of a container image. Only Google Container Registry and Artifact Registry are supported now. Accepted forms: * Google Container Registry path. For example: `gcr.io/projectId/imageName:tag`. * Artifact Registry path. For example: `us-central1-docker.pkg.dev/projectId/repoName/imageName:tag`. If a tag is not specified, \"latest\" will be used as the default tag.", "type": "string" } }, "description": "The Container Registry location for the container image." }, "GoogleCloudAiplatformV1beta1DedicatedResources": { "description": "A description of resources that are dedicated to a DeployedModel or DeployedIndex, and that need a higher degree of manual configuration.", "properties": { "requiredReplicaCount": { "description": "Optional. Number of required available replicas for the deployment to succeed. This field is only needed when partial deployment/mutation is desired. If set, the deploy/mutate operation will succeed once available_replica_count reaches required_replica_count, and the rest of the replicas will be retried. If not set, the default required_replica_count will be min_replica_count.", "format": "int32", "type": "integer" }, "minReplicaCount": { "format": "int32", "description": "Required. Immutable. The minimum number of machine replicas that will be always deployed on. This value must be greater than or equal to 1. If traffic increases, it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed.", "type": "integer" }, "initialReplicaCount": { "type": "integer", "description": "Immutable. Number of initial replicas being deployed on when scaling the workload up from zero or when creating the workload in case min_replica_count = 0. When min_replica_count \u003e 0 (meaning that the scale-to-zero feature is not enabled), initial_replica_count should not be set. When min_replica_count = 0 (meaning that the scale-to-zero feature is enabled), initial_replica_count should be larger than zero, but no greater than max_replica_count.", "format": "int32" }, "scaleToZeroSpec": { "$ref": "GoogleCloudAiplatformV1beta1DedicatedResourcesScaleToZeroSpec", "description": "Optional. Specification for scale-to-zero feature." }, "spot": { "description": "Optional. If true, schedule the deployment workload on [spot VMs](https://cloud.google.com/kubernetes-engine/docs/concepts/spot-vms).", "type": "boolean" }, "machineSpec": { "$ref": "GoogleCloudAiplatformV1beta1MachineSpec", "description": "Required. Immutable. The specification of a single machine being used." }, "maxReplicaCount": { "type": "integer", "format": "int32", "description": "Immutable. The maximum number of replicas that may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale to that many replicas is guaranteed (barring service outages). If traffic increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, will use min_replica_count as the default value. The value of this field impacts the charge against Vertex CPU and GPU quotas. Specifically, you will be charged for (max_replica_count * number of cores in the selected machine type) and (max_replica_count * number of GPUs per replica in the selected machine type)." }, "autoscalingMetricSpecs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1AutoscalingMetricSpec" }, "description": "Immutable. The metric specifications that overrides a resource utilization metric (CPU utilization, accelerator's duty cycle, and so on) target value (default to 60 if not set). At most one entry is allowed per metric. If machine_spec.accelerator_count is above 0, the autoscaling will be based on both CPU utilization and accelerator's duty cycle metrics and scale up when either metrics exceeds its target value while scale down if both metrics are under their target value. The default target value is 60 for both metrics. If machine_spec.accelerator_count is 0, the autoscaling will be based on CPU utilization metric only with default target value 60 if not explicitly set. For example, in the case of Online Prediction, if you want to override target CPU utilization to 80, you should set autoscaling_metric_specs.metric_name to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and autoscaling_metric_specs.target to `80`." }, "flexStart": { "$ref": "GoogleCloudAiplatformV1beta1FlexStart", "description": "Optional. Immutable. If set, use DWS resource to schedule the deployment workload. reference: (https://cloud.google.com/blog/products/compute/introducing-dynamic-workload-scheduler)" } }, "id": "GoogleCloudAiplatformV1beta1DedicatedResources", "type": "object" }, "GoogleCloudAiplatformV1beta1GroundingSupport": { "id": "GoogleCloudAiplatformV1beta1GroundingSupport", "type": "object", "description": "A collection of supporting references for a segment or part of the model's response.", "properties": { "segment": { "$ref": "GoogleCloudAiplatformV1beta1Segment", "description": "The content segment that this support message applies to." }, "groundingChunkIndices": { "description": "A list of indices into the `grounding_chunks` field of the `GroundingMetadata` message. These indices specify which grounding chunks support the claim made in the content segment. For example, if this field has the values `[1, 3]`, it means that `grounding_chunks[1]` and `grounding_chunks[3]` are the sources for the claim in the content segment.", "type": "array", "items": { "format": "int32", "type": "integer" } }, "confidenceScores": { "type": "array", "items": { "format": "float", "type": "number" }, "description": "The confidence scores for the support references. This list is parallel to the `grounding_chunk_indices` list. A score is a value between 0.0 and 1.0, with a higher score indicating a higher confidence that the reference supports the claim. For Gemini 2.0 and before, this list has the same size as `grounding_chunk_indices`. For Gemini 2.5 and later, this list is empty and should be ignored." }, "renderedParts": { "description": "Indices into the `rendered_parts` field of the `GroundingMetadata` message. These indices specify which rendered parts are associated with this support message.", "type": "array", "items": { "format": "int32", "type": "integer" } } } }, "GoogleCloudAiplatformV1beta1ExamplesRestrictionsNamespace": { "properties": { "namespaceName": { "description": "The namespace name.", "type": "string" }, "deny": { "type": "array", "items": { "type": "string" }, "description": "The list of deny tags." }, "allow": { "description": "The list of allowed tags.", "type": "array", "items": { "type": "string" } } }, "description": "Restrictions namespace for example-based explanations overrides.", "id": "GoogleCloudAiplatformV1beta1ExamplesRestrictionsNamespace", "type": "object" }, "GoogleCloudAiplatformV1beta1GdcConfig": { "id": "GoogleCloudAiplatformV1beta1GdcConfig", "type": "object", "description": "Google Distributed Cloud (GDC) config.", "properties": { "zone": { "description": "GDC zone. A cluster will be designated for the Vertex AI workload in this zone.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1DirectRawPredictResponse": { "id": "GoogleCloudAiplatformV1beta1DirectRawPredictResponse", "type": "object", "properties": { "output": { "format": "byte", "description": "The prediction output.", "type": "string" } }, "description": "Response message for PredictionService.DirectRawPredict." }, "GoogleCloudAiplatformV1beta1A2aTask": { "id": "GoogleCloudAiplatformV1beta1A2aTask", "type": "object", "description": "An A2aTask represents a unit of work.", "properties": { "expireTime": { "type": "string", "description": "Optional. Timestamp of when this task is considered expired. This is *always* provided on output, and is calculated based on the `ttl` if set on the request", "format": "google-datetime" }, "ttl": { "type": "string", "format": "google-duration", "description": "Optional. Input only. The TTL (Time To Live) for the task. If not set, the task will expire in 24 hours by default. Valid range: (0 seconds, 1000 days]" }, "state": { "readOnly": true, "type": "string", "enumDescriptions": [ "Task state unspecified. Default value if not set.", "Task is submitted and waiting to be processed.", "Task is actively being processed.", "Task is finished.", "Task is cancelled.", "Task has failed.", "Task is rejected by the system.", "Task requires input from the user.", "Task requires auth (e.g. OAuth) from the user.", "Task is paused." ], "enum": [ "STATE_UNSPECIFIED", "SUBMITTED", "WORKING", "COMPLETED", "CANCELLED", "FAILED", "REJECTED", "INPUT_REQUIRED", "AUTH_REQUIRED", "PAUSED" ], "description": "Output only. The state of the task. The state of a new task is SUBMITTED by default. The state of a task can only be updated via AppendA2aTaskEvents API." }, "statusDetails": { "description": "Optional. The status details of the task.", "$ref": "GoogleCloudAiplatformV1beta1TaskStatusDetails" }, "contextId": { "description": "Optional. A generic identifier for grouping related tasks (e.g., session_id, workflow_id).", "type": "string" }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. The creation timestamp of the task.", "format": "google-datetime" }, "metadata": { "description": "Optional. Arbitrary, user-defined metadata.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "nextEventSequenceNumber": { "type": "string", "readOnly": true, "description": "Output only. The next event sequence number to be appended to the task. This value starts at 1 and is guaranteed to be monotonically increasing.", "format": "int64" }, "output": { "$ref": "GoogleCloudAiplatformV1beta1TaskOutput", "description": "Optional. The final output of the task." }, "updateTime": { "description": "Output only. The last update timestamp of the task.", "format": "google-datetime", "type": "string", "readOnly": true }, "name": { "description": "Identifier. The resource name of the task. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/a2aTasks/{a2a_task}`", "type": "string" } } }, "CloudAiLargeModelsVisionSemanticFilterResponse": { "properties": { "passedSemanticFilter": { "description": "This response is added when semantic filter config is turned on in EditConfig. It reports if this image is passed semantic filter response. If passed_semantic_filter is false, the bounding box information will be populated for user to check what caused the semantic filter to fail.", "type": "boolean" }, "namedBoundingBoxes": { "description": "Class labels of the bounding boxes that failed the semantic filtering. Bounding box coordinates.", "type": "array", "items": { "$ref": "CloudAiLargeModelsVisionNamedBoundingBox" } } }, "id": "CloudAiLargeModelsVisionSemanticFilterResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1EmbedContentResponse": { "id": "GoogleCloudAiplatformV1beta1EmbedContentResponse", "type": "object", "properties": { "truncated": { "description": "Whether the input content was truncated before generating the embedding.", "type": "boolean" }, "embedding": { "description": "The embedding generated from the input content.", "$ref": "GoogleCloudAiplatformV1beta1EmbedContentResponseEmbedding" }, "usageMetadata": { "description": "Usage metadata about the response(s).", "$ref": "GoogleCloudAiplatformV1beta1UsageMetadata" } }, "description": "Response message for PredictionService.EmbedContent." }, "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityOpenTelemetry": { "description": "Configuration for data source following OpenTelemetry.", "properties": { "semconvVersion": { "description": "Required. Defines which version OTel Semantic Convention the data follows. Can be \"1.39.0\" or newer.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1OnlineEvaluatorCloudObservabilityOpenTelemetry", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentiment": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentiment", "type": "object", "properties": { "inputs": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs", "description": "The input parameters of this TrainingJob." } }, "description": "A TrainingJob that trains and uploads an AutoML Text Sentiment Model." }, "GoogleCloudAiplatformV1beta1BleuInput": { "description": "Input for bleu metric.", "properties": { "metricSpec": { "description": "Required. Spec for bleu score metric.", "$ref": "GoogleCloudAiplatformV1beta1BleuSpec" }, "instances": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1BleuInstance" }, "description": "Required. Repeated bleu instances." } }, "id": "GoogleCloudAiplatformV1beta1BleuInput", "type": "object" }, "GoogleCloudAiplatformV1beta1CustomJob": { "id": "GoogleCloudAiplatformV1beta1CustomJob", "type": "object", "properties": { "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key options for a CustomJob. If this is set, then all resources created by the CustomJob will be encrypted with the provided encryption key." }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize CustomJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." }, "endTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the CustomJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`." }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Time when the CustomJob was most recently updated.", "format": "google-datetime" }, "error": { "description": "Output only. Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "webAccessUris": { "readOnly": true, "type": "object", "additionalProperties": { "type": "string" }, "description": "Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if job_spec.enable_web_access is `true`. The keys are names of each node in the training job; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell." }, "jobSpec": { "$ref": "GoogleCloudAiplatformV1beta1CustomJobSpec", "description": "Required. Job spec." }, "createTime": { "format": "google-datetime", "description": "Output only. Time when the CustomJob was created.", "readOnly": true, "type": "string" }, "startTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state." }, "state": { "readOnly": true, "type": "string", "enumDescriptions": [ "The job state is unspecified.", "The job has been just created or resumed and processing has not yet begun.", "The service is preparing to run the job.", "The job is in progress.", "The job completed successfully.", "The job failed.", "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "The job has been cancelled.", "The job has been stopped, and can be resumed.", "The job has expired.", "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", "The job is partially succeeded, some results may be missing due to errors." ], "enum": [ "JOB_STATE_UNSPECIFIED", "JOB_STATE_QUEUED", "JOB_STATE_PENDING", "JOB_STATE_RUNNING", "JOB_STATE_SUCCEEDED", "JOB_STATE_FAILED", "JOB_STATE_CANCELLING", "JOB_STATE_CANCELLED", "JOB_STATE_PAUSED", "JOB_STATE_EXPIRED", "JOB_STATE_UPDATING", "JOB_STATE_PARTIALLY_SUCCEEDED" ], "description": "Output only. The detailed state of the job." }, "displayName": { "description": "Required. The display name of the CustomJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "name": { "readOnly": true, "type": "string", "description": "Output only. Resource name of a CustomJob." }, "satisfiesPzs": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." } }, "description": "Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded)." }, "GoogleCloudAiplatformV1beta1PredictRequestResponseLoggingConfig": { "id": "GoogleCloudAiplatformV1beta1PredictRequestResponseLoggingConfig", "type": "object", "properties": { "enabled": { "description": "If logging is enabled or not.", "type": "boolean" }, "bigqueryDestination": { "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination", "description": "BigQuery table for logging. If only given a project, a new dataset will be created with name `logging__` where will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores). If no table name is given, a new table will be created with name `request_response_logging`" }, "requestResponseLoggingSchemaVersion": { "type": "string", "readOnly": true, "description": "Output only. The schema version used in creating the BigQuery table for the request response logging. The versions are \"v1\" and \"v2\". The current default version is \"v1\"." }, "enableOtelLogging": { "description": "This field is used for large models. If true, in addition to the original large model logs, logs will be converted in OTel schema format, and saved in otel_log column. Default value is false.", "type": "boolean" }, "samplingRate": { "type": "number", "format": "double", "description": "Percentage of requests to be logged, expressed as a fraction in range(0,1]." }, "errorSamplingRate": { "type": "number", "format": "double", "description": "Optional. Percentage of failed requests to be logged, expressed as a fraction in range [0,1]. Only non-transient errors will be logged (currently `500/Internal` errors)." } }, "description": "Configuration for logging request-response to a BigQuery table." }, "GoogleCloudAiplatformV1beta1IndexDatapointRestriction": { "id": "GoogleCloudAiplatformV1beta1IndexDatapointRestriction", "type": "object", "properties": { "namespace": { "description": "The namespace of this restriction. e.g.: color.", "type": "string" }, "denyList": { "type": "array", "items": { "type": "string" }, "description": "The attributes to deny in this namespace. e.g.: 'blue'" }, "allowList": { "type": "array", "items": { "type": "string" }, "description": "The attributes to allow in this namespace. e.g.: 'red'" } }, "description": "Restriction of a datapoint which describe its attributes(tokens) from each of several attribute categories(namespaces)." }, "GoogleCloudAiplatformV1beta1TaskStatusDetails": { "id": "GoogleCloudAiplatformV1beta1TaskStatusDetails", "type": "object", "description": "Represents the additional status details of a task.", "properties": { "taskMessage": { "$ref": "GoogleCloudAiplatformV1beta1TaskMessage", "description": "Optional. The message associated with the single-turn interaction between the user and the agent or agent and agent." } } }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsQuestionAnsweringEvaluationMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsQuestionAnsweringEvaluationMetrics", "type": "object", "properties": { "exactMatch": { "type": "number", "format": "float", "description": "The rate at which the input predicted strings exactly match their references." } } }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetrics", "type": "object", "properties": { "confidenceMetrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics" }, "description": "Metrics for each label-match `confidenceThreshold` from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is derived from them." }, "iouThreshold": { "format": "float", "description": "The intersection-over-union threshold value between bounding boxes across frames used to compute this metric entry.", "type": "number" }, "meanBoundingBoxIou": { "description": "The mean bounding box iou over all confidence thresholds.", "format": "float", "type": "number" }, "meanTrackingAveragePrecision": { "type": "number", "format": "float", "description": "The mean average precision over all confidence thresholds." }, "meanMismatchRate": { "type": "number", "format": "float", "description": "The mean mismatch rate over all confidence thresholds." } }, "description": "UNIMPLEMENTED. Track matching model metrics for a single track match threshold and multiple label match confidence thresholds." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs": { "properties": { "multiLabel": { "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs", "type": "object" }, "GoogleCloudAiplatformV1beta1ImportFeatureValuesResponse": { "properties": { "importedFeatureValueCount": { "description": "Number of Feature values that have been imported by the operation.", "format": "int64", "type": "string" }, "timestampOutsideRetentionRowsCount": { "type": "string", "description": "The number rows that weren't ingested due to having feature timestamps outside the retention boundary.", "format": "int64" }, "invalidRowCount": { "type": "string", "format": "int64", "description": "The number of rows in input source that weren't imported due to either * Not having any featureValues. * Having a null entityId. * Having a null timestamp. * Not being parsable (applicable for CSV sources)." }, "importedEntityCount": { "type": "string", "description": "Number of entities that have been imported by the operation.", "format": "int64" } }, "description": "Response message for FeaturestoreService.ImportFeatureValues.", "id": "GoogleCloudAiplatformV1beta1ImportFeatureValuesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ExportModelOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1ExportModelOperationMetadata", "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The common part of the operation metadata." }, "outputInfo": { "description": "Output only. Information further describing the output of this Model export.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ExportModelOperationMetadataOutputInfo" } }, "description": "Details of ModelService.ExportModel operation." }, "GoogleCloudAiplatformV1beta1ToolCallValidInstance": { "description": "Spec for tool call valid instance.", "properties": { "reference": { "description": "Required. Ground truth used to compare against the prediction.", "type": "string" }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ToolCallValidInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1FeatureMonitor": { "properties": { "name": { "description": "Identifier. Name of the FeatureMonitor. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}/featureMonitors/{featureMonitor}`", "type": "string" }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this FeatureMonitor was last updated." }, "scheduleConfig": { "$ref": "GoogleCloudAiplatformV1beta1ScheduleConfig", "description": "Required. Schedule config for the FeatureMonitor." }, "labels": { "description": "Optional. The labels with user-defined metadata to organize your FeatureMonitor. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", "type": "object", "additionalProperties": { "type": "string" } }, "featureSelectionConfig": { "$ref": "GoogleCloudAiplatformV1beta1FeatureSelectionConfig", "description": "Required. Feature selection config for the FeatureMonitor." }, "createTime": { "description": "Output only. Timestamp when this FeatureMonitor was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "description": { "description": "Optional. Description of the FeatureMonitor.", "type": "string" }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" } }, "description": "Vertex AI Feature Monitor.", "id": "GoogleCloudAiplatformV1beta1FeatureMonitor", "type": "object" }, "GoogleCloudAiplatformV1beta1ImportDataResponse": { "properties": {}, "description": "Response message for DatasetService.ImportData.", "id": "GoogleCloudAiplatformV1beta1ImportDataResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequest": { "properties": { "csvSource": { "$ref": "GoogleCloudAiplatformV1beta1CsvSource" }, "featureTime": { "description": "Single Feature timestamp for all entities being imported. The timestamp must not have higher than millisecond precision.", "format": "google-datetime", "type": "string" }, "bigquerySource": { "$ref": "GoogleCloudAiplatformV1beta1BigQuerySource" }, "disableIngestionAnalysis": { "description": "If true, API doesn't start ingestion analysis pipeline.", "type": "boolean" }, "disableOnlineServing": { "description": "If set, data will not be imported for online serving. This is typically used for backfilling, where Feature generation timestamps are not in the timestamp range needed for online serving.", "type": "boolean" }, "featureTimeField": { "description": "Source column that holds the Feature timestamp for all Feature values in each entity.", "type": "string" }, "avroSource": { "$ref": "GoogleCloudAiplatformV1beta1AvroSource" }, "featureSpecs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequestFeatureSpec" }, "description": "Required. Specifications defining which Feature values to import from the entity. The request fails if no feature_specs are provided, and having multiple feature_specs for one Feature is not allowed." }, "workerCount": { "format": "int32", "description": "Specifies the number of workers that are used to write data to the Featurestore. Consider the online serving capacity that you require to achieve the desired import throughput without interfering with online serving. The value must be positive, and less than or equal to 100. If not set, defaults to using 1 worker. The low count ensures minimal impact on online serving performance.", "type": "integer" }, "entityIdField": { "description": "Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id.", "type": "string" } }, "description": "Request message for FeaturestoreService.ImportFeatureValues.", "id": "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationRunMetric": { "description": "The metric used for evaluation runs.", "properties": { "rubricBasedMetricSpec": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricBasedMetricSpec", "description": "Spec for rubric based metric." }, "predefinedMetricSpec": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunMetricPredefinedMetricSpec", "description": "Spec for a pre-defined metric." }, "llmBasedMetricSpec": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunMetricLLMBasedMetricSpec", "description": "Spec for an LLM based metric." }, "metricResourceName": { "description": "Optional. The resource name of the metric definition.", "type": "string" }, "metric": { "description": "Required. The name of the metric.", "type": "string" }, "computationBasedMetricSpec": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRunMetricComputationBasedMetricSpec", "description": "Spec for a computation based metric." }, "metricConfig": { "$ref": "GoogleCloudAiplatformV1beta1Metric", "description": "The metric config." } }, "id": "GoogleCloudAiplatformV1beta1EvaluationRunMetric", "type": "object" }, "GoogleCloudAiplatformV1beta1SearchExamplesResponse": { "id": "GoogleCloudAiplatformV1beta1SearchExamplesResponse", "type": "object", "description": "Response message for ExampleStoreService.SearchExamples.", "properties": { "results": { "description": "The results of searching for similar examples.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SearchExamplesResponseSimilarExample" } } } }, "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValues": { "id": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValues", "type": "object", "properties": { "features": { "description": "List of features to write.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeature" } }, "dataKey": { "description": "The data key.", "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKey" } }, "description": "A data key and associated feature values to write to the feature view." }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame": { "properties": { "xMax": { "type": "number", "format": "float", "description": "The rightmost coordinate of the bounding box." }, "xMin": { "format": "float", "description": "The leftmost coordinate of the bounding box.", "type": "number" }, "yMax": { "description": "The bottommost coordinate of the bounding box.", "format": "float", "type": "number" }, "timeOffset": { "type": "string", "format": "google-duration", "description": "A time (frame) of a video in which the object has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with \"s\" appended at the end." }, "yMin": { "description": "The topmost coordinate of the bounding box.", "format": "float", "type": "number" } }, "description": "The fields `xMin`, `xMax`, `yMin`, and `yMax` refer to a bounding box, i.e. the rectangle over the video frame pinpointing the found AnnotationSpec. The coordinates are relative to the frame size, and the point 0,0 is in the top left of the frame.", "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageSegmentationPredictionParams": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageSegmentationPredictionParams", "type": "object", "properties": { "confidenceThreshold": { "format": "float", "description": "When the model predicts category of pixels of the image, it will only provide predictions for pixels that it is at least this much confident about. All other pixels will be classified as background. Default value is 0.5.", "type": "number" } }, "description": "Prediction model parameters for Image Segmentation." }, "GoogleCloudAiplatformV1beta1FeatureValue": { "id": "GoogleCloudAiplatformV1beta1FeatureValue", "type": "object", "description": "Value for a feature.", "properties": { "boolArrayValue": { "$ref": "GoogleCloudAiplatformV1beta1BoolArray", "description": "A list of bool type feature value." }, "int64ArrayValue": { "description": "A list of int64 type feature value.", "$ref": "GoogleCloudAiplatformV1beta1Int64Array" }, "stringArrayValue": { "$ref": "GoogleCloudAiplatformV1beta1StringArray", "description": "A list of string type feature value." }, "doubleValue": { "description": "Double type feature value.", "format": "double", "type": "number" }, "doubleArrayValue": { "$ref": "GoogleCloudAiplatformV1beta1DoubleArray", "description": "A list of double type feature value." }, "stringValue": { "description": "String feature value.", "type": "string" }, "bytesValue": { "type": "string", "format": "byte", "description": "Bytes feature value." }, "structValue": { "description": "A struct type feature value.", "$ref": "GoogleCloudAiplatformV1beta1StructValue" }, "metadata": { "description": "Metadata of feature value.", "$ref": "GoogleCloudAiplatformV1beta1FeatureValueMetadata" }, "boolValue": { "description": "Bool type feature value.", "type": "boolean" }, "int64Value": { "type": "string", "description": "Int64 feature value.", "format": "int64" } } }, "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoObjectTrackingMetrics": { "id": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoObjectTrackingMetrics", "type": "object", "properties": { "boundingBoxMeanAveragePrecision": { "type": "number", "format": "float", "description": "The single metric for bounding boxes evaluation: the `meanAveragePrecision` averaged over all `boundingBoxMetrics`." }, "evaluatedFrameCount": { "format": "int32", "description": "UNIMPLEMENTED. The number of video frames used to create this evaluation.", "type": "integer" }, "trackMetrics": { "description": "UNIMPLEMENTED. The tracks match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetrics" } }, "trackMeanAveragePrecision": { "type": "number", "format": "float", "description": "UNIMPLEMENTED. The single metric for tracks accuracy evaluation: the `meanAveragePrecision` averaged over all `trackMetrics`." }, "trackMeanMismatchRate": { "type": "number", "format": "float", "description": "UNIMPLEMENTED. The single metric for tracking consistency evaluation: the `meanMismatchRate` averaged over all `trackMetrics`." }, "trackMeanBoundingBoxIou": { "type": "number", "format": "float", "description": "UNIMPLEMENTED. The single metric for tracks bounding box iou evaluation: the `meanBoundingBoxIou` averaged over all `trackMetrics`." }, "evaluatedBoundingBoxCount": { "type": "integer", "description": "UNIMPLEMENTED. The total number of bounding boxes (i.e. summed over all frames) the ground truth used to create this evaluation had.", "format": "int32" }, "boundingBoxMetrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetrics" }, "description": "The bounding boxes match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair." }, "evaluatedTrackCount": { "type": "integer", "format": "int32", "description": "UNIMPLEMENTED. The total number of tracks (i.e. as seen across all frames) the ground truth used to create this evaluation had." } }, "description": "Model evaluation metrics for video object tracking problems. Evaluates prediction quality of both labeled bounding boxes and labeled tracks (i.e. series of bounding boxes sharing same label and instance ID)." }, "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfigScaling": { "description": "Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).", "properties": { "maxNodeCount": { "type": "integer", "description": "The maximum number of nodes to scale up to. Must be greater than min_node_count, and less than or equal to 10 times of 'min_node_count'.", "format": "int32" }, "cpuUtilizationTarget": { "type": "integer", "description": "Optional. The cpu utilization that the Autoscaler should be trying to achieve. This number is on a scale from 0 (no utilization) to 100 (total utilization), and is limited between 10 and 80. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set or set to 0, default to 50.", "format": "int32" }, "minNodeCount": { "format": "int32", "description": "Required. The minimum number of nodes to scale down to. Must be greater than or equal to 1.", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfigScaling", "type": "object" }, "GoogleCloudAiplatformV1beta1PauseModelDeploymentMonitoringJobRequest": { "properties": {}, "description": "Request message for JobService.PauseModelDeploymentMonitoringJob.", "id": "GoogleCloudAiplatformV1beta1PauseModelDeploymentMonitoringJobRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata": { "id": "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata", "type": "object", "properties": { "promptTokenCount": { "type": "integer", "format": "int32", "description": "The total number of tokens in the prompt. This includes any text, images, or other media provided in the request. When `cached_content` is set, this also includes the number of tokens in the cached content." }, "totalTokenCount": { "type": "integer", "description": "The total number of tokens for the entire request. This is the sum of `prompt_token_count`, `candidates_token_count`, `tool_use_prompt_token_count`, and `thoughts_token_count`.", "format": "int32" }, "candidatesTokenCount": { "type": "integer", "format": "int32", "description": "The total number of tokens in the generated candidates." }, "toolUsePromptTokensDetails": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" }, "readOnly": true, "description": "Output only. A detailed breakdown by modality of the token counts from the results of tool executions, which are provided back to the model as input." }, "candidatesTokensDetails": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" }, "readOnly": true, "description": "Output only. A detailed breakdown of the token count for each modality in the generated candidates." }, "thoughtsTokenCount": { "type": "integer", "readOnly": true, "description": "Output only. The number of tokens that were part of the model's generated \"thoughts\" output, if applicable.", "format": "int32" }, "promptTokensDetails": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" }, "readOnly": true, "description": "Output only. A detailed breakdown of the token count for each modality in the prompt." }, "toolUsePromptTokenCount": { "type": "integer", "readOnly": true, "description": "Output only. The number of tokens in the results from tool executions, which are provided back to the model as input, if applicable.", "format": "int32" }, "cacheTokensDetails": { "description": "Output only. A detailed breakdown of the token count for each modality in the cached content.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" } }, "trafficType": { "type": "string", "enumDescriptions": [ "Unspecified request traffic type.", "The request was processed using Pay-As-You-Go quota.", "Type for Priority Pay-As-You-Go traffic.", "Type for Flex traffic.", "Type for Provisioned Throughput traffic." ], "readOnly": true, "description": "Output only. The traffic type for this request.", "enum": [ "TRAFFIC_TYPE_UNSPECIFIED", "ON_DEMAND", "ON_DEMAND_PRIORITY", "ON_DEMAND_FLEX", "PROVISIONED_THROUGHPUT" ] }, "cachedContentTokenCount": { "format": "int32", "description": "Output only. The number of tokens in the cached content that was used for this request.", "readOnly": true, "type": "integer" } }, "description": "Usage metadata about the content generation request and response. This message provides a detailed breakdown of token usage and other relevant metrics." }, "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectMemoriesSource": { "id": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectMemoriesSource", "type": "object", "description": "Defines a direct source of memories that should be uploaded to Memory Bank with consolidation.", "properties": { "directMemories": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectMemoriesSourceDirectMemory" }, "description": "Required. The direct memories to upload to Memory Bank. At most 5 direct memories are allowed per request." } } }, "GoogleCloudAiplatformV1beta1LossAnalysisConfig": { "description": "Configuration for the loss analysis job.", "properties": { "candidate": { "description": "Required. The candidate model/agent to analyze (e.g., \"gemini-3.0-pro\"). This targets the specific CandidateResult within the EvaluationResult.", "type": "string" }, "metric": { "description": "Required. The metric to analyze (e.g., \"tool_use_quality\"). This filters the EvaluationItems in the EvalSet to only those where EvaluationResult.metric matches this value.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1LossAnalysisConfig", "type": "object" }, "CloudAiLargeModelsVisionGenerateVideoResponse": { "description": "Generate video response.", "properties": { "raiMediaFilteredReasons": { "description": "Returns rai failure reasons if any.", "type": "array", "items": { "type": "string" } }, "generatedSamples": { "description": "The generates samples.", "type": "array", "items": { "$ref": "CloudAiLargeModelsVisionMedia" } }, "raiMediaFilteredCount": { "type": "integer", "format": "int32", "description": "Returns if any videos were filtered due to RAI policies." }, "videos": { "type": "array", "items": { "$ref": "CloudAiLargeModelsVisionGenerateVideoResponseVideo" }, "description": "List of videos, used to align naming with the external response." } }, "id": "CloudAiLargeModelsVisionGenerateVideoResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1PublisherModelParent": { "description": "The information about the parent of a model.", "properties": { "reference": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelResourceReference", "description": "Optional. The Google Cloud resource name or the URI reference." }, "displayName": { "description": "Required. The display name of the parent. E.g., LaMDA, T5, Vision API, Natural Language API.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1PublisherModelParent", "type": "object" }, "GoogleCloudAiplatformV1beta1GroundednessSpec": { "id": "GoogleCloudAiplatformV1beta1GroundednessSpec", "type": "object", "properties": { "version": { "description": "Optional. Which version to use for evaluation.", "format": "int32", "type": "integer" } }, "description": "Spec for groundedness metric." }, "GoogleCloudAiplatformV1beta1DirectPredictResponse": { "description": "Response message for PredictionService.DirectPredict.", "properties": { "outputs": { "description": "The prediction output.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tensor" } }, "parameters": { "$ref": "GoogleCloudAiplatformV1beta1Tensor", "description": "The parameters that govern the prediction." } }, "id": "GoogleCloudAiplatformV1beta1DirectPredictResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationInstanceMapInstance": { "description": "Instance data specified as a map.", "properties": { "mapInstance": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData" }, "description": "Optional. Map of instance data." } }, "id": "GoogleCloudAiplatformV1beta1EvaluationInstanceMapInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1DeployedIndex": { "id": "GoogleCloudAiplatformV1beta1DeployedIndex", "type": "object", "description": "A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes.", "properties": { "automaticResources": { "$ref": "GoogleCloudAiplatformV1beta1AutomaticResources", "description": "Optional. A description of resources that the DeployedIndex uses, which to large degree are decided by Vertex AI, and optionally allows only a modest additional configuration. If min_replica_count is not set, the default value is 2 (we don't provide SLA when min_replica_count=1). If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000." }, "enableDatapointUpsertLogging": { "description": "Optional. If true, logs to Cloud Logging errors relating to datapoint upserts. Under normal operation conditions, these log entries should be very rare. However, if incompatible datapoint updates are being uploaded to an index, a high volume of log entries may be generated in a short period of time. Note that logs may incur a cost, especially if the deployed index receives a high volume of datapoint upserts. Estimate your costs before enabling this option.", "type": "boolean" }, "privateEndpoints": { "description": "Output only. Provides paths for users to send requests directly to the deployed index services running on Cloud via private services access. This field is populated if network is configured.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1IndexPrivateEndpoints" }, "createTime": { "description": "Output only. Timestamp when the DeployedIndex was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "dedicatedResources": { "$ref": "GoogleCloudAiplatformV1beta1DedicatedResources", "description": "Optional. A description of resources that are dedicated to the DeployedIndex, and that need a higher degree of manual configuration. The field min_replica_count must be set to a value strictly greater than 0, or else validation will fail. We don't provide SLA when min_replica_count=1. If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000. Available machine types for SMALL shard: e2-standard-2 and all machine types available for MEDIUM and LARGE shard. Available machine types for MEDIUM shard: e2-standard-16 and all machine types available for LARGE shard. Available machine types for LARGE shard: e2-highmem-16, n2d-standard-32. n1-standard-16 and n1-standard-32 are still available, but we recommend e2-standard-16 and e2-highmem-16 for cost efficiency." }, "index": { "description": "Required. The name of the Index this is the deployment of. We may refer to this Index as the DeployedIndex's \"original\" Index.", "type": "string" }, "deployedIndexAuthConfig": { "description": "Optional. If set, the authentication is enabled for the private endpoint.", "$ref": "GoogleCloudAiplatformV1beta1DeployedIndexAuthConfig" }, "reservedIpRanges": { "type": "array", "items": { "type": "string" }, "description": "Optional. A list of reserved ip ranges under the VPC network that can be used for this DeployedIndex. If set, we will deploy the index within the provided ip ranges. Otherwise, the index might be deployed to any ip ranges under the provided VPC network. The value should be the name of the address (https://cloud.google.com/compute/docs/reference/rest/v1/addresses) Example: ['vertex-ai-ip-range']. For more information about subnets and network IP ranges, please see https://cloud.google.com/vpc/docs/subnets#manually_created_subnet_ip_ranges." }, "deploymentTier": { "description": "Optional. The deployment tier that the index is deployed to. DEPLOYMENT_TIER_UNSPECIFIED will use a system-chosen default tier.", "enum": [ "DEPLOYMENT_TIER_UNSPECIFIED", "STORAGE" ], "type": "string", "enumDescriptions": [ "Default deployment tier.", "Optimized for costs." ] }, "indexSyncTime": { "type": "string", "readOnly": true, "description": "Output only. The DeployedIndex may depend on various data on its original Index. Additionally when certain changes to the original Index are being done (e.g. when what the Index contains is being changed) the DeployedIndex may be asynchronously updated in the background to reflect these changes. If this timestamp's value is at least the Index.update_time of the original Index, it means that this DeployedIndex and the original Index are in sync. If this timestamp is older, then to see which updates this DeployedIndex already contains (and which it does not), one must list the operations that are running on the original Index. Only the successfully completed Operations with update_time equal or before this sync time are contained in this DeployedIndex.", "format": "google-datetime" }, "deploymentGroup": { "description": "Optional. The deployment group can be no longer than 64 characters (eg: 'test', 'prod'). If not set, we will use the 'default' deployment group. Creating `deployment_groups` with `reserved_ip_ranges` is a recommended practice when the peered network has multiple peering ranges. This creates your deployments from predictable IP spaces for easier traffic administration. Also, one deployment_group (except 'default') can only be used with the same reserved_ip_ranges which means if the deployment_group has been used with reserved_ip_ranges: [a, b, c], using it with [a, b] or [d, e] is disallowed. Note: we only support up to 5 deployment groups(not including 'default').", "type": "string" }, "id": { "description": "Required. The user specified ID of the DeployedIndex. The ID can be up to 128 characters long and must start with a letter and only contain letters, numbers, and underscores. The ID must be unique within the project it is created in.", "type": "string" }, "displayName": { "description": "The display name of the DeployedIndex. If not provided upon creation, the Index's display_name is used.", "type": "string" }, "enableAccessLogging": { "description": "Optional. If true, private endpoint's access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each MatchRequest. Note that logs may incur a cost, especially if the deployed index receives a high queries per second rate (QPS). Estimate your costs before enabling this option.", "type": "boolean" }, "pscAutomationConfigs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PSCAutomationConfig" }, "description": "Optional. If set for PSC deployed index, PSC connection will be automatically created after deployment is done and the endpoint information is populated in private_endpoints.psc_automated_endpoints." } } }, "GoogleCloudAiplatformV1beta1PurgeContextsResponse": { "id": "GoogleCloudAiplatformV1beta1PurgeContextsResponse", "type": "object", "properties": { "purgeSample": { "description": "A sample of the Context names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer).", "type": "array", "items": { "type": "string" } }, "purgeCount": { "description": "The number of Contexts that this request deleted (or, if `force` is false, the number of Contexts that will be deleted). This can be an estimate.", "format": "int64", "type": "string" } }, "description": "Response message for MetadataService.PurgeContexts." }, "GoogleCloudAiplatformV1beta1SmoothGradConfig": { "id": "GoogleCloudAiplatformV1beta1SmoothGradConfig", "type": "object", "description": "Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf", "properties": { "featureNoiseSigma": { "description": "This is similar to noise_sigma, but provides additional flexibility. A separate noise sigma can be provided for each feature, which is useful if their distributions are different. No noise is added to features that are not set. If this field is unset, noise_sigma will be used for all features.", "$ref": "GoogleCloudAiplatformV1beta1FeatureNoiseSigma" }, "noiseSigma": { "format": "float", "description": "This is a single float value and will be used to add noise to all the features. Use this field when all features are normalized to have the same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where features are normalized to have 0-mean and 1-variance. Learn more about [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization). For best results the recommended value is about 10% - 20% of the standard deviation of the input feature. Refer to section 3.2 of the SmoothGrad paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1. If the distribution is different per feature, set feature_noise_sigma instead for each feature.", "type": "number" }, "noisySampleCount": { "description": "The number of gradient samples to use for approximation. The higher this number, the more accurate the gradient is, but the runtime complexity increases by this factor as well. Valid range of its value is [1, 50]. Defaults to 3.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1beta1ReportRuntimeEventResponse": { "description": "Response message for NotebookInternalService.ReportRuntimeEvent.", "properties": { "idleShutdownMessage": { "description": "If the idle shutdown is blocked by CP, CP will send the block message. Otherwise, this field is not set.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ReportRuntimeEventResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1EnableModelRequest": { "description": "Request message for ModelGardenService.EnableModel.", "properties": { "service": { "description": "Optional. The ID links the Marketplace listing to the underlying Vertex AI model endpoint. Format: `services/{service_id}` Format: `services/{service_id}`", "type": "string", "deprecated": true } }, "id": "GoogleCloudAiplatformV1beta1EnableModelRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetailProcessedDataset": { "properties": { "location": { "description": "Actual data location of the processed dataset.", "type": "string" }, "timeRange": { "description": "Dataset time range information if any.", "$ref": "GoogleTypeInterval" } }, "description": "Processed dataset information.", "id": "GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetailProcessedDataset", "type": "object" }, "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponse": { "properties": { "monthlyUsageData": { "description": "Maps year-month (YYYYMM) string to per month usage data.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerMonthUsageData" } } }, "description": "Response message for TensorboardService.ReadTensorboardUsage.", "id": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ListRagFilesResponse": { "id": "GoogleCloudAiplatformV1beta1ListRagFilesResponse", "type": "object", "properties": { "ragFiles": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1RagFile" }, "description": "List of RagFiles in the requested page." }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListRagFilesRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for VertexRagDataService.ListRagFiles." }, "GoogleCloudAiplatformV1beta1TrainingPipeline": { "properties": { "name": { "description": "Output only. Resource name of the TrainingPipeline.", "readOnly": true, "type": "string" }, "inputDataConfig": { "$ref": "GoogleCloudAiplatformV1beta1InputDataConfig", "description": "Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration." }, "state": { "enum": [ "PIPELINE_STATE_UNSPECIFIED", "PIPELINE_STATE_QUEUED", "PIPELINE_STATE_PENDING", "PIPELINE_STATE_RUNNING", "PIPELINE_STATE_SUCCEEDED", "PIPELINE_STATE_FAILED", "PIPELINE_STATE_CANCELLING", "PIPELINE_STATE_CANCELLED", "PIPELINE_STATE_PAUSED" ], "description": "Output only. The detailed state of the pipeline.", "readOnly": true, "type": "string", "enumDescriptions": [ "The pipeline state is unspecified.", "The pipeline has been created or resumed, and processing has not yet begun.", "The service is preparing to run the pipeline.", "The pipeline is in progress.", "The pipeline completed successfully.", "The pipeline failed.", "The pipeline is being cancelled. From this state, the pipeline may only go to either PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED.", "The pipeline has been cancelled.", "The pipeline has been stopped, and can be resumed." ] }, "startTime": { "format": "google-datetime", "description": "Output only. Time when the TrainingPipeline for the first time entered the `PIPELINE_STATE_RUNNING` state.", "readOnly": true, "type": "string" }, "modelId": { "description": "Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen.", "type": "string" }, "trainingTaskInputs": { "description": "Required. The training task's parameter(s), as specified in the training_task_definition's `inputs`.", "type": "any" }, "modelToUpload": { "$ref": "GoogleCloudAiplatformV1beta1Model", "description": "Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's training_task_definition should make clear whether this Model description should be populated, and if there are any special requirements regarding how it should be filled. If nothing is mentioned in the training_task_definition, then it should be assumed that this field should not be filled and the training task either uploads the Model without a need of this information, or that training task does not support uploading a Model as part of the pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and the trained Model had been uploaded into Vertex AI, then the model_to_upload's resource name is populated. The Model is always uploaded into the Project and Location in which this pipeline is." }, "displayName": { "description": "Required. The user-defined name of this TrainingPipeline.", "type": "string" }, "trainingTaskMetadata": { "description": "Output only. The metadata information as specified in the training_task_definition's `metadata`. This metadata is an auxiliary runtime and final information about the training task. While the pipeline is running this information is populated only at a best effort basis. Only present if the pipeline's training_task_definition contains `metadata` object.", "readOnly": true, "type": "any" }, "endTime": { "type": "string", "readOnly": true, "description": "Output only. Time when the TrainingPipeline entered any of the following states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`, `PIPELINE_STATE_CANCELLED`.", "format": "google-datetime" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels." }, "error": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. Only populated when the pipeline's state is `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`." }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Time when the TrainingPipeline was most recently updated.", "format": "google-datetime" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the TrainingPipeline was created." }, "parentModel": { "description": "Optional. When specify this field, the `model_to_upload` will not be uploaded as a new model, instead, it will become a new version of this `parent_model`.", "type": "string" }, "trainingTaskDefinition": { "description": "Required. A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.", "type": "string" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately." } }, "description": "The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.", "id": "GoogleCloudAiplatformV1beta1TrainingPipeline", "type": "object" }, "GoogleCloudAiplatformV1beta1IndexDatapoint": { "id": "GoogleCloudAiplatformV1beta1IndexDatapoint", "type": "object", "properties": { "datapointId": { "description": "Required. Unique identifier of the datapoint.", "type": "string" }, "restricts": { "description": "Optional. List of Restrict of the datapoint, used to perform \"restricted searches\" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1IndexDatapointRestriction" } }, "embeddingMetadata": { "description": "Optional. The key-value map of additional metadata for the datapoint.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "sparseEmbedding": { "description": "Optional. Feature embedding vector for sparse index.", "$ref": "GoogleCloudAiplatformV1beta1IndexDatapointSparseEmbedding" }, "numericRestricts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1IndexDatapointNumericRestriction" }, "description": "Optional. List of Restrict of the datapoint, used to perform \"restricted searches\" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons." }, "featureVector": { "type": "array", "items": { "type": "number", "format": "float" }, "description": "Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions]." }, "crowdingTag": { "$ref": "GoogleCloudAiplatformV1beta1IndexDatapointCrowdingTag", "description": "Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query." } }, "description": "A datapoint of Index." }, "GoogleCloudAiplatformV1beta1ImportExtensionOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1ImportExtensionOperationMetadata", "type": "object", "description": "Details of ExtensionRegistryService.ImportExtension operation.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata", "description": "The common part of the operation metadata." } } }, "GoogleCloudAiplatformV1beta1NearestNeighborQueryNumericFilter": { "properties": { "valueFloat": { "description": "float value type.", "format": "float", "type": "number" }, "name": { "description": "Required. Column name in BigQuery that used as filters.", "type": "string" }, "valueInt": { "type": "string", "format": "int64", "description": "int value type." }, "op": { "type": "string", "enumDescriptions": [ "Unspecified operator.", "Entities are eligible if their value is \u003c the query's.", "Entities are eligible if their value is \u003c= the query's.", "Entities are eligible if their value is == the query's.", "Entities are eligible if their value is \u003e= the query's.", "Entities are eligible if their value is \u003e the query's.", "Entities are eligible if their value is != the query's." ], "enum": [ "OPERATOR_UNSPECIFIED", "LESS", "LESS_EQUAL", "EQUAL", "GREATER_EQUAL", "GREATER", "NOT_EQUAL" ], "description": "Optional. This MUST be specified for queries and must NOT be specified for database points." }, "valueDouble": { "type": "number", "description": "double value type.", "format": "double" } }, "description": "Numeric filter is used to search a subset of the entities by using boolean rules on numeric columns. For example: Database Point 0: {name: \"a\" value_int: 42} {name: \"b\" value_float: 1.0} Database Point 1: {name: \"a\" value_int: 10} {name: \"b\" value_float: 2.0} Database Point 2: {name: \"a\" value_int: -1} {name: \"b\" value_float: 3.0} Query: {name: \"a\" value_int: 12 operator: LESS} // Matches Point 1, 2 {name: \"b\" value_float: 2.0 operator: EQUAL} // Matches Point 1", "id": "GoogleCloudAiplatformV1beta1NearestNeighborQueryNumericFilter", "type": "object" }, "GoogleCloudAiplatformV1beta1Study": { "properties": { "studySpec": { "$ref": "GoogleCloudAiplatformV1beta1StudySpec", "description": "Required. Configuration of the Study." }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time at which the study was created." }, "displayName": { "description": "Required. Describes the Study, default value is empty string.", "type": "string" }, "inactiveReason": { "readOnly": true, "type": "string", "description": "Output only. A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED." }, "name": { "type": "string", "readOnly": true, "description": "Output only. The name of a study. The study's globally unique identifier. Format: `projects/{project}/locations/{location}/studies/{study}`" }, "state": { "enum": [ "STATE_UNSPECIFIED", "ACTIVE", "INACTIVE", "COMPLETED" ], "description": "Output only. The detailed state of a Study.", "readOnly": true, "type": "string", "enumDescriptions": [ "The study state is unspecified.", "The study is active.", "The study is stopped due to an internal error.", "The study is done when the service exhausts the parameter search space or max_trial_count is reached." ] } }, "description": "A message representing a Study.", "id": "GoogleCloudAiplatformV1beta1Study", "type": "object" }, "GoogleCloudAiplatformV1beta1ListModelVersionsResponse": { "id": "GoogleCloudAiplatformV1beta1ListModelVersionsResponse", "type": "object", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListModelVersionsRequest.page_token to obtain that page.", "type": "string" }, "models": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Model" }, "description": "List of Model versions in the requested page. In the returned Model name field, version ID instead of regvision tag will be included." } }, "description": "Response message for ModelService.ListModelVersions" }, "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataResponse": { "properties": {}, "description": "Response message for TensorboardService.WriteTensorboardRunData.", "id": "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1VoiceConfig": { "id": "GoogleCloudAiplatformV1beta1VoiceConfig", "type": "object", "description": "Configuration for a voice.", "properties": { "prebuiltVoiceConfig": { "$ref": "GoogleCloudAiplatformV1beta1PrebuiltVoiceConfig", "description": "The configuration for a prebuilt voice." }, "replicatedVoiceConfig": { "description": "Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.", "$ref": "GoogleCloudAiplatformV1beta1ReplicatedVoiceConfig" } } }, "GoogleCloudAiplatformV1beta1GroundingChunkMapsRoute": { "id": "GoogleCloudAiplatformV1beta1GroundingChunkMapsRoute", "type": "object", "properties": { "duration": { "type": "string", "description": "The total duration of the route.", "format": "google-duration" }, "distanceMeters": { "description": "The total distance of the route, in meters.", "format": "int32", "type": "integer" }, "encodedPolyline": { "description": "An encoded polyline of the route. See https://developers.google.com/maps/documentation/utilities/polylinealgorithm", "type": "string" } }, "description": "Route information from Google Maps." }, "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig": { "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig", "type": "object", "properties": { "annotatedDataset": { "description": "Required. Full resource name of data labeling AnnotatedDataset. Format: `projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}`.", "type": "string" } }, "description": "Config for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery." }, "GoogleCloudAiplatformV1beta1ListBatchPredictionJobsResponse": { "id": "GoogleCloudAiplatformV1beta1ListBatchPredictionJobsResponse", "type": "object", "description": "Response message for JobService.ListBatchPredictionJobs", "properties": { "batchPredictionJobs": { "description": "List of BatchPredictionJobs in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJob" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListBatchPredictionJobsRequest.page_token to obtain that page.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentConfigTools": { "id": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentConfigTools", "type": "object", "properties": { "tool": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" }, "description": "Optional. List of tools: each tool can have multiple function declarations." } }, "description": "Represents a list of tools for an agent." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs", "type": "object", "properties": { "hierarchyConfig": { "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig" }, "timeSeriesAttributeColumns": { "type": "array", "items": { "type": "string" }, "description": "Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color." }, "exportEvaluatedDataItemsConfig": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig", "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed." }, "optimizationObjective": { "description": "Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). * \"minimize-mae\" - Minimize mean-absolute error (MAE). * \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE). * \"minimize-rmspe\" - Minimize root-mean-squared percentage error (RMSPE). * \"minimize-wape-mae\" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * \"minimize-quantile-loss\" - Minimize the quantile loss at the quantiles defined in `quantiles`. * \"minimize-mape\" - Minimize the mean absolute percentage error.", "type": "string" }, "timeSeriesIdentifierColumn": { "description": "The name of the column that identifies the time series.", "type": "string" }, "timeColumn": { "description": "The name of the column that identifies time order in the time series. This column must be available at forecast.", "type": "string" }, "validationOptions": { "description": "Validation options for the data validation component. The available options are: * \"fail-pipeline\" - default, will validate against the validation and fail the pipeline if it fails. * \"ignore-validation\" - ignore the results of the validation and continue", "type": "string" }, "transformations": { "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation" } }, "quantiles": { "type": "array", "items": { "format": "double", "type": "number" }, "description": "Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique." }, "unavailableAtForecastColumns": { "description": "Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day.", "type": "array", "items": { "type": "string" } }, "dataGranularity": { "description": "Expected difference in time granularity between rows in the data.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity" }, "windowConfig": { "description": "Config containing strategy for generating sliding windows.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig" }, "additionalExperiments": { "description": "Additional experiment flags for the time series forcasting training.", "type": "array", "items": { "type": "string" } }, "targetColumn": { "description": "The name of the column that the Model is to predict values for. This column must be unavailable at forecast.", "type": "string" }, "trainBudgetMilliNodeHours": { "type": "string", "format": "int64", "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive." }, "weightColumn": { "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1. This column must be available at forecast.", "type": "string" }, "forecastHorizon": { "format": "int64", "description": "The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field.", "type": "string" }, "contextWindow": { "type": "string", "description": "The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field.", "format": "int64" }, "availableAtForecastColumns": { "type": "array", "items": { "type": "string" }, "description": "Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day." }, "holidayRegions": { "type": "array", "items": { "type": "string" }, "description": "The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option." } } }, "GoogleCloudAiplatformV1beta1FeatureViewBigQuerySource": { "properties": { "entityIdColumns": { "description": "Required. Columns to construct entity_id / row keys.", "type": "array", "items": { "type": "string" } }, "uri": { "description": "Required. The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1FeatureViewBigQuerySource", "type": "object" }, "GoogleCloudAiplatformV1beta1ExampleStoreConfig": { "id": "GoogleCloudAiplatformV1beta1ExampleStoreConfig", "type": "object", "description": "Configuration for the Example Store.", "properties": { "vertexEmbeddingModel": { "description": "Required. The embedding model to be used for vector embedding. Immutable. Supported models: * \"text-embedding-005\" * \"text-multilingual-embedding-002\"", "type": "string" } } }, "GoogleCloudAiplatformV1beta1UrlContext": { "description": "Tool to support URL context.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1UrlContext", "type": "object" }, "GoogleCloudAiplatformV1beta1ListReasoningEnginesResponse": { "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListReasoningEnginesRequest.page_token to obtain that page.", "type": "string" }, "reasoningEngines": { "description": "List of ReasoningEngines in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngine" } } }, "description": "Response message for ReasoningEngineService.ListReasoningEngines", "id": "GoogleCloudAiplatformV1beta1ListReasoningEnginesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentSpecCodeExecutionEnvironment": { "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSpecCodeExecutionEnvironment", "type": "object", "properties": { "machineConfig": { "enum": [ "MACHINE_CONFIG_UNSPECIFIED", "MACHINE_CONFIG_VCPU4_RAM4GIB" ], "description": "The machine config of the code execution environment.", "type": "string", "enumDescriptions": [ "The default value: milligcu 2000, memory 1.5Gib", "The default value: milligcu 4000, memory 4 Gib" ] }, "codeLanguage": { "type": "string", "enumDescriptions": [ "The default value. This value is unused.", "The coding language is Python.", "The coding language is JavaScript." ], "description": "The coding language supported in this environment.", "enum": [ "LANGUAGE_UNSPECIFIED", "LANGUAGE_PYTHON", "LANGUAGE_JAVASCRIPT" ] } }, "description": "The code execution environment with customized settings." }, "GoogleIamV1GetIamPolicyRequest": { "id": "GoogleIamV1GetIamPolicyRequest", "type": "object", "properties": { "options": { "$ref": "GoogleIamV1GetPolicyOptions", "description": "OPTIONAL: A `GetPolicyOptions` object for specifying options to `GetIamPolicy`." } }, "description": "Request message for `GetIamPolicy` method." }, "GoogleCloudAiplatformV1beta1Examples": { "properties": { "exampleGcsSource": { "$ref": "GoogleCloudAiplatformV1beta1ExamplesExampleGcsSource", "description": "The Cloud Storage input instances." }, "presets": { "description": "Simplified preset configuration, which automatically sets configuration values based on the desired query speed-precision trade-off and modality.", "$ref": "GoogleCloudAiplatformV1beta1Presets" }, "nearestNeighborSearchConfig": { "description": "The full configuration for the generated index, the semantics are the same as metadata and should match [NearestNeighborSearchConfig](https://cloud.google.com/vertex-ai/docs/explainable-ai/configuring-explanations-example-based#nearest-neighbor-search-config).", "type": "any" }, "gcsSource": { "$ref": "GoogleCloudAiplatformV1beta1GcsSource", "description": "The Cloud Storage locations that contain the instances to be indexed for approximate nearest neighbor search." }, "neighborCount": { "type": "integer", "description": "The number of neighbors to return when querying for examples.", "format": "int32" } }, "description": "Example-based explainability that returns the nearest neighbors from the provided dataset.", "id": "GoogleCloudAiplatformV1beta1Examples", "type": "object" }, "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution": { "id": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution", "type": "object", "properties": { "p5": { "format": "double", "description": "Output only. The 5th percentile of the values in the population.", "readOnly": true, "type": "number" }, "median": { "readOnly": true, "type": "number", "format": "double", "description": "Output only. The median of the values in the population." }, "p95": { "readOnly": true, "type": "number", "format": "double", "description": "Output only. The 95th percentile of the values in the population." }, "buckets": { "description": "Output only. Defines the histogram bucket.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistributionDatasetBucket" }, "readOnly": true }, "min": { "format": "double", "description": "Output only. The minimum of the population values.", "readOnly": true, "type": "number" }, "billableSum": { "description": "Output only. Sum of a given population of values that are billable.", "format": "int64", "type": "string", "readOnly": true }, "mean": { "description": "Output only. The arithmetic mean of the values in the population.", "format": "double", "type": "number", "readOnly": true }, "sum": { "format": "int64", "description": "Output only. Sum of a given population of values.", "readOnly": true, "type": "string" }, "max": { "description": "Output only. The maximum of the population values.", "format": "double", "type": "number", "readOnly": true } }, "description": "Dataset distribution for Supervised Tuning." }, "GoogleCloudAiplatformV1beta1ProbeHttpGetAction": { "id": "GoogleCloudAiplatformV1beta1ProbeHttpGetAction", "type": "object", "description": "HttpGetAction describes an action based on HTTP Get requests.", "properties": { "path": { "description": "Path to access on the HTTP server.", "type": "string" }, "host": { "description": "Host name to connect to, defaults to the model serving container's IP. You probably want to set \"Host\" in httpHeaders instead.", "type": "string" }, "scheme": { "description": "Scheme to use for connecting to the host. Defaults to HTTP. Acceptable values are \"HTTP\" or \"HTTPS\".", "type": "string" }, "port": { "type": "integer", "description": "Number of the port to access on the container. Number must be in the range 1 to 65535.", "format": "int32" }, "httpHeaders": { "description": "Custom headers to set in the request. HTTP allows repeated headers.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ProbeHttpHeader" } } } }, "GoogleCloudAiplatformV1beta1PipelineTaskRerunConfig": { "id": "GoogleCloudAiplatformV1beta1PipelineTaskRerunConfig", "type": "object", "properties": { "taskName": { "description": "Optional. The name of the task.", "type": "string" }, "skipDownstreamTasks": { "description": "Optional. Whether to skip downstream tasks. Default value is False.", "type": "boolean" }, "taskId": { "type": "string", "description": "Optional. The system generated ID of the task. Retrieved from original run.", "format": "int64" }, "skipTask": { "description": "Optional. Whether to skip this task. Default value is False.", "type": "boolean" }, "inputs": { "$ref": "GoogleCloudAiplatformV1beta1PipelineTaskRerunConfigInputs", "description": "Optional. The runtime input of the task overridden by the user." } }, "description": "User provided rerun config to submit a rerun pipelinejob. This includes 1. Which task to rerun 2. User override input parameters and artifacts." }, "GoogleCloudAiplatformV1beta1EvaluatedAnnotation": { "id": "GoogleCloudAiplatformV1beta1EvaluatedAnnotation", "type": "object", "properties": { "type": { "type": "string", "enumDescriptions": [ "Invalid value.", "The EvaluatedAnnotation is a true positive. It has a prediction created by the Model and a ground truth Annotation which the prediction matches.", "The EvaluatedAnnotation is false positive. It has a prediction created by the Model which does not match any ground truth annotation.", "The EvaluatedAnnotation is false negative. It has a ground truth annotation which is not matched by any of the model created predictions." ], "readOnly": true, "description": "Output only. Type of the EvaluatedAnnotation.", "enum": [ "EVALUATED_ANNOTATION_TYPE_UNSPECIFIED", "TRUE_POSITIVE", "FALSE_POSITIVE", "FALSE_NEGATIVE" ] }, "explanations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EvaluatedAnnotationExplanation" }, "description": "Explanations of predictions. Each element of the explanations indicates the explanation for one explanation Method. The attributions list in the EvaluatedAnnotationExplanation.explanation object corresponds to the predictions list. For example, the second element in the attributions list explains the second element in the predictions list." }, "errorAnalysisAnnotations": { "description": "Annotations of model error analysis results.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotation" } }, "dataItemPayload": { "readOnly": true, "type": "any", "description": "Output only. The data item payload that the Model predicted this EvaluatedAnnotation on." }, "evaluatedDataItemViewId": { "type": "string", "readOnly": true, "description": "Output only. ID of the EvaluatedDataItemView under the same ancestor ModelEvaluation. The EvaluatedDataItemView consists of all ground truths and predictions on data_item_payload." }, "predictions": { "readOnly": true, "type": "array", "items": { "type": "any" }, "description": "Output only. The model predicted annotations. For true positive, there is one and only one prediction, which matches the only one ground truth annotation in ground_truths. For false positive, there is one and only one prediction, which doesn't match any ground truth annotation of the corresponding data_item_view_id. For false negative, there are zero or more predictions which are similar to the only ground truth annotation in ground_truths but not enough for a match. The schema of the prediction is stored in ModelEvaluation.annotation_schema_uri" }, "groundTruths": { "description": "Output only. The ground truth Annotations, i.e. the Annotations that exist in the test data the Model is evaluated on. For true positive, there is one and only one ground truth annotation, which matches the only prediction in predictions. For false positive, there are zero or more ground truth annotations that are similar to the only prediction in predictions, but not enough for a match. For false negative, there is one and only one ground truth annotation, which doesn't match any predictions created by the model. The schema of the ground truth is stored in ModelEvaluation.annotation_schema_uri", "readOnly": true, "type": "array", "items": { "type": "any" } } }, "description": "True positive, false positive, or false negative. EvaluatedAnnotation is only available under ModelEvaluationSlice with slice of `annotationSpec` dimension." }, "GoogleCloudAiplatformV1beta1MetadataSchema": { "description": "Instance of a general MetadataSchema.", "properties": { "name": { "description": "Output only. The resource name of the MetadataSchema.", "type": "string", "readOnly": true }, "schema": { "description": "Required. The raw YAML string representation of the MetadataSchema. The combination of [MetadataSchema.version] and the schema name given by `title` in [MetadataSchema.schema] must be unique within a MetadataStore. The schema is defined as an OpenAPI 3.0.2 [MetadataSchema Object](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.0.2.md#schemaObject)", "type": "string" }, "schemaType": { "enum": [ "METADATA_SCHEMA_TYPE_UNSPECIFIED", "ARTIFACT_TYPE", "EXECUTION_TYPE", "CONTEXT_TYPE" ], "description": "The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema.", "type": "string", "enumDescriptions": [ "Unspecified type for the MetadataSchema.", "A type indicating that the MetadataSchema will be used by Artifacts.", "A typee indicating that the MetadataSchema will be used by Executions.", "A state indicating that the MetadataSchema will be used by Contexts." ] }, "description": { "description": "Description of the Metadata Schema", "type": "string" }, "schemaVersion": { "description": "The version of the MetadataSchema. The version's format must match the following regular expression: `^[0-9]+.+.+$`, which would allow to order/compare different versions. Example: 1.0.0, 1.0.1, etc.", "type": "string" }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this MetadataSchema was created.", "format": "google-datetime" } }, "id": "GoogleCloudAiplatformV1beta1MetadataSchema", "type": "object" }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpec": { "description": "The specification of a Reasoning Engine deployment.", "properties": { "keepAliveProbe": { "$ref": "GoogleCloudAiplatformV1beta1KeepAliveProbe", "description": "Optional. Specifies the configuration for keep-alive probe. Contains configuration on a specified endpoint that a deployment host should use to keep the container alive based on the probe settings." }, "agentServerMode": { "type": "string", "enumDescriptions": [ "Unspecified agent server mode. Do not use.", "Stable agent server mode. This mode has everything stable and well-tested features agent engine offers.", "Experimental agent server mode. This mode contains experimental features." ], "description": "The agent server mode.", "enum": [ "AGENT_SERVER_MODE_UNSPECIFIED", "STABLE", "EXPERIMENTAL" ] }, "env": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EnvVar" }, "description": "Optional. Environment variables to be set with the Reasoning Engine deployment. The environment variables can be updated through the UpdateReasoningEngine API." }, "minInstances": { "description": "Optional. The minimum number of application instances that will be kept running at all times. Defaults to 1. Range: [0, 75].", "format": "int32", "type": "integer" }, "agentGatewayConfig": { "description": "Optional. Agent Gateway configuration for the Reasoning Engine deployment.", "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpecAgentGatewayConfig" }, "secretEnv": { "description": "Optional. Environment variables where the value is a secret in Cloud Secret Manager. To use this feature, add 'Secret Manager Secret Accessor' role (roles/secretmanager.secretAccessor) to AI Platform Reasoning Engine Service Agent.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SecretEnvVar" } }, "maxInstances": { "type": "integer", "format": "int32", "description": "Optional. The maximum number of application instances that can be launched to handle increased traffic. Defaults to 100. Range: [1, 1000]. If VPC-SC or PSC-I is enabled, the acceptable range is [1, 100]." }, "containerConcurrency": { "type": "integer", "description": "Optional. Concurrency for each container and agent server. Recommended value: 2 * cpu + 1. Defaults to 9.", "format": "int32" }, "pscInterfaceConfig": { "description": "Optional. Configuration for PSC-I.", "$ref": "GoogleCloudAiplatformV1beta1PscInterfaceConfig" }, "resourceLimits": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. Resource limits for each container. Only 'cpu' and 'memory' keys are supported. Defaults to {\"cpu\": \"4\", \"memory\": \"4Gi\"}. * The only supported values for CPU are '1', '2', '4', '6' and '8'. For more information, go to https://cloud.google.com/run/docs/configuring/cpu. * The only supported values for memory are '1Gi', '2Gi', ... '32 Gi'. * For required cpu on different memory values, go to https://cloud.google.com/run/docs/configuring/memory-limits" } }, "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1GroundednessInput": { "description": "Input for groundedness metric.", "properties": { "instance": { "description": "Required. Groundedness instance.", "$ref": "GoogleCloudAiplatformV1beta1GroundednessInstance" }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1GroundednessSpec", "description": "Required. Spec for groundedness metric." } }, "id": "GoogleCloudAiplatformV1beta1GroundednessInput", "type": "object" }, "GoogleCloudAiplatformV1beta1ResourceRuntime": { "properties": { "notebookRuntimeTemplate": { "type": "string", "readOnly": true, "deprecated": true, "description": "Output only. The resource name of NotebookRuntimeTemplate for the RoV Persistent Cluster The NotebokRuntimeTemplate is created in the same VPC (if set), and with the same Ray and Python version as the Persistent Cluster. Example: \"projects/1000/locations/us-central1/notebookRuntimeTemplates/abc123\"" }, "accessUris": { "readOnly": true, "type": "object", "additionalProperties": { "type": "string" }, "description": "Output only. URIs for user to connect to the Cluster. Example: { \"RAY_HEAD_NODE_INTERNAL_IP\": \"head-node-IP:10001\" \"RAY_DASHBOARD_URI\": \"ray-dashboard-address:8888\" }" } }, "description": "Persistent Cluster runtime information as output", "id": "GoogleCloudAiplatformV1beta1ResourceRuntime", "type": "object" }, "GoogleCloudAiplatformV1beta1GeminiRequestReadConfig": { "id": "GoogleCloudAiplatformV1beta1GeminiRequestReadConfig", "type": "object", "properties": { "assembledRequestColumnName": { "description": "Optional. Column name in the dataset table that contains already fully assembled Gemini requests.", "type": "string" }, "templateConfig": { "description": "Gemini request template with placeholders.", "$ref": "GoogleCloudAiplatformV1beta1GeminiTemplateConfig" } }, "description": "Configuration for how to read Gemini requests from a multimodal dataset." }, "GoogleCloudAiplatformV1beta1BlurBaselineConfig": { "id": "GoogleCloudAiplatformV1beta1BlurBaselineConfig", "type": "object", "properties": { "maxBlurSigma": { "format": "float", "description": "The standard deviation of the blur kernel for the blurred baseline. The same blurring parameter is used for both the height and the width dimension. If not set, the method defaults to the zero (i.e. black for images) baseline.", "type": "number" } }, "description": "Config for blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383" }, "GoogleCloudAiplatformV1beta1OnlineEvaluatorConfigRandomSampling": { "id": "GoogleCloudAiplatformV1beta1OnlineEvaluatorConfigRandomSampling", "type": "object", "properties": { "percentage": { "type": "integer", "format": "int32", "description": "Required. The percentage of traces to sample for evaluation. Must be an integer between `1` and `100`." } }, "description": "Configuration for random sampling." }, "GoogleCloudAiplatformV1beta1StudySpecConvexAutomatedStoppingSpec": { "description": "Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early-stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model.", "properties": { "minMeasurementCount": { "type": "string", "description": "The minimal number of measurements in a Trial. Early-stopping checks will not trigger if less than min_measurement_count+1 completed trials or pending trials with less than min_measurement_count measurements. If not defined, the default value is 5.", "format": "int64" }, "useElapsedDuration": { "description": "This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_elapsed_duration==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_elapsed_duration==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.", "type": "boolean" }, "learningRateParameterName": { "description": "The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial.", "type": "string" }, "maxStepCount": { "format": "int64", "description": "Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. If not defined, it will learn it from the completed trials. When use_steps is false, this field is set to the maximum elapsed seconds.", "type": "string" }, "updateAllStoppedTrials": { "description": "ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model. When this flag is set to True, all stopped trials from the beginning are potentially updated in terms of their `final_measurement`. Also, note that the training logic of autoregressive models is different in this case. Enabling this option has shown better results and this may be the default option in the future.", "type": "boolean" }, "minStepCount": { "description": "Minimum number of steps for a trial to complete. Trials which do not have a measurement with step_count \u003e min_step_count won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_step_count is set to be one-tenth of the max_step_count. When use_elapsed_duration is true, this field is set to the minimum elapsed seconds.", "format": "int64", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1StudySpecConvexAutomatedStoppingSpec", "type": "object" }, "CloudAiLargeModelsVisionNamedBoundingBox": { "properties": { "y2": { "format": "float", "type": "number" }, "x1": { "type": "number", "format": "float" }, "x2": { "type": "number", "format": "float" }, "y1": { "format": "float", "type": "number" }, "classes": { "type": "array", "items": { "type": "string" } }, "entities": { "type": "array", "items": { "type": "string" } }, "scores": { "type": "array", "items": { "type": "number", "format": "float" } } }, "id": "CloudAiLargeModelsVisionNamedBoundingBox", "type": "object" }, "GoogleCloudAiplatformV1beta1ModalityTokenCount": { "properties": { "tokenCount": { "format": "int32", "description": "The number of tokens counted for this modality.", "type": "integer" }, "modality": { "type": "string", "enumDescriptions": [ "When a modality is not specified, it is treated as `TEXT`.", "The `Part` contains plain text.", "The `Part` contains an image.", "The `Part` contains a video.", "The `Part` contains audio.", "The `Part` contains a document, such as a PDF." ], "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "VIDEO", "AUDIO", "DOCUMENT" ], "description": "The modality that this token count applies to." } }, "description": "Represents a breakdown of token usage by modality. This message is used in CountTokensResponse and GenerateContentResponse.UsageMetadata to provide a detailed view of how many tokens are used by each modality (e.g., text, image, video) in a request. This is particularly useful for multimodal models, allowing you to track and manage token consumption for billing and quota purposes.", "id": "GoogleCloudAiplatformV1beta1ModalityTokenCount", "type": "object" }, "GoogleCloudAiplatformV1beta1CorroborateContentResponse": { "id": "GoogleCloudAiplatformV1beta1CorroborateContentResponse", "type": "object", "description": "Response message for CorroborateContent.", "properties": { "claims": { "description": "Claims that are extracted from the input content and facts that support the claims.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Claim" } }, "corroborationScore": { "type": "number", "description": "Confidence score of corroborating content. Value is [0,1] with 1 is the most confidence.", "format": "float" } } }, "GoogleCloudAiplatformV1beta1UploadModelRequest": { "description": "Request message for ModelService.UploadModel.", "properties": { "modelId": { "description": "Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen.", "type": "string" }, "serviceAccount": { "description": "Optional. The user-provided custom service account to use to do the model upload. If empty, [Vertex AI Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) will be used to access resources needed to upload the model. This account must belong to the target project where the model is uploaded to, i.e., the project specified in the `parent` field of this request and have necessary read permissions (to Google Cloud Storage, Artifact Registry, etc.).", "type": "string" }, "parentModel": { "description": "Optional. The resource name of the model into which to upload the version. Only specify this field when uploading a new version.", "type": "string" }, "model": { "description": "Required. The Model to create.", "$ref": "GoogleCloudAiplatformV1beta1Model" } }, "id": "GoogleCloudAiplatformV1beta1UploadModelRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelSourceInfo": { "properties": { "copy": { "description": "If this Model is copy of another Model. If true then source_type pertains to the original.", "type": "boolean" }, "sourceType": { "enum": [ "MODEL_SOURCE_TYPE_UNSPECIFIED", "AUTOML", "CUSTOM", "BQML", "MODEL_GARDEN", "GENIE", "CUSTOM_TEXT_EMBEDDING", "MARKETPLACE" ], "description": "Type of the model source.", "type": "string", "enumDescriptions": [ "Should not be used.", "The Model is uploaded by automl training pipeline.", "The Model is uploaded by user or custom training pipeline.", "The Model is registered and sync'ed from BigQuery ML.", "The Model is saved or tuned from Model Garden.", "The Model is saved or tuned from Genie.", "The Model is uploaded by text embedding finetuning pipeline.", "The Model is saved or tuned from Marketplace." ] } }, "description": "Detail description of the source information of the model.", "id": "GoogleCloudAiplatformV1beta1ModelSourceInfo", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata": { "properties": { "runTime": { "type": "string", "description": "The time that most recent monitoring pipelines that is related to this run.", "format": "google-datetime" }, "status": { "description": "The status of the most recent monitoring pipeline.", "$ref": "GoogleRpcStatus" } }, "description": "All metadata of most recent monitoring pipelines.", "id": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1Memory": { "id": "GoogleCloudAiplatformV1beta1Memory", "type": "object", "properties": { "revisionTtl": { "type": "string", "description": "Optional. Input only. Represents the TTL for the revision. The expiration time is computed: now + TTL.", "format": "google-duration" }, "revisionExpireTime": { "type": "string", "description": "Optional. Input only. Represents the timestamp of when the revision is considered expired. If not set, the memory revision will be kept until manually deleted.", "format": "google-datetime" }, "name": { "description": "Identifier. Represents the resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "type": "string" }, "scope": { "description": "Required. Immutable. Represents the scope of the Memory. Memories are isolated within their scope. The scope is defined when creating or generating memories. Scope values cannot contain the wildcard character '*'.", "type": "object", "additionalProperties": { "type": "string" } }, "topics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1MemoryTopicId" }, "description": "Optional. Represents the Topics of the Memory." }, "structuredContent": { "description": "Optional. Represents the structured content of the memory.", "$ref": "GoogleCloudAiplatformV1beta1MemoryStructuredContent" }, "expireTime": { "format": "google-datetime", "description": "Optional. Represents the timestamp of when this resource is considered expired. This is *always* provided on output when `expiration` is set on input, regardless of whether `expire_time` or `ttl` was provided.", "type": "string" }, "fact": { "description": "Optional. Represents semantic knowledge extracted from the source content.", "type": "string" }, "disableMemoryRevisions": { "description": "Optional. Input only. Indicates whether no revision will be created for this request.", "type": "boolean" }, "displayName": { "description": "Optional. Represents the display name of the Memory.", "type": "string" }, "updateTime": { "format": "google-datetime", "description": "Output only. Represents the timestamp when this Memory was most recently updated.", "readOnly": true, "type": "string" }, "metadata": { "description": "Optional. Represents user-provided metadata for the Memory. This information was provided when creating, updating, or generating the Memory. It was not generated by Memory Bank.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1MemoryMetadataValue" } }, "description": { "description": "Optional. Represents the description of the Memory.", "type": "string" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Represents the timestamp when this Memory was created." }, "ttl": { "type": "string", "format": "google-duration", "description": "Optional. Input only. Represents the TTL for this resource. The expiration time is computed: now + TTL." }, "revisionLabels": { "description": "Optional. Input only. Represents the labels to apply to the Memory Revision created as a result of this request.", "type": "object", "additionalProperties": { "type": "string" } }, "memoryType": { "description": "Optional. Represents the type of the memory. If not set, the `NATURAL_LANGUAGE_COLLECTION` type is used. If `STRUCTURED_COLLECTION` or `STRUCTURED_PROFILE` is used, then `structured_data` must be provided.", "enum": [ "MEMORY_TYPE_UNSPECIFIED", "NATURAL_LANGUAGE_COLLECTION", "STRUCTURED_PROFILE" ], "type": "string", "enumDescriptions": [ "Represents an unspecified memory type. This value should not be used.", "Indicates belonging to a collection of natural language memories.", "Indicates belonging to a structured profile." ] } }, "description": "A memory." }, "GoogleCloudAiplatformV1beta1ListPublisherModelsResponse": { "properties": { "publisherModels": { "description": "List of PublisherModels in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModel" } }, "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListPublisherModels.page_token to obtain that page.", "type": "string" } }, "description": "Response message for ModelGardenService.ListPublisherModels.", "id": "GoogleCloudAiplatformV1beta1ListPublisherModelsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1DataItem": { "properties": { "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this DataItem was last updated.", "format": "google-datetime" }, "name": { "readOnly": true, "type": "string", "description": "Output only. The resource name of the DataItem." }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The labels with user-defined metadata to organize your DataItems. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one DataItem(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable." }, "payload": { "description": "Required. The data that the DataItem represents (for example, an image or a text snippet). The schema of the payload is stored in the parent Dataset's metadata schema's dataItemSchemaUri field.", "type": "any" }, "satisfiesPzi": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "createTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this DataItem was created.", "format": "google-datetime" }, "satisfiesPzs": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" } }, "description": "A piece of data in a Dataset. Could be an image, a video, a document or plain text.", "id": "GoogleCloudAiplatformV1beta1DataItem", "type": "object" }, "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesResponse": { "id": "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesResponse", "type": "object", "properties": { "dataKeysWithError": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDataKey" } }, "data": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse" } }, "status": { "$ref": "GoogleRpcStatus", "description": "Response status. If OK, then StreamingFetchFeatureValuesResponse.data will be populated. Otherwise StreamingFetchFeatureValuesResponse.data_keys_with_error will be populated with the appropriate data keys. The error only applies to the listed data keys - the stream will remain open for further FeatureOnlineStoreService.StreamingFetchFeatureValuesRequest requests." } }, "description": "Response message for FeatureOnlineStoreService.StreamingFetchFeatureValues." }, "GoogleCloudAiplatformV1beta1Scheduling": { "description": "All parameters related to queuing and scheduling of custom jobs.", "properties": { "timeout": { "format": "google-duration", "description": "Optional. The maximum job running time. The default is 7 days.", "type": "string" }, "strategy": { "type": "string", "enumDescriptions": [ "Strategy will default to STANDARD.", "Deprecated. Regular on-demand provisioning strategy.", "Deprecated. Low cost by making potential use of spot resources.", "Standard provisioning strategy uses regular on-demand resources.", "Spot provisioning strategy uses spot resources.", "Flex Start strategy uses DWS to queue for resources." ], "enumDeprecated": [ false, true, true, false, false, false ], "description": "Optional. This determines which type of scheduling strategy to use.", "enum": [ "STRATEGY_UNSPECIFIED", "ON_DEMAND", "LOW_COST", "STANDARD", "SPOT", "FLEX_START" ] }, "restartJobOnWorkerRestart": { "description": "Optional. Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.", "type": "boolean" }, "disableRetries": { "description": "Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false.", "type": "boolean" }, "maxWaitDuration": { "description": "Optional. This is the maximum duration that a job will wait for the requested resources to be provisioned if the scheduling strategy is set to [Strategy.DWS_FLEX_START]. If set to 0, the job will wait indefinitely. The default is 24 hours.", "format": "google-duration", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1Scheduling", "type": "object" }, "GoogleCloudAiplatformV1beta1SuggestTrialsResponse": { "id": "GoogleCloudAiplatformV1beta1SuggestTrialsResponse", "type": "object", "description": "Response message for VizierService.SuggestTrials.", "properties": { "endTime": { "type": "string", "description": "The time at which operation processing completed.", "format": "google-datetime" }, "startTime": { "description": "The time at which the operation was started.", "format": "google-datetime", "type": "string" }, "studyState": { "type": "string", "enumDescriptions": [ "The study state is unspecified.", "The study is active.", "The study is stopped due to an internal error.", "The study is done when the service exhausts the parameter search space or max_trial_count is reached." ], "enum": [ "STATE_UNSPECIFIED", "ACTIVE", "INACTIVE", "COMPLETED" ], "description": "The state of the Study." }, "trials": { "description": "A list of Trials.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Trial" } } } }, "GoogleCloudAiplatformV1beta1MetadataStoreMetadataStoreState": { "description": "Represents state information for a MetadataStore.", "properties": { "diskUtilizationBytes": { "type": "string", "format": "int64", "description": "The disk utilization of the MetadataStore in bytes." } }, "id": "GoogleCloudAiplatformV1beta1MetadataStoreMetadataStoreState", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation", "type": "object", "properties": { "columnName": { "type": "string" } }, "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * A boolean value that indicates whether the value is valid." }, "GoogleCloudAiplatformV1beta1SharePointSourcesSharePointSource": { "properties": { "fileId": { "description": "Output only. The SharePoint file id. Output only.", "type": "string", "readOnly": true }, "clientId": { "description": "The Application ID for the app registered in Microsoft Azure Portal. The application must also be configured with MS Graph permissions \"Files.ReadAll\", \"Sites.ReadAll\" and BrowserSiteLists.Read.All.", "type": "string" }, "sharepointSiteName": { "description": "The name of the SharePoint site to download from. This can be the site name or the site id.", "type": "string" }, "driveId": { "description": "The ID of the drive to download from.", "type": "string" }, "sharepointFolderPath": { "description": "The path of the SharePoint folder to download from.", "type": "string" }, "driveName": { "description": "The name of the drive to download from.", "type": "string" }, "sharepointFolderId": { "description": "The ID of the SharePoint folder to download from.", "type": "string" }, "clientSecret": { "description": "The application secret for the app registered in Azure.", "$ref": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig" }, "tenantId": { "description": "Unique identifier of the Azure Active Directory Instance.", "type": "string" } }, "description": "An individual SharePointSource.", "id": "GoogleCloudAiplatformV1beta1SharePointSourcesSharePointSource", "type": "object" }, "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInstance": { "description": "Spec for tool parameter key value match instance.", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "reference": { "description": "Required. Ground truth used to compare against the prediction.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictionResultError": { "properties": { "status": { "type": "string", "enumDescriptions": [ "Not an error; returned on success. HTTP Mapping: 200 OK", "The operation was cancelled, typically by the caller. HTTP Mapping: 499 Client Closed Request", "Unknown error. For example, this error may be returned when a `Status` value received from another address space belongs to an error space that is not known in this address space. Also errors raised by APIs that do not return enough error information may be converted to this error. HTTP Mapping: 500 Internal Server Error", "The client specified an invalid argument. Note that this differs from `FAILED_PRECONDITION`. `INVALID_ARGUMENT` indicates arguments that are problematic regardless of the state of the system (e.g., a malformed file name). HTTP Mapping: 400 Bad Request", "The deadline expired before the operation could complete. For operations that change the state of the system, this error may be returned even if the operation has completed successfully. For example, a successful response from a server could have been delayed long enough for the deadline to expire. HTTP Mapping: 504 Gateway Timeout", "Some requested entity (e.g., file or directory) was not found. Note to server developers: if a request is denied for an entire class of users, such as gradual feature rollout or undocumented allowlist, `NOT_FOUND` may be used. If a request is denied for some users within a class of users, such as user-based access control, `PERMISSION_DENIED` must be used. HTTP Mapping: 404 Not Found", "The entity that a client attempted to create (e.g., file or directory) already exists. HTTP Mapping: 409 Conflict", "The caller does not have permission to execute the specified operation. `PERMISSION_DENIED` must not be used for rejections caused by exhausting some resource (use `RESOURCE_EXHAUSTED` instead for those errors). `PERMISSION_DENIED` must not be used if the caller can not be identified (use `UNAUTHENTICATED` instead for those errors). This error code does not imply the request is valid or the requested entity exists or satisfies other pre-conditions. HTTP Mapping: 403 Forbidden", "The request does not have valid authentication credentials for the operation. HTTP Mapping: 401 Unauthorized", "Some resource has been exhausted, perhaps a per-user quota, or perhaps the entire file system is out of space. HTTP Mapping: 429 Too Many Requests", "The operation was rejected because the system is not in a state required for the operation's execution. For example, the directory to be deleted is non-empty, an rmdir operation is applied to a non-directory, etc. Service implementors can use the following guidelines to decide between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`: (a) Use `UNAVAILABLE` if the client can retry just the failing call. (b) Use `ABORTED` if the client should retry at a higher level. For example, when a client-specified test-and-set fails, indicating the client should restart a read-modify-write sequence. (c) Use `FAILED_PRECONDITION` if the client should not retry until the system state has been explicitly fixed. For example, if an \"rmdir\" fails because the directory is non-empty, `FAILED_PRECONDITION` should be returned since the client should not retry unless the files are deleted from the directory. HTTP Mapping: 400 Bad Request", "The operation was aborted, typically due to a concurrency issue such as a sequencer check failure or transaction abort. See the guidelines above for deciding between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`. HTTP Mapping: 409 Conflict", "The operation was attempted past the valid range. E.g., seeking or reading past end-of-file. Unlike `INVALID_ARGUMENT`, this error indicates a problem that may be fixed if the system state changes. For example, a 32-bit file system will generate `INVALID_ARGUMENT` if asked to read at an offset that is not in the range [0,2^32-1], but it will generate `OUT_OF_RANGE` if asked to read from an offset past the current file size. There is a fair bit of overlap between `FAILED_PRECONDITION` and `OUT_OF_RANGE`. We recommend using `OUT_OF_RANGE` (the more specific error) when it applies so that callers who are iterating through a space can easily look for an `OUT_OF_RANGE` error to detect when they are done. HTTP Mapping: 400 Bad Request", "The operation is not implemented or is not supported/enabled in this service. HTTP Mapping: 501 Not Implemented", "Internal errors. This means that some invariants expected by the underlying system have been broken. This error code is reserved for serious errors. HTTP Mapping: 500 Internal Server Error", "The service is currently unavailable. This is most likely a transient condition, which can be corrected by retrying with a backoff. Note that it is not always safe to retry non-idempotent operations. See the guidelines above for deciding between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`. HTTP Mapping: 503 Service Unavailable", "Unrecoverable data loss or corruption. HTTP Mapping: 500 Internal Server Error" ], "description": "Error status. This will be serialized into the enum name e.g. \"NOT_FOUND\".", "enum": [ "OK", "CANCELLED", "UNKNOWN", "INVALID_ARGUMENT", "DEADLINE_EXCEEDED", "NOT_FOUND", "ALREADY_EXISTS", "PERMISSION_DENIED", "UNAUTHENTICATED", "RESOURCE_EXHAUSTED", "FAILED_PRECONDITION", "ABORTED", "OUT_OF_RANGE", "UNIMPLEMENTED", "INTERNAL", "UNAVAILABLE", "DATA_LOSS" ] }, "message": { "description": "Error message with additional details.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaPredictionResultError", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation": { "properties": { "columnName": { "type": "string" } }, "description": "Training pipeline will infer the proper transformation based on the statistic of dataset.", "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation", "type": "object" }, "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualitySpec": { "properties": { "useReference": { "description": "Optional. Whether to use instance.reference to compute question answering quality.", "type": "boolean" }, "version": { "type": "integer", "description": "Optional. Which version to use for evaluation.", "format": "int32" } }, "description": "Spec for pairwise question answering quality score metric.", "id": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualitySpec", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictionResult": { "properties": { "instance": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "User's input instance. Struct is used here instead of Any so that JsonFormat does not append an extra \"@type\" field when we convert the proto to JSON." }, "key": { "description": "Optional user-provided key from the input instance.", "type": "string" }, "error": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPredictionResultError", "description": "The error result. Do not set prediction if this is set." }, "prediction": { "description": "The prediction result. Value is used here instead of Any so that JsonFormat does not append an extra \"@type\" field when we convert the proto to JSON and so we can represent array of objects. Do not set error if this is set.", "type": "any" } }, "description": "Represents a line of JSONL in the batch prediction output file.", "id": "GoogleCloudAiplatformV1beta1SchemaPredictionResult", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesMetadata": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesMetadata", "type": "object", "description": "Model metadata specific to AutoML Tables.", "properties": { "trainCostMilliNodeHours": { "type": "string", "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget.", "format": "int64" }, "evaluatedDataItemsBigqueryUri": { "description": "BigQuery destination uri for exported evaluated examples.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ListDatasetsResponse": { "id": "GoogleCloudAiplatformV1beta1ListDatasetsResponse", "type": "object", "description": "Response message for DatasetService.ListDatasets.", "properties": { "datasets": { "description": "A list of Datasets that matches the specified filter in the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Dataset" } }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeature": { "properties": { "value": { "$ref": "GoogleCloudAiplatformV1beta1FeatureValue", "description": "Feature value. A user provided timestamp may be set in the `FeatureValue.metadata.generate_time` field." }, "valueAndTimestamp": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeatureFeatureValueAndTimestamp", "description": "Feature value and timestamp." }, "name": { "description": "Feature short name.", "type": "string" } }, "description": "Feature name & value pair.", "id": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeature", "type": "object" }, "GoogleCloudAiplatformV1beta1ResourceRuntimeSpec": { "properties": { "serviceAccountSpec": { "description": "Optional. Configure the use of workload identity on the PersistentResource", "$ref": "GoogleCloudAiplatformV1beta1ServiceAccountSpec" }, "raySpec": { "description": "Optional. Ray cluster configuration. Required when creating a dedicated RayCluster on the PersistentResource.", "$ref": "GoogleCloudAiplatformV1beta1RaySpec" } }, "description": "Configuration for the runtime on a PersistentResource instance, including but not limited to: * Service accounts used to run the workloads. * Whether to make it a dedicated Ray Cluster.", "id": "GoogleCloudAiplatformV1beta1ResourceRuntimeSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1QueryDeployedModelsResponse": { "properties": { "deployedModels": { "description": "DEPRECATED Use deployed_model_refs instead.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DeployedModel" }, "deprecated": true }, "totalDeployedModelCount": { "type": "integer", "format": "int32", "description": "The total number of DeployedModels on this DeploymentResourcePool." }, "nextPageToken": { "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" }, "deployedModelRefs": { "description": "References to the DeployedModels that share the specified deploymentResourcePool.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DeployedModelRef" } }, "totalEndpointCount": { "format": "int32", "description": "The total number of Endpoints that have DeployedModels on this DeploymentResourcePool.", "type": "integer" } }, "description": "Response message for QueryDeployedModels method.", "id": "GoogleCloudAiplatformV1beta1QueryDeployedModelsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringAnomalyTabularAnomaly": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAnomalyTabularAnomaly", "type": "object", "description": "Tabular anomaly details.", "properties": { "triggerTime": { "type": "string", "format": "google-datetime", "description": "The time the anomaly was triggered." }, "anomalyUri": { "description": "Additional anomaly information. e.g. Google Cloud Storage uri.", "type": "string" }, "anomaly": { "description": "Anomaly body.", "type": "any" }, "condition": { "description": "The alert condition associated with this anomaly.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition" }, "summary": { "description": "Overview of this anomaly.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ToolNameMatchInstance": { "description": "Spec for tool name match instance.", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "reference": { "description": "Required. Ground truth used to compare against the prediction.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ToolNameMatchInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataEvents": { "description": "Represents a list of events for an agent.", "properties": { "event": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "description": "Optional. A list of events." } }, "id": "GoogleCloudAiplatformV1beta1EvaluationInstanceDeprecatedAgentDataEvents", "type": "object" }, "GoogleCloudAiplatformV1beta1NasJobOutputMultiTrialJobOutput": { "description": "The output of a multi-trial Neural Architecture Search (NAS) jobs.", "properties": { "searchTrials": { "description": "Output only. List of NasTrials that were started as part of search stage.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NasTrial" }, "readOnly": true }, "trainTrials": { "description": "Output only. List of NasTrials that were started as part of train stage.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NasTrial" }, "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1NasJobOutputMultiTrialJobOutput", "type": "object" }, "GoogleCloudAiplatformV1beta1Endpoint": { "description": "Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.", "properties": { "encryptionSpec": { "description": "Customer-managed encryption key spec for an Endpoint. If set, this Endpoint and all sub-resources of this Endpoint will be secured by this key.", "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" }, "clientConnectionConfig": { "description": "Configurations that are applied to the endpoint for online prediction.", "$ref": "GoogleCloudAiplatformV1beta1ClientConnectionConfig" }, "dedicatedEndpointDns": { "type": "string", "readOnly": true, "description": "Output only. DNS of the dedicated endpoint. Will only be populated if dedicated_endpoint_enabled is true. Depending on the features enabled, uid might be a random number or a string. For example, if fast_tryout is enabled, uid will be fasttryout. Format: `https://{endpoint_id}.{region}-{uid}.prediction.vertexai.goog`." }, "modelDeploymentMonitoringJob": { "type": "string", "readOnly": true, "description": "Output only. Resource name of the Model Monitoring job associated with this Endpoint if monitoring is enabled by JobService.CreateModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`" }, "trafficSplit": { "type": "object", "additionalProperties": { "type": "integer", "format": "int32" }, "description": "A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If a DeployedModel's ID is not listed in this map, then it receives no traffic. The traffic percentage values must add up to 100, or map must be empty if the Endpoint is to not accept any traffic at a moment." }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "dedicatedEndpointEnabled": { "description": "If true, the endpoint will be exposed through a dedicated DNS [Endpoint.dedicated_endpoint_dns]. Your request to the dedicated DNS will be isolated from other users' traffic and will have better performance and reliability. Note: Once you enabled dedicated endpoint, you won't be able to send request to the shared DNS {region}-aiplatform.googleapis.com. The limitation will be removed soon.", "type": "boolean" }, "description": { "description": "The description of the Endpoint.", "type": "string" }, "deployedModels": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DeployedModel" }, "readOnly": true, "description": "Output only. The models deployed in this Endpoint. To add or remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel respectively." }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this Endpoint was created." }, "labels": { "description": "The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", "type": "object", "additionalProperties": { "type": "string" } }, "privateServiceConnectConfig": { "description": "Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive.", "$ref": "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig" }, "predictRequestResponseLoggingConfig": { "description": "Configures the request-response logging for online prediction.", "$ref": "GoogleCloudAiplatformV1beta1PredictRequestResponseLoggingConfig" }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this Endpoint was last updated.", "format": "google-datetime" }, "displayName": { "description": "Required. The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "enablePrivateServiceConnect": { "description": "Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.", "deprecated": true, "type": "boolean" }, "network": { "description": "Optional. The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks) to which the Endpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. Only one of the fields, network or enable_private_service_connect, can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where `{project}` is a project number, as in `12345`, and `{network}` is network name.", "type": "string" }, "genAiAdvancedFeaturesConfig": { "$ref": "GoogleCloudAiplatformV1beta1GenAiAdvancedFeaturesConfig", "description": "Optional. Configuration for GenAiAdvancedFeatures. If the endpoint is serving GenAI models, advanced features like native RAG integration can be configured. Currently, only Model Garden models are supported." }, "gdcConfig": { "$ref": "GoogleCloudAiplatformV1beta1GdcConfig", "description": "Configures the Google Distributed Cloud (GDC) environment for online prediction. Only set this field when the Endpoint is to be deployed in a GDC environment." }, "satisfiesPzs": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "name": { "description": "Identifier. The resource name of the Endpoint.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1Endpoint", "type": "object" }, "GoogleCloudAiplatformV1beta1ListOnlineEvaluatorsResponse": { "id": "GoogleCloudAiplatformV1beta1ListOnlineEvaluatorsResponse", "type": "object", "description": "Response message for ListOnlineEvaluators.", "properties": { "onlineEvaluators": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluator" }, "description": "A list of OnlineEvaluators matching the request." }, "nextPageToken": { "description": "A token to retrieve the next page. Absence of this field indicates there are no subsequent pages.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1NasJob": { "properties": { "displayName": { "description": "Required. The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "startTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the NasJob for the first time entered the `JOB_STATE_RUNNING` state." }, "state": { "readOnly": true, "type": "string", "enumDescriptions": [ "The job state is unspecified.", "The job has been just created or resumed and processing has not yet begun.", "The service is preparing to run the job.", "The job is in progress.", "The job completed successfully.", "The job failed.", "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "The job has been cancelled.", "The job has been stopped, and can be resumed.", "The job has expired.", "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", "The job is partially succeeded, some results may be missing due to errors." ], "enum": [ "JOB_STATE_UNSPECIFIED", "JOB_STATE_QUEUED", "JOB_STATE_PENDING", "JOB_STATE_RUNNING", "JOB_STATE_SUCCEEDED", "JOB_STATE_FAILED", "JOB_STATE_CANCELLING", "JOB_STATE_CANCELLED", "JOB_STATE_PAUSED", "JOB_STATE_EXPIRED", "JOB_STATE_UPDATING", "JOB_STATE_PARTIALLY_SUCCEEDED" ], "description": "Output only. The detailed state of the job." }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "nasJobSpec": { "description": "Required. The specification of a NasJob.", "$ref": "GoogleCloudAiplatformV1beta1NasJobSpec" }, "name": { "description": "Output only. Resource name of the NasJob.", "readOnly": true, "type": "string" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key." }, "enableRestrictedImageTraining": { "deprecated": true, "type": "boolean", "description": "Optional. Enable a separation of Custom model training and restricted image training for tenant project." }, "nasJobOutput": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1NasJobOutput", "description": "Output only. Output of the NasJob." }, "createTime": { "format": "google-datetime", "description": "Output only. Time when the NasJob was created.", "readOnly": true, "type": "string" }, "labels": { "description": "The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", "type": "object", "additionalProperties": { "type": "string" } }, "endTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the NasJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`." }, "updateTime": { "format": "google-datetime", "description": "Output only. Time when the NasJob was most recently updated.", "readOnly": true, "type": "string" }, "error": { "description": "Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.", "readOnly": true, "$ref": "GoogleRpcStatus" } }, "description": "Represents a Neural Architecture Search (NAS) job.", "id": "GoogleCloudAiplatformV1beta1NasJob", "type": "object" }, "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessResult": { "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessResult", "type": "object", "properties": { "explanation": { "description": "Output only. Explanation for question answering correctness score.", "readOnly": true, "type": "string" }, "score": { "type": "number", "readOnly": true, "description": "Output only. Question Answering Correctness score.", "format": "float" }, "confidence": { "format": "float", "description": "Output only. Confidence for question answering correctness score.", "readOnly": true, "type": "number" } }, "description": "Spec for question answering correctness result." }, "GoogleCloudAiplatformV1beta1ModelMonitoringAlert": { "properties": { "alertTime": { "type": "string", "format": "google-datetime", "description": "Alert creation time." }, "anomaly": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringAnomaly", "description": "Anomaly details." }, "statsName": { "description": "The stats name.", "type": "string" }, "objectiveType": { "description": "One of the supported monitoring objectives: `raw-feature-drift` `prediction-output-drift` `feature-attribution`", "type": "string" } }, "description": "Represents a single monitoring alert. This is currently used in the SearchModelMonitoringAlerts api, thus the alert wrapped in this message belongs to the resource asked in the request.", "id": "GoogleCloudAiplatformV1beta1ModelMonitoringAlert", "type": "object" }, "GoogleCloudAiplatformV1beta1RagManagedDbConfigEnterprise": { "deprecated": true, "id": "GoogleCloudAiplatformV1beta1RagManagedDbConfigEnterprise", "properties": {}, "description": "Enterprise tier offers production grade performance along with autoscaling functionality. It is suitable for customers with large amounts of data or performance sensitive workloads.", "type": "object" }, "GoogleCloudAiplatformV1beta1Attribution": { "id": "GoogleCloudAiplatformV1beta1Attribution", "type": "object", "properties": { "outputName": { "description": "Output only. Name of the explain output. Specified as the key in ExplanationMetadata.outputs.", "readOnly": true, "type": "string" }, "outputDisplayName": { "description": "Output only. The display name of the output identified by output_index. For example, the predicted class name by a multi-classification Model. This field is only populated iff the Model predicts display names as a separate field along with the explained output. The predicted display name must has the same shape of the explained output, and can be located using output_index.", "type": "string", "readOnly": true }, "featureAttributions": { "description": "Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance contributed to the predicted result. The format of the value is determined by the feature's input format: * If the feature is a scalar value, the attribution value is a floating number. * If the feature is an array of scalar values, the attribution value is an array. * If the feature is a struct, the attribution value is a struct. The keys in the attribution value struct are the same as the keys in the feature struct. The formats of the values in the attribution struct are determined by the formats of the values in the feature struct. The ExplanationMetadata.feature_attributions_schema_uri field, pointed to by the ExplanationSpec field of the Endpoint.deployed_models object, points to the schema file that describes the features and their attribution values (if it is populated).", "type": "any", "readOnly": true }, "approximationError": { "format": "double", "description": "Output only. Error of feature_attributions caused by approximation used in the explanation method. Lower value means more precise attributions. * For Sampled Shapley attribution, increasing path_count might reduce the error. * For Integrated Gradients attribution, increasing step_count might reduce the error. * For XRAI attribution, increasing step_count might reduce the error. See [this introduction](/vertex-ai/docs/explainable-ai/overview) for more information.", "readOnly": true, "type": "number" }, "outputIndex": { "description": "Output only. The index that locates the explained prediction output. If the prediction output is a scalar value, output_index is not populated. If the prediction output has multiple dimensions, the length of the output_index list is the same as the number of dimensions of the output. The i-th element in output_index is the element index of the i-th dimension of the output vector. Indices start from 0.", "readOnly": true, "type": "array", "items": { "format": "int32", "type": "integer" } }, "instanceOutputValue": { "format": "double", "description": "Output only. Model predicted output on the corresponding explanation instance. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model predicted output has multiple dimensions, this is the value in the output located by output_index.", "readOnly": true, "type": "number" }, "baselineOutputValue": { "type": "number", "readOnly": true, "description": "Output only. Model predicted output if the input instance is constructed from the baselines of all the features defined in ExplanationMetadata.inputs. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model's predicted output has multiple dimensions (rank \u003e 1), this is the value in the output located by output_index. If there are multiple baselines, their output values are averaged.", "format": "double" } }, "description": "Attribution that explains a particular prediction output." }, "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputConfig": { "id": "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputConfig", "type": "object", "properties": { "gcsDestination": { "description": "The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is `prediction--`, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files `predictions_0001.`, `predictions_0002.`, ..., `predictions_N.` are created where `` depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional `errors_0001.`, `errors_0002.`,..., `errors_N.` files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional `error` field which as value has google.rpc.Status containing only `code` and `message` fields.", "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" }, "vertexMultimodalDatasetDestination": { "$ref": "GoogleCloudAiplatformV1beta1VertexMultimodalDatasetDestination", "description": "The details for a Vertex Multimodal Dataset that will be created for the output." }, "bigqueryDestination": { "description": "The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name `prediction__` where is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ \"based on ISO-8601\" format. In the dataset two tables will be created, `predictions`, and `errors`. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The `predictions` table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The `errors` table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single \"errors\" column, which as values has google.rpc.Status represented as a STRUCT, and containing only `code` and `message`.", "$ref": "GoogleCloudAiplatformV1beta1BigQueryDestination" }, "predictionsFormat": { "description": "Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.", "type": "string" } }, "description": "Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them." }, "GoogleCloudAiplatformV1beta1ReasoningEngineSpecPackageSpec": { "id": "GoogleCloudAiplatformV1beta1ReasoningEngineSpecPackageSpec", "type": "object", "description": "User-provided package specification, containing pickled object and package requirements.", "properties": { "pythonVersion": { "description": "Optional. The Python version. Supported values are 3.9, 3.10, 3.11, 3.12, 3.13, 3.14. If not specified, the default value is 3.10.", "type": "string" }, "pickleObjectGcsUri": { "description": "Optional. The Cloud Storage URI of the pickled python object.", "type": "string" }, "dependencyFilesGcsUri": { "description": "Optional. The Cloud Storage URI of the dependency files in tar.gz format.", "type": "string" }, "requirementsGcsUri": { "description": "Optional. The Cloud Storage URI of the `requirements.txt` file", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTables": { "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputs" }, "metadata": { "description": "The metadata information.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesMetadata" } }, "description": "A TrainingJob that trains and uploads an AutoML Tables Model.", "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTables", "type": "object" }, "GoogleCloudAiplatformV1beta1ExternalApiElasticSearchParams": { "id": "GoogleCloudAiplatformV1beta1ExternalApiElasticSearchParams", "type": "object", "description": "The search parameters to use for the ELASTIC_SEARCH spec.", "properties": { "searchTemplate": { "description": "The ElasticSearch search template to use.", "type": "string" }, "index": { "description": "The ElasticSearch index to use.", "type": "string" }, "numHits": { "description": "Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1beta1AssembleDataRequest": { "properties": { "geminiRequestReadConfig": { "$ref": "GoogleCloudAiplatformV1beta1GeminiRequestReadConfig", "description": "Optional. The read config for the dataset." } }, "description": "Request message for DatasetService.AssembleData. Used only for MULTIMODAL datasets.", "id": "GoogleCloudAiplatformV1beta1AssembleDataRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1RetrieveContextsResponse": { "description": "Response message for VertexRagService.RetrieveContexts.", "properties": { "contexts": { "$ref": "GoogleCloudAiplatformV1beta1RagContexts", "description": "The contexts of the query." } }, "id": "GoogleCloudAiplatformV1beta1RetrieveContextsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetResponse": { "description": "Response message of ModelService.UpdateExplanationDataset operation.", "properties": {}, "id": "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1TaskOutputChange": { "id": "GoogleCloudAiplatformV1beta1TaskOutputChange", "type": "object", "properties": { "taskArtifactChange": { "$ref": "GoogleCloudAiplatformV1beta1TaskArtifactChange", "description": "Required. A granular change to the list of artifacts." } }, "description": "An event representing a change to the task's outputs." }, "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSourceEvent": { "properties": { "content": { "$ref": "GoogleCloudAiplatformV1beta1Content", "description": "Required. Represents the content of the event." } }, "description": "A single conversation event.", "id": "GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSourceEvent", "type": "object" }, "GoogleCloudAiplatformV1beta1ExportDataConfig": { "description": "Describes what part of the Dataset is to be exported, the destination of the export and how to export.", "properties": { "gcsDestination": { "description": "The Google Cloud Storage location where the output is to be written to. In the given directory a new directory will be created with name: `export-data--` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All export output will be written into that directory. Inside that directory, annotations with the same schema will be grouped into sub directories which are named with the corresponding annotations' schema title. Inside these sub directories, a schema.yaml will be created to describe the output format.", "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" }, "annotationsFilter": { "description": "An expression for filtering what part of the Dataset is to be exported. Only Annotations that match this filter will be exported. The filter syntax is the same as in ListAnnotations.", "type": "string" }, "fractionSplit": { "description": "Split based on fractions defining the size of each set.", "$ref": "GoogleCloudAiplatformV1beta1ExportFractionSplit" } }, "id": "GoogleCloudAiplatformV1beta1ExportDataConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1DeployPublisherModelRequest": { "type": "object", "description": "Request message for ModelGardenService.DeployPublisherModel.", "properties": { "model": { "description": "Required. The model to deploy. Format: 1. `publishers/{publisher}/models/{publisher_model}@{version_id}`, or `publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001`. 2. Hugging Face model ID like `google/gemma-2-2b-it`. 3. Custom model Google Cloud Storage URI like `gs://bucket`. 4. Custom model zip file like `https://example.com/a.zip`.", "type": "string" }, "modelDisplayName": { "description": "Optional. The user-specified display name of the uploaded model. If not set, a default name will be used.", "type": "string" }, "huggingFaceAccessToken": { "description": "Optional. The Hugging Face read access token used to access the model artifacts of gated models.", "type": "string" }, "dedicatedResources": { "$ref": "GoogleCloudAiplatformV1beta1DedicatedResources", "description": "Optional. The dedicated resources to use for the endpoint. If not set, the default resources will be used." }, "acceptEula": { "description": "Optional. Whether the user accepts the End User License Agreement (EULA) for the model.", "type": "boolean" }, "endpointDisplayName": { "description": "Optional. The user-specified display name of the endpoint. If not set, a default name will be used.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1DeployPublisherModelRequest", "deprecated": true }, "GoogleCloudAiplatformV1beta1RuntimeConfigCodeInterpreterRuntimeConfig": { "id": "GoogleCloudAiplatformV1beta1RuntimeConfigCodeInterpreterRuntimeConfig", "type": "object", "properties": { "fileInputGcsBucket": { "description": "Optional. The Cloud Storage bucket for file input of this Extension. If specified, support input from the Cloud Storage bucket. Vertex Extension Custom Code Service Agent should be granted file reader to this bucket. If not specified, the extension will only accept file contents from request body and reject Cloud Storage file inputs.", "type": "string" }, "fileOutputGcsBucket": { "description": "Optional. The Cloud Storage bucket for file output of this Extension. If specified, write all output files to the Cloud Storage bucket. Vertex Extension Custom Code Service Agent should be granted file writer to this bucket. If not specified, the file content will be output in response body.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1EvaluationParserConfig": { "description": "Config for parsing LLM responses. It can be used to parse the LLM response to be evaluated, or the LLM response from LLM-based metrics/Autoraters.", "properties": { "customCodeParserConfig": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationParserConfigCustomCodeParserConfig", "description": "Optional. Use custom code to parse the LLM response." } }, "id": "GoogleCloudAiplatformV1beta1EvaluationParserConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1RagManagedDbConfigBasic": { "id": "GoogleCloudAiplatformV1beta1RagManagedDbConfigBasic", "type": "object", "description": "Basic tier is a cost-effective and low compute tier suitable for the following cases: * Experimenting with RagManagedDb. * Small data size. * Latency insensitive workload. * Only using RAG Engine with external vector DBs. NOTE: This is the default tier under Spanner mode if not explicitly chosen.", "properties": {} }, "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTabularRegressionPredictionResult": { "description": "Prediction output format for Tabular Regression.", "properties": { "lowerBound": { "description": "The lower bound of the prediction interval.", "format": "float", "type": "number" }, "upperBound": { "format": "float", "description": "The upper bound of the prediction interval.", "type": "number" }, "quantileValues": { "type": "array", "items": { "format": "float", "type": "number" }, "description": "Quantile values." }, "value": { "description": "The regression value.", "format": "float", "type": "number" }, "quantilePredictions": { "description": "Quantile predictions, in 1-1 correspondence with quantile_values.", "type": "array", "items": { "format": "float", "type": "number" } } }, "id": "GoogleCloudAiplatformV1beta1SchemaPredictPredictionTabularRegressionPredictionResult", "type": "object" }, "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponse": { "description": "Response message for FeaturestoreOnlineServingService.ReadFeatureValues.", "properties": { "header": { "description": "Response header.", "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseHeader" }, "entityView": { "description": "Entity view with Feature values. This may be the entity in the Featurestore if values for all Features were requested, or a projection of the entity in the Featurestore if values for only some Features were requested.", "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityView" } }, "id": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponse", "type": "object" }, "GoogleIamV1Policy": { "properties": { "etag": { "type": "string", "format": "byte", "description": "`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost." }, "bindings": { "type": "array", "items": { "$ref": "GoogleIamV1Binding" }, "description": "Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`." }, "version": { "type": "integer", "description": "Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "format": "int32" } }, "description": "An Identity and Access Management (IAM) policy, which specifies access controls for Google Cloud resources. A `Policy` is a collection of `bindings`. A `binding` binds one or more `members`, or principals, to a single `role`. Principals can be user accounts, service accounts, Google groups, and domains (such as G Suite). A `role` is a named list of permissions; each `role` can be an IAM predefined role or a user-created custom role. For some types of Google Cloud resources, a `binding` can also specify a `condition`, which is a logical expression that allows access to a resource only if the expression evaluates to `true`. A condition can add constraints based on attributes of the request, the resource, or both. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies). **JSON example:** ``` { \"bindings\": [ { \"role\": \"roles/resourcemanager.organizationAdmin\", \"members\": [ \"user:mike@example.com\", \"group:admins@example.com\", \"domain:google.com\", \"serviceAccount:my-project-id@appspot.gserviceaccount.com\" ] }, { \"role\": \"roles/resourcemanager.organizationViewer\", \"members\": [ \"user:eve@example.com\" ], \"condition\": { \"title\": \"expirable access\", \"description\": \"Does not grant access after Sep 2020\", \"expression\": \"request.time \u003c timestamp('2020-10-01T00:00:00.000Z')\", } } ], \"etag\": \"BwWWja0YfJA=\", \"version\": 3 } ``` **YAML example:** ``` bindings: - members: - user:mike@example.com - group:admins@example.com - domain:google.com - serviceAccount:my-project-id@appspot.gserviceaccount.com role: roles/resourcemanager.organizationAdmin - members: - user:eve@example.com role: roles/resourcemanager.organizationViewer condition: title: expirable access description: Does not grant access after Sep 2020 expression: request.time \u003c timestamp('2020-10-01T00:00:00.000Z') etag: BwWWja0YfJA= version: 3 ``` For a description of IAM and its features, see the [IAM documentation](https://cloud.google.com/iam/docs/).", "id": "GoogleIamV1Policy", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelBaseModelSource": { "description": "User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models.", "properties": { "modelGardenSource": { "$ref": "GoogleCloudAiplatformV1beta1ModelGardenSource", "description": "Source information of Model Garden models." }, "genieSource": { "description": "Information about the base model of Genie models.", "$ref": "GoogleCloudAiplatformV1beta1GenieSource" } }, "id": "GoogleCloudAiplatformV1beta1ModelBaseModelSource", "type": "object" }, "GoogleCloudAiplatformV1beta1ListSavedQueriesResponse": { "id": "GoogleCloudAiplatformV1beta1ListSavedQueriesResponse", "type": "object", "properties": { "savedQueries": { "description": "A list of SavedQueries that match the specified filter in the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SavedQuery" } }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "description": "Response message for DatasetService.ListSavedQueries." }, "GoogleCloudAiplatformV1beta1PublisherModelConfig": { "properties": { "loggingConfig": { "description": "The prediction request/response logging config.", "$ref": "GoogleCloudAiplatformV1beta1PredictRequestResponseLoggingConfig" } }, "description": "This message contains configs of a publisher model.", "id": "GoogleCloudAiplatformV1beta1PublisherModelConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateModelMonitorOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1UpdateModelMonitorOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Runtime operation information for ModelMonitoringService.UpdateModelMonitor." }, "GoogleCloudAiplatformV1beta1ListNasTrialDetailsResponse": { "properties": { "nasTrialDetails": { "description": "List of top NasTrials in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NasTrialDetail" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListNasTrialDetailsRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for JobService.ListNasTrialDetails", "id": "GoogleCloudAiplatformV1beta1ListNasTrialDetailsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1RagManagedDbConfigScaled": { "id": "GoogleCloudAiplatformV1beta1RagManagedDbConfigScaled", "type": "object", "description": "Scaled tier offers production grade performance along with autoscaling functionality. It is suitable for customers with large amounts of data or performance sensitive workloads.", "properties": {} }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecStructuredPrompt": { "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecStructuredPrompt", "type": "object", "properties": { "examples": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecPartList" }, "description": "Preamble: A set of examples for expected model response." }, "predictionInputs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecPartList" }, "description": "Preamble: The input test data for prediction. Each PartList in this field represents one text-only input set for a single model request." }, "interactionData": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecInteractionData", "description": "Data for interaction use case." }, "context": { "description": "Preamble: The context of the prompt.", "$ref": "GoogleCloudAiplatformV1beta1Content" }, "infillPrefix": { "description": "Preamble: For infill prompt, the prefix before expected model response.", "type": "string" }, "appBuilderData": { "description": "Data for app builder use case.", "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecAppBuilderData" }, "inputPrefixes": { "type": "array", "items": { "type": "string" }, "description": "Preamble: The input prefixes before each example input." }, "infillSuffix": { "description": "Preamble: For infill prompt, the suffix after expected model response.", "type": "string" }, "promptMessage": { "$ref": "GoogleCloudAiplatformV1beta1SchemaPromptSpecPromptMessage", "description": "The prompt message." }, "outputPrefixes": { "description": "Preamble: The output prefixes before each example output.", "type": "array", "items": { "type": "string" } } }, "description": "Prompt variation that stores preambles in separate fields." }, "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences": { "id": "GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences", "type": "object", "description": "The regional resource name or the URI. Key is region, e.g., us-central1, europe-west2, global, etc..", "properties": { "supportsWorkbench": { "description": "Optional. For notebook resource, whether the notebook supports Workbench.", "type": "boolean" }, "title": { "description": "Required. ", "type": "string" }, "resourceTitle": { "description": "Optional. Title of the resource.", "type": "string" }, "references": { "description": "Required.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelResourceReference" } }, "resourceDescription": { "description": "Optional. Description of the resource.", "type": "string" }, "resourceUseCase": { "description": "Optional. Use case (CUJ) of the resource.", "type": "string" }, "colabNotebookDisabled": { "description": "Optional. For notebook resource. When set to true, the Colab Enterprise link will be disabled in the \"open notebook\" dialog in UI.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationOption": { "description": "Optional settings for translation prompt.", "properties": { "numberOfShots": { "type": "integer", "description": "How many shots to use.", "format": "int32" } }, "id": "GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationOption", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageClassificationPredictionParams": { "properties": { "confidenceThreshold": { "type": "number", "format": "float", "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0" }, "maxPredictions": { "type": "integer", "format": "int32", "description": "The Model only returns up to that many top, by confidence score, predictions per instance. If this number is very high, the Model may return fewer predictions. Default value is 10." } }, "description": "Prediction model parameters for Image Classification.", "id": "GoogleCloudAiplatformV1beta1SchemaPredictParamsImageClassificationPredictionParams", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolygonAnnotation": { "id": "GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolygonAnnotation", "type": "object", "description": "Represents a polygon in image.", "properties": { "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "vertexes": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaVertex" }, "description": "The vertexes are connected one by one and the last vertex is connected to the first one to represent a polygon." }, "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ExactMatchSpec": { "properties": {}, "description": "Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0.", "id": "GoogleCloudAiplatformV1beta1ExactMatchSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1DeploySolverOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1DeploySolverOperationMetadata", "type": "object", "description": "Runtime operation information for SolverService.DeploySolver.", "properties": { "genericMetadata": { "description": "The generic operation information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1beta1IndexPrivateEndpoints": { "id": "GoogleCloudAiplatformV1beta1IndexPrivateEndpoints", "type": "object", "properties": { "matchGrpcAddress": { "description": "Output only. The ip address used to send match gRPC requests.", "type": "string", "readOnly": true }, "pscAutomatedEndpoints": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PscAutomatedEndpoints" }, "description": "Output only. PscAutomatedEndpoints is populated if private service connect is enabled if PscAutomatedConfig is set." }, "serviceAttachment": { "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled.", "readOnly": true, "type": "string" } }, "description": "IndexPrivateEndpoints proto is used to provide paths for users to send requests via private endpoints (e.g. private service access, private service connect). To send request via private service access, use match_grpc_address. To send request via private service connect, use service_attachment." }, "GoogleCloudAiplatformV1beta1Metric": { "id": "GoogleCloudAiplatformV1beta1Metric", "type": "object", "description": "The metric used for running evaluations.", "properties": { "rougeSpec": { "$ref": "GoogleCloudAiplatformV1beta1RougeSpec", "description": "Spec for rouge metric." }, "computationBasedMetricSpec": { "$ref": "GoogleCloudAiplatformV1beta1ComputationBasedMetricSpec", "description": "Spec for a computation based metric." }, "exactMatchSpec": { "$ref": "GoogleCloudAiplatformV1beta1ExactMatchSpec", "description": "Spec for exact match metric." }, "predefinedMetricSpec": { "$ref": "GoogleCloudAiplatformV1beta1PredefinedMetricSpec", "description": "The spec for a pre-defined metric." }, "pointwiseMetricSpec": { "$ref": "GoogleCloudAiplatformV1beta1PointwiseMetricSpec", "description": "Spec for pointwise metric." }, "bleuSpec": { "$ref": "GoogleCloudAiplatformV1beta1BleuSpec", "description": "Spec for bleu metric." }, "metadata": { "$ref": "GoogleCloudAiplatformV1beta1MetricMetadata", "description": "Optional. Metadata about the metric, used for visualization and organization." }, "llmBasedMetricSpec": { "description": "Spec for an LLM based metric.", "$ref": "GoogleCloudAiplatformV1beta1LLMBasedMetricSpec" }, "customCodeExecutionSpec": { "$ref": "GoogleCloudAiplatformV1beta1CustomCodeExecutionSpec", "description": "Spec for Custom Code Execution metric." }, "pairwiseMetricSpec": { "$ref": "GoogleCloudAiplatformV1beta1PairwiseMetricSpec", "description": "Spec for pairwise metric." }, "aggregationMetrics": { "description": "Optional. The aggregation metrics to use.", "type": "array", "items": { "enum": [ "AGGREGATION_METRIC_UNSPECIFIED", "AVERAGE", "MODE", "STANDARD_DEVIATION", "VARIANCE", "MINIMUM", "MAXIMUM", "MEDIAN", "PERCENTILE_P90", "PERCENTILE_P95", "PERCENTILE_P99" ], "type": "string", "enumDescriptions": [ "Unspecified aggregation metric.", "Average aggregation metric. Not supported for Pairwise metric.", "Mode aggregation metric.", "Standard deviation aggregation metric. Not supported for pairwise metric.", "Variance aggregation metric. Not supported for pairwise metric.", "Minimum aggregation metric. Not supported for pairwise metric.", "Maximum aggregation metric. Not supported for pairwise metric.", "Median aggregation metric. Not supported for pairwise metric.", "90th percentile aggregation metric. Not supported for pairwise metric.", "95th percentile aggregation metric. Not supported for pairwise metric.", "99th percentile aggregation metric. Not supported for pairwise metric." ] } } } }, "GoogleCloudAiplatformV1beta1RubricVerdict": { "id": "GoogleCloudAiplatformV1beta1RubricVerdict", "type": "object", "properties": { "evaluatedRubric": { "$ref": "GoogleCloudAiplatformV1beta1Rubric", "description": "Required. The full rubric definition that was evaluated. Storing this ensures the verdict is self-contained and understandable, especially if the original rubric definition changes or was dynamically generated." }, "verdict": { "description": "Required. Outcome of the evaluation against the rubric, represented as a boolean. `true` indicates a \"Pass\", `false` indicates a \"Fail\".", "type": "boolean" }, "reasoning": { "description": "Optional. Human-readable reasoning or explanation for the verdict. This can include specific examples or details from the evaluated content that justify the given verdict.", "type": "string" } }, "description": "Represents the verdict of an evaluation against a single rubric." }, "GoogleCloudAiplatformV1beta1SearchExamplesResponseSimilarExample": { "description": "The result of the similar example.", "properties": { "example": { "description": "The example that is similar to the searched query.", "$ref": "GoogleCloudAiplatformV1beta1Example" }, "similarityScore": { "description": "The similarity score of this example.", "format": "float", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1SearchExamplesResponseSimilarExample", "type": "object" }, "GoogleCloudAiplatformV1beta1ContainerSpec": { "id": "GoogleCloudAiplatformV1beta1ContainerSpec", "type": "object", "description": "The spec of a Container.", "properties": { "command": { "description": "The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.", "type": "array", "items": { "type": "string" } }, "args": { "type": "array", "items": { "type": "string" }, "description": "The arguments to be passed when starting the container." }, "imageUri": { "description": "Required. The URI of a container image in the Container Registry that is to be run on each worker replica.", "type": "string" }, "env": { "description": "Environment variables to be passed to the container. Maximum limit is 100.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1EnvVar" } } } }, "GoogleCloudAiplatformV1beta1FunctionResponsePart": { "id": "GoogleCloudAiplatformV1beta1FunctionResponsePart", "type": "object", "properties": { "fileData": { "$ref": "GoogleCloudAiplatformV1beta1FunctionResponseFileData", "description": "URI based data." }, "inlineData": { "description": "Inline media bytes.", "$ref": "GoogleCloudAiplatformV1beta1FunctionResponseBlob" } }, "description": "A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes." }, "GoogleCloudAiplatformV1beta1ListFeatureViewSyncsResponse": { "id": "GoogleCloudAiplatformV1beta1ListFeatureViewSyncsResponse", "type": "object", "properties": { "featureViewSyncs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewSync" }, "description": "The FeatureViewSyncs matching the request." }, "nextPageToken": { "description": "A token, which can be sent as ListFeatureViewSyncsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureViewSyncs." }, "GoogleCloudAiplatformV1beta1IngestEventsRequest": { "properties": { "generationTriggerConfig": { "description": "Optional. Configuration for triggering memory generation from this ingestion. If not set, then the stream will be force flushed immediately.", "$ref": "GoogleCloudAiplatformV1beta1MemoryGenerationTriggerConfig" }, "scope": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Required. The scope of the memories that should be generated from the stream. Memories will be consolidated across memories with the same scope. Scope values cannot contain the wildcard character '*'." }, "streamId": { "description": "Optional. The ID of the stream to ingest events into. If not provided, a new one will be created.", "type": "string" }, "forceFlush": { "description": "Optional. Forces a flush of all pending events in the stream and triggers memory generation immediately bypassing any conditions configured in the `generation_trigger_config`.", "type": "boolean" }, "directContentsSource": { "$ref": "GoogleCloudAiplatformV1beta1IngestionDirectContentsSource", "description": "Ingest events directly from the request." } }, "description": "Request message for MemoryBankService.IngestEvents.", "id": "GoogleCloudAiplatformV1beta1IngestEventsRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker": { "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker", "type": "object", "description": "Config for LlmRanker.", "properties": { "modelName": { "description": "Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ExplanationParameters": { "properties": { "sampledShapleyAttribution": { "$ref": "GoogleCloudAiplatformV1beta1SampledShapleyAttribution", "description": "An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265." }, "examples": { "description": "Example-based explanations that returns the nearest neighbors from the provided dataset.", "$ref": "GoogleCloudAiplatformV1beta1Examples" }, "topK": { "type": "integer", "description": "If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.", "format": "int32" }, "integratedGradientsAttribution": { "$ref": "GoogleCloudAiplatformV1beta1IntegratedGradientsAttribution", "description": "An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365" }, "xraiAttribution": { "$ref": "GoogleCloudAiplatformV1beta1XraiAttribution", "description": "An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead." }, "outputIndices": { "type": "array", "items": { "type": "any" }, "description": "If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining. If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs. Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes)." } }, "description": "Parameters to configure explaining for Model's predictions.", "id": "GoogleCloudAiplatformV1beta1ExplanationParameters", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputs": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputs", "type": "object", "properties": { "availableAtForecastColumns": { "description": "Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day.", "type": "array", "items": { "type": "string" } }, "holidayRegions": { "description": "The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option.", "type": "array", "items": { "type": "string" } }, "trainBudgetMilliNodeHours": { "description": "Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive.", "format": "int64", "type": "string" }, "weightColumn": { "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1.", "type": "string" }, "forecastHorizon": { "type": "string", "description": "The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field.", "format": "int64" }, "contextWindow": { "type": "string", "format": "int64", "description": "The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field." }, "windowConfig": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig", "description": "Config containing strategy for generating sliding windows." }, "additionalExperiments": { "type": "array", "items": { "type": "string" }, "description": "Additional experiment flags for the time series forcasting training." }, "targetColumn": { "description": "The name of the column that the Model is to predict values for. This column must be unavailable at forecast.", "type": "string" }, "quantiles": { "description": "Quantiles to use for minimize-quantile-loss `optimization_objective`, or for probabilistic inference. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique.", "type": "array", "items": { "format": "double", "type": "number" } }, "unavailableAtForecastColumns": { "type": "array", "items": { "type": "string" }, "description": "Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day." }, "dataGranularity": { "description": "Expected difference in time granularity between rows in the data.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity" }, "transformations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation" }, "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter." }, "enableProbabilisticInference": { "description": "If probabilistic inference is enabled, the model will fit a distribution that captures the uncertainty of a prediction. At inference time, the predictive distribution is used to make a point prediction that minimizes the optimization objective. For example, the mean of a predictive distribution is the point prediction that minimizes RMSE loss. If quantiles are specified, then the quantiles of the distribution are also returned. The optimization objective cannot be minimize-quantile-loss.", "type": "boolean" }, "optimizationObjective": { "description": "Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). * \"minimize-mae\" - Minimize mean-absolute error (MAE). * \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE). * \"minimize-rmspe\" - Minimize root-mean-squared percentage error (RMSPE). * \"minimize-wape-mae\" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * \"minimize-quantile-loss\" - Minimize the quantile loss at the quantiles defined in `quantiles`. * \"minimize-mape\" - Minimize the mean absolute percentage error.", "type": "string" }, "timeSeriesIdentifierColumn": { "description": "The name of the column that identifies the time series.", "type": "string" }, "timeColumn": { "description": "The name of the column that identifies time order in the time series. This column must be available at forecast.", "type": "string" }, "validationOptions": { "description": "Validation options for the data validation component. The available options are: * \"fail-pipeline\" - default, will validate against the validation and fail the pipeline if it fails. * \"ignore-validation\" - ignore the results of the validation and continue", "type": "string" }, "exportEvaluatedDataItemsConfig": { "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig" }, "hierarchyConfig": { "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies.", "$ref": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig" }, "timeSeriesAttributeColumns": { "description": "Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.", "type": "array", "items": { "type": "string" } } } }, "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity": { "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity", "type": "object", "properties": { "mid": { "description": "MID of the label", "type": "string" }, "description": { "description": "Description of the label", "type": "string" }, "score": { "type": "number", "format": "float", "description": "Confidence score of the label" }, "iouScore": { "type": "number", "description": "The intersection ratio between the detection bounding box and the mask.", "format": "float" }, "boundingBox": { "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox", "description": "Bounding box of the label" } }, "description": "The properties for a detected entity from the rai signal." }, "GoogleCloudAiplatformV1beta1ConversationTurn": { "description": "Represents a single turn/invocation in the conversation.", "properties": { "turnId": { "description": "Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.", "type": "string" }, "events": { "description": "Optional. The list of events that occurred during this turn.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1AgentEvent" } }, "turnIndex": { "type": "integer", "description": "Required. The 0-based index of the turn in the conversation sequence.", "format": "int32" } }, "id": "GoogleCloudAiplatformV1beta1ConversationTurn", "type": "object" }, "GoogleCloudAiplatformV1beta1Transcription": { "properties": { "text": { "description": "Optional. Transcription text.", "type": "string" }, "finished": { "description": "Optional. The bool indicates the end of the transcription.", "type": "boolean" } }, "description": "Audio transcription in Server Content.", "id": "GoogleCloudAiplatformV1beta1Transcription", "type": "object" }, "GoogleCloudAiplatformV1beta1ListSpecialistPoolsResponse": { "properties": { "specialistPools": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SpecialistPool" }, "description": "A list of SpecialistPools that matches the specified filter in the request." }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "description": "Response message for SpecialistPoolService.ListSpecialistPools.", "id": "GoogleCloudAiplatformV1beta1ListSpecialistPoolsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataGcsSource": { "properties": { "uri": { "description": "Cloud Storage URI of one or more files. Only CSV files are supported. The first line of the CSV file is used as the header. If there are multiple files, the header is the first line of the lexicographically first file, the other files must either contain the exact same header or omit the header.", "type": "array", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataGcsSource", "type": "object" }, "GoogleCloudAiplatformV1beta1IdMatcher": { "id": "GoogleCloudAiplatformV1beta1IdMatcher", "type": "object", "properties": { "ids": { "type": "array", "items": { "type": "string" }, "description": "Required. The following are accepted as `ids`: * A single-element list containing only `*`, which selects all Features in the target EntityType, or * A list containing only Feature IDs, which selects only Features with those IDs in the target EntityType." } }, "description": "Matcher for Features of an EntityType by Feature ID." }, "GoogleCloudAiplatformV1beta1RemoveContextChildrenRequest": { "id": "GoogleCloudAiplatformV1beta1RemoveContextChildrenRequest", "type": "object", "properties": { "childContexts": { "type": "array", "items": { "type": "string" }, "description": "The resource names of the child Contexts." } }, "description": "Request message for MetadataService.DeleteContextChildrenRequest." }, "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestPassThroughField": { "properties": { "fieldName": { "description": "Required. The name of the field in the CSV header or the name of the column in BigQuery table. The naming restriction is the same as Feature.name.", "type": "string" } }, "description": "Describe pass-through fields in read_instance source.", "id": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestPassThroughField", "type": "object" }, "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInstance": { "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInstance", "type": "object", "description": "Spec for question answering helpfulness instance.", "properties": { "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" }, "context": { "description": "Optional. Text provided as context to answer the question.", "type": "string" }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "instruction": { "description": "Required. The question asked and other instruction in the inference prompt.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpec": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpec", "type": "object", "description": "Notification spec(email, notification channel) for model monitoring statistics/alerts.", "properties": { "emailConfig": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecEmailConfig", "description": "Email alert config." }, "notificationChannelConfigs": { "description": "Notification channel config.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecNotificationChannelConfig" } }, "enableCloudLogging": { "description": "Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1SyntheticExample": { "properties": { "fields": { "description": "Required. A list of fields that constitute an example.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SyntheticField" } } }, "description": "A single instance of generated synthetic data. Each example is made up of one or more named fields, as defined in `OutputFieldSpec`. These examples are used as few-shot examples to show the model what you want (in `GenerateSyntheticDataRequest.examples`) and to return generated examples in the response (in `GenerateSyntheticDataResponse.synthetic_examples`).", "id": "GoogleCloudAiplatformV1beta1SyntheticExample", "type": "object" }, "GoogleCloudAiplatformV1beta1ExtensionManifestApiSpec": { "id": "GoogleCloudAiplatformV1beta1ExtensionManifestApiSpec", "type": "object", "properties": { "openApiYaml": { "description": "The API spec in Open API standard and YAML format.", "type": "string" }, "openApiGcsUri": { "description": "Cloud Storage URI pointing to the OpenAPI spec.", "type": "string" } }, "description": "The API specification shown to the LLM." }, "GoogleCloudAiplatformV1beta1FulfillmentInput": { "id": "GoogleCloudAiplatformV1beta1FulfillmentInput", "type": "object", "properties": { "instance": { "description": "Required. Fulfillment instance.", "$ref": "GoogleCloudAiplatformV1beta1FulfillmentInstance" }, "metricSpec": { "description": "Required. Spec for fulfillment score metric.", "$ref": "GoogleCloudAiplatformV1beta1FulfillmentSpec" } }, "description": "Input for fulfillment metric." }, "GoogleCloudAiplatformV1beta1CancelNasJobRequest": { "id": "GoogleCloudAiplatformV1beta1CancelNasJobRequest", "type": "object", "description": "Request message for JobService.CancelNasJob.", "properties": {} }, "GoogleCloudAiplatformV1beta1FeatureViewSyncConfig": { "properties": { "continuous": { "description": "Optional. If true, syncs the FeatureView in a continuous manner to Online Store.", "type": "boolean" }, "cron": { "description": "Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: \"CRON_TZ=${IANA_TIME_ZONE}\" or \"TZ=${IANA_TIME_ZONE}\". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, \"CRON_TZ=America/New_York 1 * * * *\", or \"TZ=America/New_York 1 * * * *\".", "type": "string" } }, "description": "Configuration for Sync. Only one option is set.", "id": "GoogleCloudAiplatformV1beta1FeatureViewSyncConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1AsyncRetrieveContextsRequest": { "id": "GoogleCloudAiplatformV1beta1AsyncRetrieveContextsRequest", "type": "object", "description": "Request message for VertexRagService.AsyncRetrieveContexts.", "properties": { "query": { "description": "Required. Single RAG retrieve query.", "$ref": "GoogleCloudAiplatformV1beta1RagQuery" }, "tools": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" }, "description": "Optional. The tools to use for AskContexts." } } }, "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceSpec": { "properties": { "useReference": { "description": "Optional. Whether to use instance.reference to compute question answering relevance.", "type": "boolean" }, "version": { "type": "integer", "description": "Optional. Which version to use for evaluation.", "format": "int32" } }, "description": "Spec for question answering relevance metric.", "id": "GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1DeployRequestDeployConfig": { "properties": { "dedicatedResources": { "$ref": "GoogleCloudAiplatformV1beta1DedicatedResources", "description": "Optional. The dedicated resources to use for the endpoint. If not set, the default resources will be used." }, "fastTryoutEnabled": { "description": "Optional. If true, enable the QMT fast tryout feature for this model if possible.", "type": "boolean" }, "systemLabels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. System labels for Model Garden deployments. These labels are managed by Google and for tracking purposes only." } }, "description": "The deploy config to use for the deployment.", "id": "GoogleCloudAiplatformV1beta1DeployRequestDeployConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation": { "properties": { "columnName": { "type": "string" } }, "description": "Training pipeline will infer the proper transformation based on the statistic of dataset.", "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation", "type": "object" }, "GoogleCloudAiplatformV1beta1CompletionStats": { "properties": { "successfulForecastPointCount": { "type": "string", "readOnly": true, "description": "Output only. The number of the successful forecast points that are generated by the forecasting model. This is ONLY used by the forecasting batch prediction.", "format": "int64" }, "successfulCount": { "description": "Output only. The number of entities that had been processed successfully.", "format": "int64", "type": "string", "readOnly": true }, "failedCount": { "readOnly": true, "type": "string", "format": "int64", "description": "Output only. The number of entities for which any error was encountered." }, "incompleteCount": { "description": "Output only. In cases when enough errors are encountered a job, pipeline, or operation may be failed as a whole. Below is the number of entities for which the processing had not been finished (either in successful or failed state). Set to -1 if the number is unknown (for example, the operation failed before the total entity number could be collected).", "format": "int64", "type": "string", "readOnly": true } }, "description": "Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.", "id": "GoogleCloudAiplatformV1beta1CompletionStats", "type": "object" }, "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInput": { "id": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInput", "type": "object", "description": "Input for pairwise question answering quality metric.", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualitySpec", "description": "Required. Spec for pairwise question answering quality score metric." }, "instance": { "$ref": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInstance", "description": "Required. Pairwise question answering quality instance." } } }, "GoogleCloudAiplatformV1beta1PartnerModelTuningSpec": { "id": "GoogleCloudAiplatformV1beta1PartnerModelTuningSpec", "type": "object", "properties": { "trainingDatasetUri": { "description": "Required. Cloud Storage path to file containing training dataset for tuning. The dataset must be formatted as a JSONL file.", "type": "string" }, "validationDatasetUri": { "description": "Optional. Cloud Storage path to file containing validation dataset for tuning. The dataset must be formatted as a JSONL file.", "type": "string" }, "hyperParameters": { "description": "Hyperparameters for tuning. The accepted hyper_parameters and their valid range of values will differ depending on the base model.", "type": "object", "additionalProperties": { "type": "any" } } }, "description": "Tuning spec for Partner models." }, "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig", "type": "object", "properties": { "attributionScoreDriftThresholds": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig" }, "description": "Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows." }, "defaultDriftThreshold": { "description": "Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.", "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig" }, "driftThresholds": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1ThresholdConfig" }, "description": "Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws." } }, "description": "The config for Prediction data drift detection." }, "GoogleCloudAiplatformV1beta1ToolParameterKVMatchResults": { "id": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchResults", "type": "object", "properties": { "toolParameterKvMatchMetricValues": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ToolParameterKVMatchMetricValue" }, "description": "Output only. Tool parameter key value match metric values." } }, "description": "Results for tool parameter key value match metric." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata": { "properties": { "costMilliNodeHours": { "description": "The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours.", "format": "int64", "type": "string" }, "successfulStopReason": { "enum": [ "SUCCESSFUL_STOP_REASON_UNSPECIFIED", "BUDGET_REACHED", "MODEL_CONVERGED" ], "description": "For successful job completions, this is the reason why the job has finished.", "type": "string", "enumDescriptions": [ "Should not be set.", "The inputs.budgetMilliNodeHours had been reached.", "Further training of the Model ceased to increase its quality, since it already has converged." ] } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata", "type": "object" }, "GoogleCloudAiplatformV1beta1ImportIndexRequest": { "id": "GoogleCloudAiplatformV1beta1ImportIndexRequest", "type": "object", "properties": { "isCompleteOverwrite": { "description": "Optional. If true, completely replace existing index data. Must be true for streaming update indexes.", "type": "boolean" }, "config": { "description": "Required. Configuration for importing data from an external source.", "$ref": "GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfig" } }, "description": "Request message for IndexService.ImportIndex." }, "GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsRequest": { "id": "GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsRequest", "type": "object", "description": "Request message for PipelineService.BatchCancelPipelineJobs.", "properties": { "names": { "description": "Required. The names of the PipelineJobs to cancel. A maximum of 32 PipelineJobs can be cancelled in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}`", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1SharePointSources": { "id": "GoogleCloudAiplatformV1beta1SharePointSources", "type": "object", "description": "The SharePointSources to pass to ImportRagFiles.", "properties": { "sharePointSources": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SharePointSourcesSharePointSource" }, "description": "The SharePoint sources." } } }, "GoogleCloudAiplatformV1beta1NearestNeighbors": { "description": "Nearest neighbors for one query.", "properties": { "neighbors": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1NearestNeighborsNeighbor" }, "description": "All its neighbors." } }, "id": "GoogleCloudAiplatformV1beta1NearestNeighbors", "type": "object" }, "GoogleCloudAiplatformV1beta1CitationMetadata": { "id": "GoogleCloudAiplatformV1beta1CitationMetadata", "type": "object", "properties": { "citations": { "description": "Output only. A list of citations for the content.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Citation" }, "readOnly": true } }, "description": "A collection of citations that apply to a piece of generated content." }, "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequest": { "id": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequest", "type": "object", "properties": { "pageSize": { "type": "integer", "format": "int32", "description": "The standard list page size." }, "startTime": { "description": "The earliest timestamp of stats being generated. If not set, indicates fetching stats till the earliest possible one.", "format": "google-datetime", "type": "string" }, "objectives": { "description": "Required. Objectives of the stats to retrieve.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective" } }, "endTime": { "type": "string", "format": "google-datetime", "description": "The latest timestamp of stats being generated. If not set, indicates feching stats till the latest possible one." }, "featureDisplayName": { "description": "The feature display name. If specified, only return the stats belonging to this feature. Format: ModelMonitoringStatsAnomalies.FeatureHistoricStatsAnomalies.feature_display_name, example: \"user_destination\".", "type": "string" }, "pageToken": { "description": "A page token received from a previous JobService.SearchModelDeploymentMonitoringStatsAnomalies call.", "type": "string" }, "deployedModelId": { "description": "Required. The DeployedModel ID of the [ModelDeploymentMonitoringObjectiveConfig.deployed_model_id].", "type": "string" } }, "description": "Request message for JobService.SearchModelDeploymentMonitoringStatsAnomalies." }, "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStoreRagResource": { "description": "The definition of the Rag resource.", "properties": { "ragCorpus": { "description": "Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "type": "string" }, "ragFileIds": { "type": "array", "items": { "type": "string" }, "description": "Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field." } }, "id": "GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStoreRagResource", "type": "object" }, "GoogleCloudAiplatformV1beta1UpdateFeatureViewOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1UpdateFeatureViewOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "Operation metadata for FeatureView Update.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Details of operations that perform update FeatureView." }, "GoogleCloudAiplatformV1beta1ListAnnotationsResponse": { "id": "GoogleCloudAiplatformV1beta1ListAnnotationsResponse", "type": "object", "properties": { "annotations": { "description": "A list of Annotations that matches the specified filter in the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Annotation" } }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "description": "Response message for DatasetService.ListAnnotations." }, "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInstance": { "properties": { "prediction": { "description": "Required. Output of the candidate model.", "type": "string" }, "baselinePrediction": { "description": "Required. Output of the baseline model.", "type": "string" }, "instruction": { "description": "Required. Summarization prompt for LLM.", "type": "string" }, "context": { "description": "Required. Text to be summarized.", "type": "string" }, "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" } }, "description": "Spec for pairwise summarization quality instance.", "id": "GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1ModelMonitoringInput": { "id": "GoogleCloudAiplatformV1beta1ModelMonitoringInput", "type": "object", "properties": { "columnizedDataset": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDataset", "description": "Columnized dataset." }, "vertexEndpointLogs": { "description": "Vertex AI Endpoint request & response logging.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputVertexEndpointLogs" }, "timeOffset": { "description": "The time offset setting for which results should be returned.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputTimeOffset" }, "batchPredictionOutput": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringInputBatchPredictionOutput", "description": "Vertex AI Batch prediction Job." }, "timeInterval": { "$ref": "GoogleTypeInterval", "description": "The time interval (pair of start_time and end_time) for which results should be returned." } }, "description": "Model monitoring data input spec." }, "GoogleCloudAiplatformV1beta1SyncFeatureViewRequest": { "properties": {}, "description": "Request message for FeatureOnlineStoreAdminService.SyncFeatureView.", "id": "GoogleCloudAiplatformV1beta1SyncFeatureViewRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ListStudiesResponse": { "description": "Response message for VizierService.ListStudies.", "properties": { "studies": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Study" }, "description": "The studies associated with the project." }, "nextPageToken": { "description": "Passes this token as the `page_token` field of the request for a subsequent call. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListStudiesResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1ExportModelRequestOutputConfig": { "properties": { "artifactDestination": { "description": "The Cloud Storage location where the Model artifact is to be written to. Under the directory given as the destination a new one with name \"`model-export--`\", where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format, will be created. Inside, the Model and any of its supporting files will be written. This field should only be set when the `exportableContent` field of the [Model.supported_export_formats] object contains `ARTIFACT`.", "$ref": "GoogleCloudAiplatformV1beta1GcsDestination" }, "imageDestination": { "$ref": "GoogleCloudAiplatformV1beta1ContainerRegistryDestination", "description": "The Google Container Registry or Artifact Registry uri where the Model container image will be copied to. This field should only be set when the `exportableContent` field of the [Model.supported_export_formats] object contains `IMAGE`." }, "exportFormatId": { "description": "The ID of the format in which the Model must be exported. Each Model lists the export formats it supports. If no value is provided here, then the first from the list of the Model's supported formats is used by default.", "type": "string" } }, "description": "Output configuration for the Model export.", "id": "GoogleCloudAiplatformV1beta1ExportModelRequestOutputConfig", "type": "object" }, "GoogleCloudAiplatformV1beta1SandboxEnvironmentSpec": { "description": "The specification of a SandboxEnvironment.", "properties": { "computerUseEnvironment": { "description": "Optional. The computer use environment.", "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSpecComputerUseEnvironment" }, "codeExecutionEnvironment": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSpecCodeExecutionEnvironment", "description": "Optional. The code execution environment." } }, "id": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSpec", "type": "object" }, "GoogleCloudAiplatformV1beta1IndexDatapointSparseEmbedding": { "id": "GoogleCloudAiplatformV1beta1IndexDatapointSparseEmbedding", "type": "object", "properties": { "values": { "type": "array", "items": { "type": "number", "format": "float" }, "description": "Required. The list of embedding values of the sparse vector." }, "dimensions": { "description": "Required. The list of indexes for the embedding values of the sparse vector.", "type": "array", "items": { "format": "int64", "type": "string" } } }, "description": "Feature embedding vector for sparse index. An array of numbers whose values are located in the specified dimensions." }, "GoogleCloudAiplatformV1beta1GenerateAccessTokenResponse": { "description": "Response message for NotebookInternalService.GenerateToken.", "properties": { "expiresIn": { "format": "int32", "description": "The time in seconds when the access token expires. Typically that's 3600.", "type": "integer" }, "tokenType": { "description": "Type of the returned access token (e.g. \"Bearer\"). It specifies how the token must be used. Bearer tokens may be used by any entity without proof of identity.", "type": "string" }, "accessToken": { "description": "Short-lived access token string which may be used to access Google APIs.", "type": "string" }, "scope": { "description": "Space-separated list of scopes contained in the returned token. https://cloud.google.com/docs/authentication/token-types#access-contents", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1GenerateAccessTokenResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateFeatureGroupOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateFeatureGroupOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "Operation metadata for FeatureGroup.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" } }, "description": "Details of operations that perform create FeatureGroup." }, "GoogleCloudAiplatformV1beta1ListDatasetVersionsResponse": { "description": "Response message for DatasetService.ListDatasetVersions.", "properties": { "datasetVersions": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" }, "description": "A list of DatasetVersions that matches the specified filter in the request." }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ListDatasetVersionsResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1PublisherModelDocumentation": { "id": "GoogleCloudAiplatformV1beta1PublisherModelDocumentation", "type": "object", "properties": { "title": { "description": "Required. E.g., OVERVIEW, USE CASES, DOCUMENTATION, SDK & SAMPLES, JAVA, NODE.JS, etc..", "type": "string" }, "content": { "description": "Required. Content of this piece of document (in Markdown format).", "type": "string" } }, "description": "A named piece of documentation." }, "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageSegmentationPredictionInstance": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageSegmentationPredictionInstance", "type": "object", "properties": { "content": { "description": "The image bytes to make the predictions on.", "type": "string" }, "mimeType": { "description": "The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/png", "type": "string" } }, "description": "Prediction input format for Image Segmentation." }, "GoogleCloudAiplatformV1beta1StreamingPredictResponse": { "properties": { "parameters": { "$ref": "GoogleCloudAiplatformV1beta1Tensor", "description": "The parameters that govern the prediction." }, "outputs": { "description": "The prediction output.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tensor" } } }, "description": "Response message for PredictionService.StreamingPredict.", "id": "GoogleCloudAiplatformV1beta1StreamingPredictResponse", "type": "object" }, "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityResult": { "id": "GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityResult", "type": "object", "properties": { "pairwiseChoice": { "readOnly": true, "type": "string", "enumDescriptions": [ "Unspecified prediction choice.", "Baseline prediction wins", "Candidate prediction wins", "Winner cannot be determined" ], "enum": [ "PAIRWISE_CHOICE_UNSPECIFIED", "BASELINE", "CANDIDATE", "TIE" ], "description": "Output only. Pairwise question answering prediction choice." }, "confidence": { "type": "number", "readOnly": true, "description": "Output only. Confidence for question answering quality score.", "format": "float" }, "explanation": { "description": "Output only. Explanation for question answering quality score.", "readOnly": true, "type": "string" } }, "description": "Spec for pairwise question answering quality result." }, "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlDatasetConfig": { "id": "GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlDatasetConfig", "type": "object", "properties": { "dataset": { "description": "Required. Full resource name of automl Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`.", "type": "string" }, "datasetDisplayName": { "description": "Required. Display name of the Dataset in Vertex AI. System will pick a display name if unspecified.", "type": "string" } }, "description": "Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset." }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs": { "properties": { "modelType": { "enum": [ "MODEL_TYPE_UNSPECIFIED", "CLOUD", "MOBILE_VERSATILE_1", "MOBILE_CORAL_VERSATILE_1", "MOBILE_CORAL_LOW_LATENCY_1", "MOBILE_JETSON_VERSATILE_1", "MOBILE_JETSON_LOW_LATENCY_1" ], "type": "string", "enumDescriptions": [ "Should not be set.", "A model best tailored to be used within Google Cloud, and which c annot be exported. Default.", "A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards.", "A versatile model that is meant to be exported (see ModelService.ExportModel) and used on a Google Coral device.", "A model that trades off quality for low latency, to be exported (see ModelService.ExportModel) and used on a Google Coral device.", "A versatile model that is meant to be exported (see ModelService.ExportModel) and used on an NVIDIA Jetson device.", "A model that trades off quality for low latency, to be exported (see ModelService.ExportModel) and used on an NVIDIA Jetson device." ] } }, "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs", "type": "object" }, "GoogleCloudAiplatformV1beta1SummarizationVerbosityInstance": { "description": "Spec for summarization verbosity instance.", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "instruction": { "description": "Optional. Summarization prompt for LLM.", "type": "string" }, "context": { "description": "Required. Text to be summarized.", "type": "string" }, "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SummarizationVerbosityInstance", "type": "object" }, "GoogleCloudAiplatformV1beta1CachedContent": { "properties": { "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. When the cache entry was last updated in UTC time." }, "createTime": { "description": "Output only. Creation time of the cache entry.", "format": "google-datetime", "type": "string", "readOnly": true }, "toolConfig": { "description": "Optional. Input only. Immutable. Tool config. This config is shared for all tools", "$ref": "GoogleCloudAiplatformV1beta1ToolConfig" }, "usageMetadata": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1CachedContentUsageMetadata", "description": "Output only. Metadata on the usage of the cached content." }, "tools": { "description": "Optional. Input only. Immutable. A list of `Tools` the model may use to generate the next response", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" } }, "ttl": { "type": "string", "description": "Input only. The TTL for this resource. The expiration time is computed: now + TTL.", "format": "google-duration" }, "encryptionSpec": { "description": "Input only. Immutable. Customer-managed encryption key spec for a `CachedContent`. If set, this `CachedContent` and all its sub-resources will be secured by this key.", "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec" }, "name": { "description": "Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}", "type": "string" }, "systemInstruction": { "$ref": "GoogleCloudAiplatformV1beta1Content", "description": "Optional. Input only. Immutable. Developer set system instruction. Currently, text only" }, "model": { "description": "Immutable. The name of the `Model` to use for cached content. Currently, only the published Gemini base models are supported, in form of projects/{PROJECT}/locations/{LOCATION}/publishers/google/models/{MODEL}", "type": "string" }, "contents": { "description": "Optional. Input only. Immutable. The content to cache", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "expireTime": { "format": "google-datetime", "description": "Timestamp of when this resource is considered expired. This is *always* provided on output, regardless of what was sent on input.", "type": "string" }, "displayName": { "description": "Optional. Immutable. The user-generated meaningful display name of the cached content.", "type": "string" } }, "description": "A resource used in LLM queries for users to explicitly specify what to cache and how to cache.", "id": "GoogleCloudAiplatformV1beta1CachedContent", "type": "object" }, "GoogleCloudAiplatformV1beta1SuggestTrialsRequest": { "properties": { "suggestionCount": { "description": "Required. The number of suggestions requested. It must be positive.", "format": "int32", "type": "integer" }, "clientId": { "description": "Required. The identifier of the client that is requesting the suggestion. If multiple SuggestTrialsRequests have the same `client_id`, the service will return the identical suggested Trial if the Trial is pending, and provide a new Trial if the last suggested Trial was completed.", "type": "string" }, "contexts": { "description": "Optional. This allows you to specify the \"context\" for a Trial; a context is a slice (a subspace) of the search space. Typical uses for contexts: 1) You are using Vizier to tune a server for best performance, but there's a strong weekly cycle. The context specifies the day-of-week. This allows Tuesday to generalize from Wednesday without assuming that everything is identical. 2) Imagine you're optimizing some medical treatment for people. As they walk in the door, you know certain facts about them (e.g. sex, weight, height, blood-pressure). Put that information in the context, and Vizier will adapt its suggestions to the patient. 3) You want to do a fair A/B test efficiently. Specify the \"A\" and \"B\" conditions as contexts, and Vizier will generalize between \"A\" and \"B\" conditions. If they are similar, this will allow Vizier to converge to the optimum faster than if \"A\" and \"B\" were separate Studies. NOTE: You can also enter contexts as REQUESTED Trials, e.g. via the CreateTrial() RPC; that's the asynchronous option where you don't need a close association between contexts and suggestions. NOTE: All the Parameters you set in a context MUST be defined in the Study. NOTE: You must supply 0 or $suggestion_count contexts. If you don't supply any contexts, Vizier will make suggestions from the full search space specified in the StudySpec; if you supply a full set of context, each suggestion will match the corresponding context. NOTE: A Context with no features set matches anything, and allows suggestions from the full search space. NOTE: Contexts MUST lie within the search space specified in the StudySpec. It's an error if they don't. NOTE: Contexts preferentially match ACTIVE then REQUESTED trials before new suggestions are generated. NOTE: Generation of suggestions involves a match between a Context and (optionally) a REQUESTED trial; if that match is not fully specified, a suggestion will be geneated in the merged subspace.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1TrialContext" } } }, "description": "Request message for VizierService.SuggestTrials.", "id": "GoogleCloudAiplatformV1beta1SuggestTrialsRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1FindNeighborsRequestQueryRRF": { "properties": { "alpha": { "description": "Required. Users can provide an alpha value to give more weight to dense vs sparse results. For example, if the alpha is 0, we only return sparse and if the alpha is 1, we only return dense.", "format": "float", "type": "number" } }, "description": "Parameters for RRF algorithm that combines search results.", "id": "GoogleCloudAiplatformV1beta1FindNeighborsRequestQueryRRF", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchPredictionJob": { "properties": { "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1beta1EncryptionSpec", "description": "Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key." }, "labels": { "description": "The labels with user-defined metadata to organize BatchPredictionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", "type": "object", "additionalProperties": { "type": "string" } }, "endTime": { "description": "Output only. Time when the BatchPredictionJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", "format": "google-datetime", "type": "string", "readOnly": true }, "updateTime": { "format": "google-datetime", "description": "Output only. Time when the BatchPredictionJob was most recently updated.", "readOnly": true, "type": "string" }, "modelMonitoringStatus": { "description": "Output only. The running status of the model monitoring pipeline.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the BatchPredictionJob was created." }, "startTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state." }, "displayName": { "description": "Required. The user-defined name of this BatchPredictionJob.", "type": "string" }, "disableContainerLogging": { "description": "For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.", "type": "boolean" }, "serviceAccount": { "description": "The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.", "type": "string" }, "instanceConfig": { "description": "Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.", "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJobInstanceConfig" }, "name": { "type": "string", "readOnly": true, "description": "Output only. Resource name of the BatchPredictionJob." }, "manualBatchTuningParameters": { "description": "Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself).", "$ref": "GoogleCloudAiplatformV1beta1ManualBatchTuningParameters" }, "completionStats": { "description": "Output only. Statistics on completed and failed prediction instances.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1CompletionStats" }, "modelMonitoringConfig": { "description": "Model monitoring config will be used for analysis model behaviors, based on the input and output to the batch prediction job, as well as the provided training dataset.", "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringConfig" }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "partialFailures": { "type": "array", "items": { "$ref": "GoogleRpcStatus" }, "readOnly": true, "description": "Output only. Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard Google Cloud error details." }, "modelVersionId": { "description": "Output only. The version ID of the Model that produces the predictions via this job.", "type": "string", "readOnly": true }, "outputInfo": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputInfo", "description": "Output only. Information further describing the output of this job." }, "unmanagedContainerModel": { "$ref": "GoogleCloudAiplatformV1beta1UnmanagedContainerModel", "description": "Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model, unmanaged_container_model, or endpoint must be set." }, "error": { "description": "Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "dedicatedResources": { "$ref": "GoogleCloudAiplatformV1beta1BatchDedicatedResources", "description": "The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided." }, "generateExplanation": { "description": "Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.", "type": "boolean" }, "modelParameters": { "description": "The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.", "type": "any" }, "state": { "description": "Output only. The detailed state of the job.", "enum": [ "JOB_STATE_UNSPECIFIED", "JOB_STATE_QUEUED", "JOB_STATE_PENDING", "JOB_STATE_RUNNING", "JOB_STATE_SUCCEEDED", "JOB_STATE_FAILED", "JOB_STATE_CANCELLING", "JOB_STATE_CANCELLED", "JOB_STATE_PAUSED", "JOB_STATE_EXPIRED", "JOB_STATE_UPDATING", "JOB_STATE_PARTIALLY_SUCCEEDED" ], "type": "string", "enumDescriptions": [ "The job state is unspecified.", "The job has been just created or resumed and processing has not yet begun.", "The service is preparing to run the job.", "The job is in progress.", "The job completed successfully.", "The job failed.", "The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "The job has been cancelled.", "The job has been stopped, and can be resumed.", "The job has expired.", "The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state.", "The job is partially succeeded, some results may be missing due to errors." ], "readOnly": true }, "resourcesConsumed": { "description": "Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1ResourcesConsumed" }, "inputConfig": { "description": "Required. Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.", "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJobInputConfig" }, "modelMonitoringStatsAnomalies": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies" }, "description": "Get batch prediction job monitoring statistics." }, "explanationSpec": { "$ref": "GoogleCloudAiplatformV1beta1ExplanationSpec", "description": "Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited." }, "model": { "description": "The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model, unmanaged_container_model, or endpoint must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "type": "string" }, "outputConfig": { "description": "Required. The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.", "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJobOutputConfig" }, "satisfiesPzs": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." } }, "description": "A job that uses a Model to produce predictions on multiple input instances. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.", "id": "GoogleCloudAiplatformV1beta1BatchPredictionJob", "type": "object" }, "GoogleCloudAiplatformV1beta1CreateEndpointOperationMetadata": { "id": "GoogleCloudAiplatformV1beta1CreateEndpointOperationMetadata", "type": "object", "description": "Runtime operation information for EndpointService.CreateEndpoint.", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1beta1GenericOperationMetadata" }, "deploymentStage": { "enum": [ "DEPLOYMENT_STAGE_UNSPECIFIED", "STARTING_DEPLOYMENT", "PREPARING_MODEL", "CREATING_SERVING_CLUSTER", "ADDING_NODES_TO_CLUSTER", "GETTING_CONTAINER_IMAGE", "STARTING_MODEL_SERVER", "FINISHING_UP", "DEPLOYMENT_TERMINATED", "SUCCESSFULLY_DEPLOYED", "FAILED_TO_DEPLOY" ], "description": "Output only. The deployment stage of the model. Only populated if this CreateEndpoint request deploys a model at the same time.", "readOnly": true, "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "The deployment is initializing and setting up the environment.", "The deployment is preparing the model assets.", "The deployment is creating the underlying serving cluster.", "The deployment is adding nodes to the serving cluster.", "The deployment is getting the container image for the model server.", "The deployment is starting the model server.", "The deployment is performing finalization steps.", "The deployment has terminated.", "The deployment has succeeded.", "The deployment has failed." ] } } }, "GoogleLongrunningOperation": { "description": "This resource represents a long-running operation that is the result of a network API call.", "properties": { "name": { "description": "The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.", "type": "string" }, "error": { "description": "The error result of the operation in case of failure or cancellation.", "$ref": "GoogleRpcStatus" }, "metadata": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." }, "description": "Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any." }, "done": { "description": "If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.", "type": "boolean" }, "response": { "description": "The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." } } }, "id": "GoogleLongrunningOperation", "type": "object" }, "GoogleCloudAiplatformV1beta1BatchCreateRagMetadataRequest": { "description": "Request message for VertexRagDataService.BatchCreateRagMetadata.", "properties": { "requests": { "description": "Required. The request messages for VertexRagDataService.CreateRagMetadata. A maximum of 500 rag file metadata can be created in a batch.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1CreateRagMetadataRequest" } } }, "id": "GoogleCloudAiplatformV1beta1BatchCreateRagMetadataRequest", "type": "object" }, "GoogleCloudAiplatformV1beta1ExamplesOverride": { "properties": { "returnEmbeddings": { "description": "If true, return the embeddings instead of neighbors.", "type": "boolean" }, "crowdingCount": { "format": "int32", "description": "The number of neighbors to return that have the same crowding tag.", "type": "integer" }, "neighborCount": { "type": "integer", "format": "int32", "description": "The number of neighbors to return." }, "restrictions": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ExamplesRestrictionsNamespace" }, "description": "Restrict the resulting nearest neighbors to respect these constraints." }, "dataFormat": { "type": "string", "enumDescriptions": [ "Unspecified format. Must not be used.", "Provided data is a set of model inputs.", "Provided data is a set of embeddings." ], "description": "The format of the data being provided with each call.", "enum": [ "DATA_FORMAT_UNSPECIFIED", "INSTANCES", "EMBEDDINGS" ] } }, "description": "Overrides for example-based explanations.", "id": "GoogleCloudAiplatformV1beta1ExamplesOverride", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoClassificationPredictionInstance": { "id": "GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoClassificationPredictionInstance", "type": "object", "description": "Prediction input format for Video Classification.", "properties": { "mimeType": { "description": "The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime", "type": "string" }, "timeSegmentEnd": { "description": "The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision, and \"inf\" or \"Infinity\" is allowed, which means the end of the video.", "type": "string" }, "content": { "description": "The Google Cloud Storage location of the video on which to perform the prediction.", "type": "string" }, "timeSegmentStart": { "description": "The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with \"s\" appended at the end. Fractions are allowed, up to a microsecond precision.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1GcsDestination": { "id": "GoogleCloudAiplatformV1beta1GcsDestination", "type": "object", "properties": { "outputUriPrefix": { "description": "Required. Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.", "type": "string" } }, "description": "The Google Cloud Storage location where the output is to be written to." }, "GoogleCloudAiplatformV1beta1SchemaTextSentimentAnnotation": { "description": "Annotation details specific to text sentiment.", "properties": { "sentimentMax": { "type": "integer", "description": "The sentiment max score for text.", "format": "int32" }, "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "sentiment": { "type": "integer", "description": "The sentiment score for text.", "format": "int32" }, "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1SchemaTextSentimentAnnotation", "type": "object" }, "GoogleCloudAiplatformV1beta1FileStatus": { "properties": { "errorStatus": { "readOnly": true, "type": "string", "description": "Output only. Only when the `state` field is ERROR." }, "state": { "enum": [ "STATE_UNSPECIFIED", "ACTIVE", "ERROR" ], "description": "Output only. RagFile state.", "readOnly": true, "type": "string", "enumDescriptions": [ "RagFile state is unspecified.", "RagFile resource has been created and indexed successfully.", "RagFile resource is in a problematic state. See `error_message` field for details." ] } }, "description": "RagFile status.", "id": "GoogleCloudAiplatformV1beta1FileStatus", "type": "object" }, "GoogleCloudAiplatformV1beta1TaskArtifact": { "properties": { "displayName": { "description": "Optional. The human-readable name of the artifact provided by the creator.", "type": "string" }, "description": { "description": "Optional. A human readable description of the artifact.", "type": "string" }, "parts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Part" }, "description": "Required. The content of the artifact." }, "artifactId": { "description": "Required. The unique identifier of the artifact within the task. This id is provided by the creator of the artifact.", "type": "string" }, "metadata": { "description": "Optional. Additional metadata for the artifact. For A2A, the URIs of the extensions that were used to produce this artifact will be stored here.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "description": "Represents a single artifact produced by a task. sample: artifacts: { artifact_id: \"image-12345\" name: \"Generated Sunset Image\" description: \"A beautiful sunset over the mountains, generated by the user's request.\" parts: { inline_data: { mime_type: \"image/png\" data: \"iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAA=\" } } }", "id": "GoogleCloudAiplatformV1beta1TaskArtifact", "type": "object" }, "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation": { "id": "GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation", "type": "object", "properties": { "columnName": { "type": "string" } }, "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index." }, "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataInputConfig": { "id": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataInputConfig", "type": "object", "properties": { "gcsSource": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataGcsSource" }, "bigquerySource": { "$ref": "GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataBigQuerySource" } }, "description": "The time series Dataset's data source. The Dataset doesn't store the data directly, but only pointer(s) to its data." } }, "rootUrl": "https://aiplatform.googleapis.com/", "fullyEncodeReservedExpansion": true, "mtlsRootUrl": "https://aiplatform.mtls.googleapis.com/", "kind": "discovery#restDescription", "icons": { "x16": "http://www.google.com/images/icons/product/search-16.gif", "x32": "http://www.google.com/images/icons/product/search-32.gif" }, "ownerName": "Google", "auth": { "oauth2": { "scopes": { "https://www.googleapis.com/auth/cloud-platform": { "description": "See, edit, configure, and delete your Google Cloud data and see the email address for your Google Account." }, "https://www.googleapis.com/auth/cloud-platform.read-only": { "description": "View your data across Google Cloud services and see the email address of your Google Account" } } } }, "id": "aiplatform:v1beta1", "baseUrl": "https://aiplatform.googleapis.com/", "resources": { "trainingPipelines": { "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "pattern": "^trainingPipelines/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1beta1/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.trainingPipelines.operations.delete" }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "type": "string", "pattern": "^trainingPipelines/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.trainingPipelines.operations.cancel", "flatPath": "v1beta1/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}:cancel" }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "type": "string", "pattern": "^trainingPipelines/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.trainingPipelines.operations.get", "flatPath": "v1beta1/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}" }, "wait": { "parameters": { "name": { "type": "string", "pattern": "^trainingPipelines/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.trainingPipelines.operations.wait" }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "type": "string", "pattern": "^trainingPipelines/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.trainingPipelines.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/trainingPipelines/{trainingPipelinesId}/operations" } } } } }, "featureGroups": { "resources": { "features": { "resources": { "operations": { "methods": { "list": { "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^featureGroups/[^/]+/features/[^/]+$", "required": true, "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/featureGroups/{featureGroupsId}/features/{featuresId}/operations", "id": "aiplatform.featureGroups.features.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "get": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "flatPath": "v1beta1/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.featureGroups.features.operations.get" }, "wait": { "flatPath": "v1beta1/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}:wait", "id": "aiplatform.featureGroups.features.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" } }, "delete": { "flatPath": "v1beta1/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", "id": "aiplatform.featureGroups.features.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "featureMonitors": { "resources": { "operations": { "methods": { "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.featureGroups.featureMonitors.operations.get", "flatPath": "v1beta1/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^featureGroups/[^/]+/featureMonitors/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^featureGroups/[^/]+/featureMonitors/[^/]+$", "required": true, "type": "string" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.featureGroups.featureMonitors.operations.list", "flatPath": "v1beta1/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}/operations" }, "delete": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^featureGroups/[^/]+/featureMonitors/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.featureGroups.featureMonitors.operations.delete" }, "wait": { "flatPath": "v1beta1/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.featureGroups.featureMonitors.operations.wait", "parameters": { "name": { "type": "string", "pattern": "^featureGroups/[^/]+/featureMonitors/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "operations": { "methods": { "get": { "id": "aiplatform.featureGroups.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/featureGroups/{featureGroupsId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^featureGroups/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ] }, "list": { "parameters": { "name": { "pattern": "^featureGroups/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/featureGroups/{featureGroupsId}/operations", "id": "aiplatform.featureGroups.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^featureGroups/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.featureGroups.operations.delete", "flatPath": "v1beta1/featureGroups/{featureGroupsId}/operations/{operationsId}" }, "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "pattern": "^featureGroups/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.featureGroups.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/featureGroups/{featureGroupsId}/operations/{operationsId}:wait" } } } } }, "datasets": { "methods": { "get": { "parameters": { "name": { "pattern": "^datasets/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the Dataset resource." }, "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ], "description": "Gets a Dataset.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Dataset" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/datasets/{datasetsId}", "id": "aiplatform.datasets.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "delete": { "parameters": { "name": { "type": "string", "pattern": "^datasets/[^/]+$", "required": true, "description": "Required. The resource name of the Dataset to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a Dataset.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/datasets/{datasetsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.datasets.delete" }, "list": { "path": "v1beta1/datasets", "httpMethod": "GET", "id": "aiplatform.datasets.list", "flatPath": "v1beta1/datasets", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListDatasetsResponse" }, "description": "Lists Datasets in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "type": "string", "location": "query", "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `display_name`: supports = and != * `metadata_schema_uri`: supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"`" }, "parent": { "type": "string", "location": "query", "description": "Required. The name of the Dataset's parent resource. Format: `projects/{project}/locations/{location}`" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "orderBy": { "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time`", "type": "string" }, "readMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read." }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [] }, "patch": { "id": "aiplatform.datasets.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1beta1Dataset" }, "flatPath": "v1beta1/datasets/{datasetsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates a Dataset.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Dataset" }, "parameters": { "name": { "description": "Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "location": "path", "pattern": "^datasets/[^/]+$", "required": true, "type": "string" }, "updateMask": { "type": "string", "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name` * `description` * `labels`", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ] }, "create": { "request": { "$ref": "GoogleCloudAiplatformV1beta1Dataset" }, "id": "aiplatform.datasets.create", "path": "v1beta1/datasets", "httpMethod": "POST", "flatPath": "v1beta1/datasets", "description": "Creates a Dataset.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "location": "query", "description": "Required. The resource name of the Location to create the Dataset in. Format: `projects/{project}/locations/{location}`", "type": "string" } }, "parameterOrder": [] } }, "resources": { "operations": { "methods": { "get": { "flatPath": "v1beta1/datasets/{datasetsId}/operations/{operationsId}", "id": "aiplatform.datasets.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "pattern": "^datasets/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "flatPath": "v1beta1/datasets/{datasetsId}/operations/{operationsId}", "id": "aiplatform.datasets.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^datasets/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "cancel": { "parameters": { "name": { "pattern": "^datasets/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/datasets/{datasetsId}/operations/{operationsId}:cancel", "id": "aiplatform.datasets.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "list": { "flatPath": "v1beta1/datasets/{datasetsId}/operations", "id": "aiplatform.datasets.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^datasets/[^/]+$", "required": true }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.datasets.operations.wait", "flatPath": "v1beta1/datasets/{datasetsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^datasets/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] } } }, "dataItems": { "resources": { "operations": { "methods": { "wait": { "id": "aiplatform.datasets.dataItems.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] }, "list": { "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^datasets/[^/]+/dataItems/[^/]+$", "required": true, "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1beta1/datasets/{datasetsId}/dataItems/{dataItemsId}/operations", "id": "aiplatform.datasets.dataItems.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "delete": { "id": "aiplatform.datasets.dataItems.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "pattern": "^datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:cancel", "id": "aiplatform.datasets.dataItems.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "flatPath": "v1beta1/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.datasets.dataItems.operations.get", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "annotations": { "resources": { "operations": { "methods": { "wait": { "flatPath": "v1beta1/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:wait", "id": "aiplatform.datasets.dataItems.annotations.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "type": "string", "pattern": "^datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "flatPath": "v1beta1/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.datasets.dataItems.annotations.operations.list", "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+$", "required": true }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "cancel": { "id": "aiplatform.datasets.dataItems.annotations.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.datasets.dataItems.annotations.operations.delete", "flatPath": "v1beta1/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "flatPath": "v1beta1/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}", "id": "aiplatform.datasets.dataItems.annotations.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "pattern": "^datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" } } } } } } } }, "annotationSpecs": { "resources": { "operations": { "methods": { "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.datasets.annotationSpecs.operations.wait", "flatPath": "v1beta1/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^datasets/[^/]+/annotationSpecs/[^/]+$", "required": true, "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.datasets.annotationSpecs.operations.list", "flatPath": "v1beta1/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations" }, "cancel": { "flatPath": "v1beta1/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:cancel", "id": "aiplatform.datasets.annotationSpecs.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "id": "aiplatform.datasets.annotationSpecs.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.datasets.annotationSpecs.operations.get", "flatPath": "v1beta1/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] } } } } }, "savedQueries": { "resources": { "operations": { "methods": { "get": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", "id": "aiplatform.datasets.savedQueries.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "flatPath": "v1beta1/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.datasets.savedQueries.operations.cancel" }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.datasets.savedQueries.operations.delete" }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.datasets.savedQueries.operations.list", "flatPath": "v1beta1/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^datasets/[^/]+/savedQueries/[^/]+$", "required": true, "type": "string" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" } }, "parameterOrder": [ "name" ] }, "wait": { "id": "aiplatform.datasets.savedQueries.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ] } } } } }, "datasetVersions": { "methods": { "create": { "parameters": { "parent": { "pattern": "^datasets/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "location": "path" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Create a version from a Dataset.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/datasets/{datasetsId}/datasetVersions", "id": "aiplatform.datasets.datasetVersions.create", "path": "v1beta1/{+parent}/datasetVersions", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" } }, "patch": { "parameters": { "name": { "location": "path", "description": "Output only. Identifier. The resource name of the DatasetVersion. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "pattern": "^datasets/[^/]+/datasetVersions/[^/]+$", "required": true, "type": "string" }, "updateMask": { "type": "string", "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name`", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ], "description": "Updates a DatasetVersion.", "response": { "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" }, "id": "aiplatform.datasets.datasetVersions.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH" }, "list": { "parameters": { "orderBy": { "type": "string", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", "location": "query" }, "pageToken": { "description": "Optional. The standard list page token.", "location": "query", "type": "string" }, "parent": { "location": "path", "description": "Required. The resource name of the Dataset to list DatasetVersions from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "type": "string", "pattern": "^datasets/[^/]+$", "required": true }, "filter": { "type": "string", "location": "query", "description": "Optional. The standard list filter." }, "pageSize": { "type": "integer", "description": "Optional. The standard list page size.", "location": "query", "format": "int32" }, "readMask": { "location": "query", "format": "google-fieldmask", "description": "Optional. Mask specifying which fields to read.", "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListDatasetVersionsResponse" }, "description": "Lists DatasetVersions in a Dataset.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/datasets/{datasetsId}/datasetVersions", "path": "v1beta1/{+parent}/datasetVersions", "httpMethod": "GET", "id": "aiplatform.datasets.datasetVersions.list" }, "delete": { "parameters": { "name": { "type": "string", "pattern": "^datasets/[^/]+/datasetVersions/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`" } }, "parameterOrder": [ "name" ], "description": "Deletes a Dataset version.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", "id": "aiplatform.datasets.datasetVersions.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^datasets/[^/]+/datasetVersions/[^/]+$", "required": true, "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "location": "path" }, "readMask": { "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a Dataset version.", "response": { "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" }, "flatPath": "v1beta1/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", "id": "aiplatform.datasets.datasetVersions.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "restore": { "parameters": { "name": { "location": "path", "description": "Required. The name of the DatasetVersion resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "pattern": "^datasets/[^/]+/datasetVersions/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Restores a dataset version.", "flatPath": "v1beta1/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}:restore", "path": "v1beta1/{+name}:restore", "httpMethod": "GET", "id": "aiplatform.datasets.datasetVersions.restore" } } } } }, "modelDeploymentMonitoringJobs": { "resources": { "operations": { "methods": { "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.modelDeploymentMonitoringJobs.operations.delete", "flatPath": "v1beta1/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.modelDeploymentMonitoringJobs.operations.cancel" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "flatPath": "v1beta1/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.modelDeploymentMonitoringJobs.operations.get" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.modelDeploymentMonitoringJobs.operations.wait", "flatPath": "v1beta1/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:wait" }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^modelDeploymentMonitoringJobs/[^/]+$", "required": true, "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.modelDeploymentMonitoringJobs.operations.list", "flatPath": "v1beta1/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations" } } } } }, "notebookRuntimes": { "resources": { "operations": { "methods": { "list": { "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^notebookRuntimes/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/notebookRuntimes/{notebookRuntimesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.notebookRuntimes.operations.list" }, "wait": { "parameters": { "name": { "type": "string", "pattern": "^notebookRuntimes/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.notebookRuntimes.operations.wait" }, "get": { "flatPath": "v1beta1/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}", "id": "aiplatform.notebookRuntimes.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^notebookRuntimes/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" } }, "cancel": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^notebookRuntimes/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "flatPath": "v1beta1/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.notebookRuntimes.operations.cancel" }, "delete": { "flatPath": "v1beta1/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.notebookRuntimes.operations.delete", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^notebookRuntimes/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "media": { "methods": { "upload": { "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "required": true, "description": "Required. The name of the RagCorpus resource into which to upload the file. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "location": "path" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1UploadRagFileResponse" }, "description": "Upload a file into a RagCorpus.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles:upload", "supportsMediaUpload": true, "path": "v1beta1/{+parent}/ragFiles:upload", "httpMethod": "POST", "id": "aiplatform.media.upload", "mediaUpload": { "accept": [ "*/*" ], "protocols": { "simple": { "path": "/upload/v1beta1/{+parent}/ragFiles:upload", "multipart": true } } }, "request": { "$ref": "GoogleCloudAiplatformV1beta1UploadRagFileRequest" } } } }, "operations": { "methods": { "list": { "id": "aiplatform.operations.list", "path": "v1beta1/operations", "httpMethod": "GET", "flatPath": "v1beta1/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "description": "The name of the operation's parent resource.", "location": "query", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [] }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.operations.wait", "flatPath": "v1beta1/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "flatPath": "v1beta1/operations/{operationsId}", "id": "aiplatform.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/operations/{operationsId}:cancel", "id": "aiplatform.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "parameters": { "name": { "pattern": "^operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.operations.delete" } } }, "customJobs": { "resources": { "operations": { "methods": { "list": { "id": "aiplatform.customJobs.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/customJobs/{customJobsId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "pattern": "^customJobs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ] }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.customJobs.operations.wait", "flatPath": "v1beta1/customJobs/{customJobsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^customJobs/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ] }, "get": { "flatPath": "v1beta1/customJobs/{customJobsId}/operations/{operationsId}", "id": "aiplatform.customJobs.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "pattern": "^customJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "flatPath": "v1beta1/customJobs/{customJobsId}/operations/{operationsId}:cancel", "id": "aiplatform.customJobs.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "pattern": "^customJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "delete": { "flatPath": "v1beta1/customJobs/{customJobsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.customJobs.operations.delete", "parameters": { "name": { "type": "string", "pattern": "^customJobs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." } } } } }, "studies": { "resources": { "operations": { "methods": { "get": { "flatPath": "v1beta1/studies/{studiesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.studies.operations.get", "parameters": { "name": { "type": "string", "pattern": "^studies/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." }, "delete": { "flatPath": "v1beta1/studies/{studiesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.studies.operations.delete", "parameters": { "name": { "type": "string", "pattern": "^studies/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "id": "aiplatform.studies.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/studies/{studiesId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^studies/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ] }, "list": { "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^studies/[^/]+$", "required": true }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1beta1/studies/{studiesId}/operations", "id": "aiplatform.studies.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "wait": { "parameters": { "name": { "type": "string", "pattern": "^studies/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1beta1/studies/{studiesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.studies.operations.wait" } } }, "trials": { "resources": { "operations": { "methods": { "cancel": { "id": "aiplatform.studies.trials.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "pattern": "^studies/[^/]+/trials/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ] }, "delete": { "parameters": { "name": { "type": "string", "pattern": "^studies/[^/]+/trials/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}", "id": "aiplatform.studies.trials.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.studies.trials.operations.get", "flatPath": "v1beta1/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^studies/[^/]+/trials/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "wait": { "flatPath": "v1beta1/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.studies.trials.operations.wait", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^studies/[^/]+/trials/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.studies.trials.operations.list", "flatPath": "v1beta1/studies/{studiesId}/trials/{trialsId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^studies/[^/]+/trials/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] } } } } } } }, "publishers": { "resources": { "models": { "methods": { "fetchPredictOperation": { "request": { "$ref": "GoogleCloudAiplatformV1beta1FetchPredictOperationRequest" }, "id": "aiplatform.publishers.models.fetchPredictOperation", "path": "v1beta1/{+endpoint}:fetchPredictOperation", "httpMethod": "POST", "flatPath": "v1beta1/publishers/{publishersId}/models/{modelsId}:fetchPredictOperation", "description": "Fetch an asynchronous online prediction operation.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "type": "string", "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`" } }, "parameterOrder": [ "endpoint" ] }, "streamGenerateContent": { "flatPath": "v1beta1/publishers/{publishersId}/models/{modelsId}:streamGenerateContent", "id": "aiplatform.publishers.models.streamGenerateContent", "path": "v1beta1/{+model}:streamGenerateContent", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "parameters": { "model": { "location": "path", "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "model" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Generate content with multimodal inputs with streaming support.", "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" } }, "get": { "parameters": { "includeEquivalentModelGardenModelDeploymentConfigs": { "type": "boolean", "description": "Optional. Whether to cnclude the deployment configs from the equivalent Model Garden model if the requested model is a Hugging Face model.", "location": "query" }, "isHuggingFaceModel": { "type": "boolean", "description": "Optional. Boolean indicates whether the requested model is a Hugging Face model.", "location": "query" }, "languageCode": { "type": "string", "description": "Optional. The IETF BCP-47 language code representing the language in which the publisher model's text information should be written in.", "location": "query" }, "view": { "type": "string", "enumDescriptions": [ "The default / unset value. The API will default to the BASIC view.", "Include basic metadata about the publisher model, but not the full contents.", "Include everything.", "Include: VersionId, ModelVersionExternalName, and SupportedActions." ], "location": "query", "enum": [ "PUBLISHER_MODEL_VIEW_UNSPECIFIED", "PUBLISHER_MODEL_VIEW_BASIC", "PUBLISHER_MODEL_VIEW_FULL", "PUBLISHER_MODEL_VERSION_VIEW_BASIC" ], "description": "Optional. PublisherModel view specifying which fields to read." }, "huggingFaceToken": { "type": "string", "location": "query", "description": "Optional. Token used to access Hugging Face gated models." }, "name": { "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}`" } }, "parameterOrder": [ "name" ], "description": "Gets a Model Garden publisher model.", "response": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModel" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/publishers/{publishersId}/models/{modelsId}", "id": "aiplatform.publishers.models.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "countTokens": { "request": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensRequest" }, "id": "aiplatform.publishers.models.countTokens", "path": "v1beta1/{+endpoint}:countTokens", "httpMethod": "POST", "flatPath": "v1beta1/publishers/{publishersId}/models/{modelsId}:countTokens", "description": "Perform a token counting.", "response": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path" } }, "parameterOrder": [ "endpoint" ] }, "predict": { "id": "aiplatform.publishers.models.predict", "path": "v1beta1/{+endpoint}:predict", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1PredictRequest" }, "flatPath": "v1beta1/publishers/{publishersId}/models/{modelsId}:predict", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "", "response": { "$ref": "GoogleCloudAiplatformV1beta1PredictResponse" }, "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "endpoint" ] }, "generateContent": { "parameters": { "model": { "location": "path", "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "model" ], "description": "Generate content with multimodal inputs.", "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "flatPath": "v1beta1/publishers/{publishersId}/models/{modelsId}:generateContent", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "id": "aiplatform.publishers.models.generateContent", "path": "v1beta1/{+model}:generateContent", "httpMethod": "POST" }, "predictLongRunning": { "description": "", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "type": "string", "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1PredictLongRunningRequest" }, "id": "aiplatform.publishers.models.predictLongRunning", "path": "v1beta1/{+endpoint}:predictLongRunning", "httpMethod": "POST", "flatPath": "v1beta1/publishers/{publishersId}/models/{modelsId}:predictLongRunning" }, "computeTokens": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensResponse" }, "description": "Return a list of tokens based on the input text.", "parameters": { "endpoint": { "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids.", "location": "path", "type": "string", "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true } }, "parameterOrder": [ "endpoint" ], "path": "v1beta1/{+endpoint}:computeTokens", "httpMethod": "POST", "id": "aiplatform.publishers.models.computeTokens", "request": { "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensRequest" }, "flatPath": "v1beta1/publishers/{publishersId}/models/{modelsId}:computeTokens" }, "list": { "path": "v1beta1/{+parent}/models", "httpMethod": "GET", "id": "aiplatform.publishers.models.list", "flatPath": "v1beta1/publishers/{publishersId}/models", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListPublisherModelsResponse" }, "description": "Lists publisher models in Model Garden.", "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The standard list page size." }, "view": { "location": "query", "enum": [ "PUBLISHER_MODEL_VIEW_UNSPECIFIED", "PUBLISHER_MODEL_VIEW_BASIC", "PUBLISHER_MODEL_VIEW_FULL", "PUBLISHER_MODEL_VERSION_VIEW_BASIC" ], "description": "Optional. PublisherModel view specifying which fields to read.", "type": "string", "enumDescriptions": [ "The default / unset value. The API will default to the BASIC view.", "Include basic metadata about the publisher model, but not the full contents.", "Include everything.", "Include: VersionId, ModelVersionExternalName, and SupportedActions." ] }, "listAllVersions": { "location": "query", "description": "Optional. List all publisher model versions if the flag is set to true.", "type": "boolean" }, "parent": { "location": "path", "description": "Required. The name of the Publisher from which to list the PublisherModels. Format: `publishers/{publisher}`", "type": "string", "pattern": "^publishers/[^/]+$", "required": true }, "languageCode": { "type": "string", "description": "Optional. The IETF BCP-47 language code representing the language in which the publisher models' text information should be written in. If not set, by default English (en).", "location": "query" }, "filter": { "type": "string", "description": "Optional. The standard list filter.", "location": "query" }, "orderBy": { "type": "string", "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending." }, "pageToken": { "description": "Optional. The standard list page token. Typically obtained via ListPublisherModelsResponse.next_page_token of the previous ModelGardenService.ListPublisherModels call.", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ] } } } } }, "models": { "resources": { "operations": { "methods": { "wait": { "flatPath": "v1beta1/models/{modelsId}/operations/{operationsId}:wait", "id": "aiplatform.models.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^models/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "id": "aiplatform.models.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/models/{modelsId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "pattern": "^models/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1beta1/models/{modelsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.models.operations.delete", "parameters": { "name": { "pattern": "^models/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "type": "string", "pattern": "^models/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.models.operations.cancel", "flatPath": "v1beta1/models/{modelsId}/operations/{operationsId}:cancel" }, "get": { "flatPath": "v1beta1/models/{modelsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.models.operations.get", "parameters": { "name": { "type": "string", "pattern": "^models/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." } } }, "evaluations": { "resources": { "operations": { "methods": { "get": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.models.evaluations.operations.get" }, "delete": { "flatPath": "v1beta1/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}", "id": "aiplatform.models.evaluations.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "id": "aiplatform.models.evaluations.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:cancel" }, "list": { "flatPath": "v1beta1/models/{modelsId}/evaluations/{evaluationsId}/operations", "id": "aiplatform.models.evaluations.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^models/[^/]+/evaluations/[^/]+$", "required": true }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "wait": { "parameters": { "name": { "pattern": "^models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:wait", "id": "aiplatform.models.evaluations.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" } } } } } } }, "featurestores": { "resources": { "operations": { "methods": { "get": { "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^featurestores/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "flatPath": "v1beta1/featurestores/{featurestoresId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.featurestores.operations.get" }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^featurestores/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/featurestores/{featurestoresId}/operations/{operationsId}", "id": "aiplatform.featurestores.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^featurestores/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.featurestores.operations.cancel", "flatPath": "v1beta1/featurestores/{featurestoresId}/operations/{operationsId}:cancel" }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.featurestores.operations.list", "flatPath": "v1beta1/featurestores/{featurestoresId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^featurestores/[^/]+$", "required": true }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" } }, "parameterOrder": [ "name" ] }, "wait": { "id": "aiplatform.featurestores.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/featurestores/{featurestoresId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^featurestores/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ] } } }, "entityTypes": { "resources": { "operations": { "methods": { "get": { "flatPath": "v1beta1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}", "id": "aiplatform.featurestores.entityTypes.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.featurestores.entityTypes.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}" }, "cancel": { "id": "aiplatform.featurestores.entityTypes.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ] }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.featurestores.entityTypes.operations.list", "flatPath": "v1beta1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.featurestores.entityTypes.operations.wait", "flatPath": "v1beta1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:wait" } } }, "features": { "resources": { "operations": { "methods": { "list": { "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "type": "string", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", "required": true, "location": "path", "description": "The name of the operation's parent resource." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1beta1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.featurestores.entityTypes.features.operations.list" }, "wait": { "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:wait", "id": "aiplatform.featurestores.entityTypes.features.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "get": { "flatPath": "v1beta1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}", "id": "aiplatform.featurestores.entityTypes.features.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" } }, "cancel": { "flatPath": "v1beta1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.featurestores.entityTypes.features.operations.cancel", "parameters": { "name": { "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.featurestores.entityTypes.features.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}" } } } } } } } } }, "evaluationTasks": { "resources": { "operations": { "methods": { "list": { "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^evaluationTasks/[^/]+$", "required": true, "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1beta1/evaluationTasks/{evaluationTasksId}/operations", "id": "aiplatform.evaluationTasks.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^evaluationTasks/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.evaluationTasks.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/evaluationTasks/{evaluationTasksId}/operations/{operationsId}" }, "wait": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^evaluationTasks/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1beta1/evaluationTasks/{evaluationTasksId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.evaluationTasks.operations.wait" }, "delete": { "parameters": { "name": { "pattern": "^evaluationTasks/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/evaluationTasks/{evaluationTasksId}/operations/{operationsId}", "id": "aiplatform.evaluationTasks.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" } } } } }, "metadataStores": { "resources": { "operations": { "methods": { "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.metadataStores.operations.cancel", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^metadataStores/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^metadataStores/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.metadataStores.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/operations/{operationsId}" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.metadataStores.operations.get", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "pattern": "^metadataStores/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^metadataStores/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "id": "aiplatform.metadataStores.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/operations/{operationsId}:wait" }, "list": { "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^metadataStores/[^/]+$", "required": true }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1beta1/metadataStores/{metadataStoresId}/operations", "id": "aiplatform.metadataStores.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" } } }, "artifacts": { "resources": { "operations": { "methods": { "list": { "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "type": "string", "pattern": "^metadataStores/[^/]+/artifacts/[^/]+$", "required": true, "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1beta1/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations", "id": "aiplatform.metadataStores.artifacts.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.metadataStores.artifacts.operations.wait", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ] }, "get": { "parameters": { "name": { "type": "string", "pattern": "^metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.metadataStores.artifacts.operations.get" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.metadataStores.artifacts.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}" }, "cancel": { "parameters": { "name": { "type": "string", "pattern": "^metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.metadataStores.artifacts.operations.cancel" } } } } }, "contexts": { "resources": { "operations": { "methods": { "cancel": { "parameters": { "name": { "pattern": "^metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:cancel", "id": "aiplatform.metadataStores.contexts.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "id": "aiplatform.metadataStores.contexts.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.metadataStores.contexts.operations.get", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "wait": { "id": "aiplatform.metadataStores.contexts.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ] }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^metadataStores/[^/]+/contexts/[^/]+$", "required": true, "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "parameterOrder": [ "name" ], "id": "aiplatform.metadataStores.contexts.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations" } } } } }, "executions": { "resources": { "operations": { "methods": { "get": { "id": "aiplatform.metadataStores.executions.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.metadataStores.executions.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}" }, "cancel": { "id": "aiplatform.metadataStores.executions.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "pattern": "^metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ] }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "type": "string", "pattern": "^metadataStores/[^/]+/executions/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.metadataStores.executions.operations.list", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/executions/{executionsId}/operations" }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.metadataStores.executions.operations.wait", "flatPath": "v1beta1/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ] } } } } } } }, "evaluationItems": { "resources": { "operations": { "methods": { "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.evaluationItems.operations.list", "flatPath": "v1beta1/evaluationItems/{evaluationItemsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^evaluationItems/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^evaluationItems/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.evaluationItems.operations.get", "flatPath": "v1beta1/evaluationItems/{evaluationItemsId}/operations/{operationsId}" }, "wait": { "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^evaluationItems/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1beta1/evaluationItems/{evaluationItemsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.evaluationItems.operations.wait" }, "delete": { "parameters": { "name": { "type": "string", "pattern": "^evaluationItems/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/evaluationItems/{evaluationItemsId}/operations/{operationsId}", "id": "aiplatform.evaluationItems.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" } } } } }, "evaluationSets": { "resources": { "operations": { "methods": { "delete": { "id": "aiplatform.evaluationSets.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/evaluationSets/{evaluationSetsId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^evaluationSets/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "wait": { "id": "aiplatform.evaluationSets.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/evaluationSets/{evaluationSetsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^evaluationSets/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "flatPath": "v1beta1/evaluationSets/{evaluationSetsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.evaluationSets.operations.get", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^evaluationSets/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^evaluationSets/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.evaluationSets.operations.list", "flatPath": "v1beta1/evaluationSets/{evaluationSetsId}/operations" } } } } }, "pipelineJobs": { "resources": { "operations": { "methods": { "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.pipelineJobs.operations.wait", "flatPath": "v1beta1/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "type": "string", "pattern": "^pipelineJobs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ] }, "list": { "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "pattern": "^pipelineJobs/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/pipelineJobs/{pipelineJobsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.pipelineJobs.operations.list" }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^pipelineJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/pipelineJobs/{pipelineJobsId}/operations/{operationsId}", "id": "aiplatform.pipelineJobs.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^pipelineJobs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.pipelineJobs.operations.cancel", "flatPath": "v1beta1/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:cancel" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^pipelineJobs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/pipelineJobs/{pipelineJobsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.pipelineJobs.operations.get" } } } } }, "onlineEvaluators": { "resources": { "operations": { "methods": { "list": { "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "name": { "pattern": "^onlineEvaluators/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1beta1/onlineEvaluators/{onlineEvaluatorsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.onlineEvaluators.operations.list" }, "wait": { "flatPath": "v1beta1/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.onlineEvaluators.operations.wait", "parameters": { "name": { "pattern": "^onlineEvaluators/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "get": { "parameters": { "name": { "type": "string", "pattern": "^onlineEvaluators/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.onlineEvaluators.operations.get" }, "cancel": { "id": "aiplatform.onlineEvaluators.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "pattern": "^onlineEvaluators/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1beta1/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.onlineEvaluators.operations.delete", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^onlineEvaluators/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." } } } } }, "hyperparameterTuningJobs": { "resources": { "operations": { "methods": { "cancel": { "flatPath": "v1beta1/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.hyperparameterTuningJobs.operations.cancel", "parameters": { "name": { "pattern": "^hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.hyperparameterTuningJobs.operations.delete", "flatPath": "v1beta1/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.hyperparameterTuningJobs.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}" }, "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.hyperparameterTuningJobs.operations.wait", "flatPath": "v1beta1/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}:wait" }, "list": { "id": "aiplatform.hyperparameterTuningJobs.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^hyperparameterTuningJobs/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] } } } } }, "extensions": { "resources": { "operations": { "methods": { "get": { "parameters": { "name": { "type": "string", "pattern": "^extensions/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/extensions/{extensionsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.extensions.operations.get" }, "delete": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^extensions/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/extensions/{extensionsId}/operations/{operationsId}", "id": "aiplatform.extensions.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.extensions.operations.cancel", "flatPath": "v1beta1/extensions/{extensionsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^extensions/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ] }, "list": { "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^extensions/[^/]+$", "required": true }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1beta1/extensions/{extensionsId}/operations", "id": "aiplatform.extensions.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "wait": { "flatPath": "v1beta1/extensions/{extensionsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.extensions.operations.wait", "parameters": { "name": { "type": "string", "pattern": "^extensions/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "migratableResources": { "resources": { "operations": { "methods": { "cancel": { "parameters": { "name": { "pattern": "^migratableResources/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/migratableResources/{migratableResourcesId}/operations/{operationsId}:cancel", "id": "aiplatform.migratableResources.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^migratableResources/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "id": "aiplatform.migratableResources.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/migratableResources/{migratableResourcesId}/operations/{operationsId}" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.migratableResources.operations.get", "flatPath": "v1beta1/migratableResources/{migratableResourcesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "type": "string", "pattern": "^migratableResources/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ] }, "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^migratableResources/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.migratableResources.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/migratableResources/{migratableResourcesId}/operations/{operationsId}:wait" }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "name": { "pattern": "^migratableResources/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.migratableResources.operations.list", "flatPath": "v1beta1/migratableResources/{migratableResourcesId}/operations" } } } } }, "ragCorpora": { "resources": { "operations": { "methods": { "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "pattern": "^ragCorpora/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.ragCorpora.operations.get", "flatPath": "v1beta1/ragCorpora/{ragCorporaId}/operations/{operationsId}" }, "delete": { "flatPath": "v1beta1/ragCorpora/{ragCorporaId}/operations/{operationsId}", "id": "aiplatform.ragCorpora.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^ragCorpora/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "type": "string", "pattern": "^ragCorpora/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.ragCorpora.operations.cancel", "flatPath": "v1beta1/ragCorpora/{ragCorporaId}/operations/{operationsId}:cancel" }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^ragCorpora/[^/]+$", "required": true, "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.ragCorpora.operations.list", "flatPath": "v1beta1/ragCorpora/{ragCorporaId}/operations" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^ragCorpora/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.ragCorpora.operations.wait", "flatPath": "v1beta1/ragCorpora/{ragCorporaId}/operations/{operationsId}:wait" } } }, "ragFiles": { "resources": { "operations": { "methods": { "wait": { "flatPath": "v1beta1/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}:wait", "id": "aiplatform.ragCorpora.ragFiles.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "type": "string", "pattern": "^ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" } }, "list": { "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^ragCorpora/[^/]+/ragFiles/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1beta1/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.ragCorpora.ragFiles.operations.list" }, "delete": { "flatPath": "v1beta1/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}", "id": "aiplatform.ragCorpora.ragFiles.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.ragCorpora.ragFiles.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}:cancel" }, "get": { "id": "aiplatform.ragCorpora.ragFiles.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ] } } } } } } }, "notebookRuntimeTemplates": { "resources": { "operations": { "methods": { "wait": { "parameters": { "name": { "type": "string", "pattern": "^notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:wait", "id": "aiplatform.notebookRuntimeTemplates.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "list": { "id": "aiplatform.notebookRuntimeTemplates.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "pattern": "^notebookRuntimeTemplates/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ] }, "delete": { "id": "aiplatform.notebookRuntimeTemplates.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "cancel": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "flatPath": "v1beta1/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.notebookRuntimeTemplates.operations.cancel" }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "type": "string", "pattern": "^notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.notebookRuntimeTemplates.operations.get", "flatPath": "v1beta1/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}" } } } } }, "evaluationRuns": { "resources": { "operations": { "methods": { "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.evaluationRuns.operations.list", "flatPath": "v1beta1/evaluationRuns/{evaluationRunsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "type": "string", "pattern": "^evaluationRuns/[^/]+$", "required": true, "location": "path", "description": "The name of the operation's parent resource." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^evaluationRuns/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "id": "aiplatform.evaluationRuns.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/evaluationRuns/{evaluationRunsId}/operations/{operationsId}" }, "wait": { "flatPath": "v1beta1/evaluationRuns/{evaluationRunsId}/operations/{operationsId}:wait", "id": "aiplatform.evaluationRuns.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^evaluationRuns/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^evaluationRuns/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.evaluationRuns.operations.delete", "flatPath": "v1beta1/evaluationRuns/{evaluationRunsId}/operations/{operationsId}" } } } } }, "batchPredictionJobs": { "methods": { "create": { "parameters": { "parent": { "type": "string", "location": "query", "description": "Required. The resource name of the Location to create the BatchPredictionJob in. Format: `projects/{project}/locations/{location}`" } }, "parameterOrder": [], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJob" }, "description": "Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start.", "flatPath": "v1beta1/batchPredictionJobs", "path": "v1beta1/batchPredictionJobs", "httpMethod": "POST", "id": "aiplatform.batchPredictionJobs.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJob" } }, "get": { "id": "aiplatform.batchPredictionJobs.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/batchPredictionJobs/{batchPredictionJobsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a BatchPredictionJob", "response": { "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJob" }, "parameters": { "name": { "pattern": "^batchPredictionJobs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the BatchPredictionJob resource. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`" } }, "parameterOrder": [ "name" ] }, "list": { "flatPath": "v1beta1/batchPredictionJobs", "path": "v1beta1/batchPredictionJobs", "httpMethod": "GET", "id": "aiplatform.batchPredictionJobs.list", "parameters": { "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `model_display_name` supports `=`, `!=` comparisons. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`" }, "parent": { "type": "string", "description": "Required. The resource name of the Location to list the BatchPredictionJobs from. Format: `projects/{project}/locations/{location}`", "location": "query" }, "pageToken": { "description": "The standard list page token. Typically obtained via ListBatchPredictionJobsResponse.next_page_token of the previous JobService.ListBatchPredictionJobs call.", "location": "query", "type": "string" } }, "parameterOrder": [], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListBatchPredictionJobsResponse" }, "description": "Lists BatchPredictionJobs in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "v1beta1": { "methods": { "evaluateDataset": { "flatPath": "v1beta1:evaluateDataset", "id": "aiplatform.evaluateDataset", "path": "v1beta1:evaluateDataset", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1EvaluateDatasetRequest" }, "parameters": {}, "parameterOrder": [], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Evaluates a dataset based on a set of given metrics.", "response": { "$ref": "GoogleLongrunningOperation" } }, "generateInstanceRubrics": { "flatPath": "v1beta1:generateInstanceRubrics", "path": "v1beta1:generateInstanceRubrics", "httpMethod": "POST", "id": "aiplatform.generateInstanceRubrics", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateInstanceRubricsRequest" }, "parameters": {}, "parameterOrder": [], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateInstanceRubricsResponse" }, "description": "Generates rubrics for a given prompt. A rubric represents a single testable criterion for evaluation. One input prompt could have multiple rubrics This RPC allows users to get suggested rubrics based on provided prompt, which can then be reviewed and used for subsequent evaluations." }, "evaluateInstances": { "parameters": {}, "parameterOrder": [], "response": { "$ref": "GoogleCloudAiplatformV1beta1EvaluateInstancesResponse" }, "description": "Evaluates instances based on a given metric.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1:evaluateInstances", "request": { "$ref": "GoogleCloudAiplatformV1beta1EvaluateInstancesRequest" }, "path": "v1beta1:evaluateInstances", "httpMethod": "POST", "id": "aiplatform.evaluateInstances" } } }, "agents": { "resources": { "operations": { "methods": { "list": { "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "pattern": "^agents/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/agents/{agentsId}/operations", "id": "aiplatform.agents.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "wait": { "id": "aiplatform.agents.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/agents/{agentsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^agents/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^agents/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/agents/{agentsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.agents.operations.get" }, "cancel": { "flatPath": "v1beta1/agents/{agentsId}/operations/{operationsId}:cancel", "id": "aiplatform.agents.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "type": "string", "pattern": "^agents/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "parameters": { "name": { "type": "string", "pattern": "^agents/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/agents/{agentsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.agents.operations.delete" } } } } }, "tensorboards": { "resources": { "operations": { "methods": { "list": { "flatPath": "v1beta1/tensorboards/{tensorboardsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.tensorboards.operations.list", "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^tensorboards/[^/]+$", "required": true }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "wait": { "parameters": { "name": { "pattern": "^tensorboards/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.tensorboards.operations.wait" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.tensorboards.operations.get", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "type": "string", "pattern": "^tensorboards/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^tensorboards/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.tensorboards.operations.delete", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/operations/{operationsId}" }, "cancel": { "parameters": { "name": { "type": "string", "pattern": "^tensorboards/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/tensorboards/{tensorboardsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.tensorboards.operations.cancel" } } }, "experiments": { "resources": { "operations": { "methods": { "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.tensorboards.experiments.operations.get", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.tensorboards.experiments.operations.delete", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:cancel", "id": "aiplatform.tensorboards.experiments.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "pattern": "^tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "name": { "pattern": "^tensorboards/[^/]+/experiments/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations", "id": "aiplatform.tensorboards.experiments.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.tensorboards.experiments.operations.wait", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:wait" } } }, "runs": { "resources": { "operations": { "methods": { "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "id": "aiplatform.tensorboards.experiments.runs.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}" }, "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.tensorboards.experiments.runs.operations.cancel", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ] }, "delete": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}", "id": "aiplatform.tensorboards.experiments.runs.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "required": true, "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.tensorboards.experiments.runs.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations" }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.tensorboards.experiments.runs.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:wait" } } }, "timeSeries": { "resources": { "operations": { "methods": { "list": { "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.tensorboards.experiments.runs.timeSeries.operations.list" }, "wait": { "id": "aiplatform.tensorboards.experiments.runs.timeSeries.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}", "id": "aiplatform.tensorboards.experiments.runs.timeSeries.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.tensorboards.experiments.runs.timeSeries.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:cancel" }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.tensorboards.experiments.runs.timeSeries.operations.delete" } } } } } } } } } } }, "endpoints": { "methods": { "fetchPredictOperation": { "request": { "$ref": "GoogleCloudAiplatformV1beta1FetchPredictOperationRequest" }, "path": "v1beta1/{+endpoint}:fetchPredictOperation", "httpMethod": "POST", "id": "aiplatform.endpoints.fetchPredictOperation", "flatPath": "v1beta1/endpoints/{endpointsId}:fetchPredictOperation", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Fetch an asynchronous online prediction operation.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "pattern": "^endpoints/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "location": "path" } }, "parameterOrder": [ "endpoint" ] }, "streamGenerateContent": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Generate content with multimodal inputs with streaming support.", "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "parameters": { "model": { "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path", "type": "string", "pattern": "^endpoints/[^/]+$", "required": true } }, "parameterOrder": [ "model" ], "id": "aiplatform.endpoints.streamGenerateContent", "path": "v1beta1/{+model}:streamGenerateContent", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "flatPath": "v1beta1/endpoints/{endpointsId}:streamGenerateContent" }, "generateContent": { "description": "Generate content with multimodal inputs.", "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "model": { "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path", "type": "string", "pattern": "^endpoints/[^/]+$", "required": true } }, "parameterOrder": [ "model" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "id": "aiplatform.endpoints.generateContent", "path": "v1beta1/{+model}:generateContent", "httpMethod": "POST", "flatPath": "v1beta1/endpoints/{endpointsId}:generateContent" }, "predict": { "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^endpoints/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "endpoint" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1PredictResponse" }, "description": "", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "flatPath": "v1beta1/endpoints/{endpointsId}:predict", "request": { "$ref": "GoogleCloudAiplatformV1beta1PredictRequest" }, "path": "v1beta1/{+endpoint}:predict", "httpMethod": "POST", "id": "aiplatform.endpoints.predict" }, "predictLongRunning": { "flatPath": "v1beta1/endpoints/{endpointsId}:predictLongRunning", "request": { "$ref": "GoogleCloudAiplatformV1beta1PredictLongRunningRequest" }, "path": "v1beta1/{+endpoint}:predictLongRunning", "httpMethod": "POST", "id": "aiplatform.endpoints.predictLongRunning", "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "type": "string", "pattern": "^endpoints/[^/]+$", "required": true } }, "parameterOrder": [ "endpoint" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ] }, "computeTokens": { "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids.", "type": "string", "pattern": "^endpoints/[^/]+$", "required": true } }, "parameterOrder": [ "endpoint" ], "description": "Return a list of tokens based on the input text.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/endpoints/{endpointsId}:computeTokens", "request": { "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensRequest" }, "id": "aiplatform.endpoints.computeTokens", "path": "v1beta1/{+endpoint}:computeTokens", "httpMethod": "POST" }, "countTokens": { "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string", "pattern": "^endpoints/[^/]+$", "required": true } }, "parameterOrder": [ "endpoint" ], "description": "Perform a token counting.", "response": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "flatPath": "v1beta1/endpoints/{endpointsId}:countTokens", "request": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensRequest" }, "id": "aiplatform.endpoints.countTokens", "path": "v1beta1/{+endpoint}:countTokens", "httpMethod": "POST" } }, "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^endpoints/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/endpoints/{endpointsId}/operations/{operationsId}", "id": "aiplatform.endpoints.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^endpoints/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/endpoints/{endpointsId}/operations/{operationsId}:cancel", "id": "aiplatform.endpoints.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^endpoints/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.endpoints.operations.get", "flatPath": "v1beta1/endpoints/{endpointsId}/operations/{operationsId}" }, "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^endpoints/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "id": "aiplatform.endpoints.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/endpoints/{endpointsId}/operations/{operationsId}:wait" }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^endpoints/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.endpoints.operations.list", "flatPath": "v1beta1/endpoints/{endpointsId}/operations" } } }, "chat": { "methods": { "completions": { "flatPath": "v1beta1/endpoints/{endpointsId}/chat/completions", "request": { "$ref": "GoogleApiHttpBody" }, "id": "aiplatform.endpoints.chat.completions", "path": "v1beta1/{+endpoint}/chat/completions", "httpMethod": "POST", "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^endpoints/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "endpoint" ], "description": "Exposes an OpenAI-compatible endpoint for chat completions.", "response": { "$ref": "GoogleApiHttpBody" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ] } } } } }, "tuningJobs": { "resources": { "operations": { "methods": { "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "pattern": "^tuningJobs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "id": "aiplatform.tuningJobs.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/tuningJobs/{tuningJobsId}/operations/{operationsId}" } } } } }, "featureOnlineStores": { "resources": { "operations": { "methods": { "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^featureOnlineStores/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.featureOnlineStores.operations.get", "flatPath": "v1beta1/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}" }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.featureOnlineStores.operations.list", "flatPath": "v1beta1/featureOnlineStores/{featureOnlineStoresId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^featureOnlineStores/[^/]+$", "required": true, "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ] }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.featureOnlineStores.operations.delete", "flatPath": "v1beta1/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^featureOnlineStores/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^featureOnlineStores/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "id": "aiplatform.featureOnlineStores.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}:wait" } } }, "featureViews": { "resources": { "operations": { "methods": { "wait": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.featureOnlineStores.featureViews.operations.wait" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "pattern": "^featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "id": "aiplatform.featureOnlineStores.featureViews.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}" }, "list": { "flatPath": "v1beta1/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations", "id": "aiplatform.featureOnlineStores.featureViews.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "pattern": "^featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "id": "aiplatform.featureOnlineStores.featureViews.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}" } } } } } } }, "specialistPools": { "resources": { "operations": { "methods": { "wait": { "flatPath": "v1beta1/specialistPools/{specialistPoolsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.specialistPools.operations.wait", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^specialistPools/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^specialistPools/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.specialistPools.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/specialistPools/{specialistPoolsId}/operations" }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^specialistPools/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.specialistPools.operations.delete", "flatPath": "v1beta1/specialistPools/{specialistPoolsId}/operations/{operationsId}" }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^specialistPools/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.specialistPools.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/specialistPools/{specialistPoolsId}/operations/{operationsId}:cancel" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.specialistPools.operations.get", "flatPath": "v1beta1/specialistPools/{specialistPoolsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "type": "string", "pattern": "^specialistPools/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] } } } } }, "projects": { "methods": { "updateCacheConfig": { "id": "aiplatform.projects.updateCacheConfig", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1beta1CacheConfig" }, "flatPath": "v1beta1/projects/{projectsId}/cacheConfig", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates a cache config.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/cacheConfig$", "required": true, "type": "string", "location": "path", "description": "Identifier. Name of the cache config. Format: - `projects/{project}/cacheConfig`." } }, "parameterOrder": [ "name" ] }, "fetchPublisherModelConfig": { "path": "v1beta1/{+name}:fetchPublisherModelConfig", "httpMethod": "GET", "id": "aiplatform.projects.fetchPublisherModelConfig", "flatPath": "v1beta1/projects/{projectsId}:fetchPublisherModelConfig", "response": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelConfig" }, "description": "Fetches the configs of publisher models.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the publisher model, in the format of `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`." } }, "parameterOrder": [ "name" ] }, "getCacheConfig": { "flatPath": "v1beta1/projects/{projectsId}/cacheConfig", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.getCacheConfig", "parameters": { "name": { "pattern": "^projects/[^/]+/cacheConfig$", "required": true, "type": "string", "description": "Required. Name of the cache config. Format: - `projects/{project}/cacheConfig`.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1CacheConfig" }, "description": "Gets a GenAI cache config.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "setPublisherModelConfig": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Sets (creates or updates) configs of publisher models. For example, sets the request/response logging config.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The name of the publisher model, in the format of `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`.", "pattern": "^projects/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1SetPublisherModelConfigRequest" }, "path": "v1beta1/{+name}:setPublisherModelConfig", "httpMethod": "POST", "id": "aiplatform.projects.setPublisherModelConfig", "flatPath": "v1beta1/projects/{projectsId}:setPublisherModelConfig" } }, "resources": { "locations": { "methods": { "evaluateInstances": { "parameters": { "location": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location to evaluate the instances. Format: `projects/{project}/locations/{location}`" } }, "parameterOrder": [ "location" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1EvaluateInstancesResponse" }, "description": "Evaluates instances based on a given metric.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:evaluateInstances", "path": "v1beta1/{+location}:evaluateInstances", "httpMethod": "POST", "id": "aiplatform.projects.locations.evaluateInstances", "request": { "$ref": "GoogleCloudAiplatformV1beta1EvaluateInstancesRequest" } }, "asyncRetrieveContexts": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:asyncRetrieveContexts", "id": "aiplatform.projects.locations.asyncRetrieveContexts", "path": "v1beta1/{+parent}:asyncRetrieveContexts", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1AsyncRetrieveContextsRequest" }, "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location from which to retrieve RagContexts. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`.", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Asynchronous API to retrieves relevant contexts for a query.", "response": { "$ref": "GoogleLongrunningOperation" } }, "generateSyntheticData": { "parameters": { "location": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "location": "path", "description": "Required. The geographic location where the synthetic data generation request is processed. This should be in the format `projects/{project}/locations/{location}`. For example, `projects/my-project/locations/us-central1`." } }, "parameterOrder": [ "location" ], "description": "Generates synthetic (artificial) data based on a description", "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateSyntheticDataResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:generateSyntheticData", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateSyntheticDataRequest" }, "id": "aiplatform.projects.locations.generateSyntheticData", "path": "v1beta1/{+location}:generateSyntheticData", "httpMethod": "POST" }, "deployPublisherModel": { "path": "v1beta1/{+destination}:deployPublisherModel", "httpMethod": "POST", "deprecated": true, "id": "aiplatform.projects.locations.deployPublisherModel", "request": { "$ref": "GoogleCloudAiplatformV1beta1DeployPublisherModelRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:deployPublisherModel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deploys publisher models.", "parameters": { "destination": { "location": "path", "description": "Required. The resource name of the Location to deploy the model in. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "destination" ] }, "updateRagEngineConfig": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig", "id": "aiplatform.projects.locations.updateRagEngineConfig", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1beta1RagEngineConfig" }, "parameters": { "name": { "location": "path", "description": "Identifier. The name of the RagEngineConfig. Format: `projects/{project}/locations/{location}/ragEngineConfig`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates a RagEngineConfig.", "response": { "$ref": "GoogleLongrunningOperation" } }, "augmentPrompt": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:augmentPrompt", "request": { "$ref": "GoogleCloudAiplatformV1beta1AugmentPromptRequest" }, "path": "v1beta1/{+parent}:augmentPrompt", "httpMethod": "POST", "id": "aiplatform.projects.locations.augmentPrompt", "parameters": { "parent": { "description": "Required. The resource name of the Location from which to augment prompt. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1AugmentPromptResponse" }, "description": "Given an input prompt, it returns augmented prompt from vertex rag store to guide LLM towards generating grounded responses.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "corroborateContent": { "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location from which to corroborate text. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`.", "location": "path" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1CorroborateContentResponse" }, "description": "Given an input text, it returns a score that evaluates the factuality of the text. It also extracts and returns claims from the text and provides supporting facts.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:corroborateContent", "path": "v1beta1/{+parent}:corroborateContent", "httpMethod": "POST", "id": "aiplatform.projects.locations.corroborateContent", "request": { "$ref": "GoogleCloudAiplatformV1beta1CorroborateContentRequest" } }, "recommendSpec": { "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location from which to recommend specs. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`." } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1RecommendSpecResponse" }, "description": "Gets a Model's spec recommendations. This API is called by UI, SDK, and internal.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:recommendSpec", "request": { "$ref": "GoogleCloudAiplatformV1beta1RecommendSpecRequest" }, "path": "v1beta1/{+parent}:recommendSpec", "httpMethod": "POST", "id": "aiplatform.projects.locations.recommendSpec" }, "generateLossClusters": { "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateLossClustersRequest" }, "path": "v1beta1/{+location}:generateLossClusters", "httpMethod": "POST", "id": "aiplatform.projects.locations.generateLossClusters", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:generateLossClusters", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Generates loss clusters from evaluation results. This is a statelss API method that would not modify the EvaluationSet resource.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "location": { "description": "Required. The resource name of the Location. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "location" ] }, "generateUserScenarios": { "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateUserScenariosRequest" }, "id": "aiplatform.projects.locations.generateUserScenarios", "path": "v1beta1/{+location}:generateUserScenarios", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:generateUserScenarios", "description": "Generates user scenarios for agent evaluation.", "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateUserScenariosResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "location": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Location to run the job. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "parameterOrder": [ "location" ] }, "evaluateDataset": { "parameters": { "location": { "description": "Required. The resource name of the Location to evaluate the dataset. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "location" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Evaluates a dataset based on a set of given metrics.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:evaluateDataset", "request": { "$ref": "GoogleCloudAiplatformV1beta1EvaluateDatasetRequest" }, "path": "v1beta1/{+location}:evaluateDataset", "httpMethod": "POST", "id": "aiplatform.projects.locations.evaluateDataset" }, "askContexts": { "path": "v1beta1/{+parent}:askContexts", "httpMethod": "POST", "id": "aiplatform.projects.locations.askContexts", "request": { "$ref": "GoogleCloudAiplatformV1beta1AskContextsRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:askContexts", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1AskContextsResponse" }, "description": "Agentic Retrieval Ask API for RAG.", "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location from which to retrieve RagContexts. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`.", "location": "path" } }, "parameterOrder": [ "parent" ] }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudLocationLocation" }, "description": "Gets information about a location.", "parameters": { "name": { "location": "path", "description": "Resource name for the location.", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}" }, "deploy": { "parameters": { "destination": { "location": "path", "description": "Required. The resource name of the Location to deploy the model in. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "destination" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deploys a model to a new endpoint.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:deploy", "request": { "$ref": "GoogleCloudAiplatformV1beta1DeployRequest" }, "path": "v1beta1/{+destination}:deploy", "httpMethod": "POST", "id": "aiplatform.projects.locations.deploy" }, "retrieveContexts": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:retrieveContexts", "request": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveContextsRequest" }, "path": "v1beta1/{+parent}:retrieveContexts", "httpMethod": "POST", "id": "aiplatform.projects.locations.retrieveContexts", "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location from which to retrieve RagContexts. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`.", "location": "path" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveContextsResponse" }, "description": "Retrieves relevant contexts for a query.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations", "path": "v1beta1/{+name}/locations", "httpMethod": "GET", "id": "aiplatform.projects.locations.list", "parameters": { "filter": { "description": "A filter to narrow down results to a preferred subset. The filtering language accepts strings like `\"displayName=tokyo\"`, and is documented in more detail in [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" }, "pageToken": { "location": "query", "description": "A page token received from the `next_page_token` field in the response. Send that page token to receive the subsequent page.", "type": "string" }, "name": { "location": "path", "description": "The resource that owns the locations collection, if applicable.", "pattern": "^projects/[^/]+$", "required": true, "type": "string" }, "extraLocationTypes": { "description": "Optional. Do not use this field. It is unsupported and is ignored unless explicitly documented otherwise. This is primarily for internal usage.", "location": "query", "repeated": true, "type": "string" }, "pageSize": { "type": "integer", "description": "The maximum number of results to return. If not set, the service selects a default.", "location": "query", "format": "int32" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudLocationListLocationsResponse" }, "description": "Lists information about the supported locations for this service. This method lists locations based on the resource scope provided in the [ListLocationsRequest.name] field: * **Global locations**: If `name` is empty, the method lists the public locations available to all projects. * **Project-specific locations**: If `name` follows the format `projects/{project}`, the method lists locations visible to that specific project. This includes public, private, or other project-specific locations enabled for the project. For gRPC and client library implementations, the resource name is passed as the `name` field. For direct service calls, the resource name is incorporated into the request path based on the specific service implementation and version.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "generateInstanceRubrics": { "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateInstanceRubricsRequest" }, "id": "aiplatform.projects.locations.generateInstanceRubrics", "path": "v1beta1/{+location}:generateInstanceRubrics", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}:generateInstanceRubrics", "description": "Generates rubrics for a given prompt. A rubric represents a single testable criterion for evaluation. One input prompt could have multiple rubrics This RPC allows users to get suggested rubrics based on provided prompt, which can then be reviewed and used for subsequent evaluations.", "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateInstanceRubricsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "location": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Location to generate rubrics from. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "parameterOrder": [ "location" ] }, "getRagEngineConfig": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.getRagEngineConfig", "parameters": { "name": { "location": "path", "description": "Required. The name of the RagEngineConfig resource. Format: `projects/{project}/locations/{location}/ragEngineConfig`", "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1RagEngineConfig" }, "description": "Gets a RagEngineConfig.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "notebookRuntimeTemplates": { "methods": { "setIamPolicy": { "parameters": { "resource": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "required": true, "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" } }, "parameterOrder": [ "resource" ], "response": { "$ref": "GoogleIamV1Policy" }, "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:setIamPolicy", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "path": "v1beta1/{+resource}:setIamPolicy", "httpMethod": "POST", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.setIamPolicy" }, "create": { "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location to create the NotebookRuntimeTemplate. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "notebookRuntimeTemplateId": { "type": "string", "location": "query", "description": "Optional. User specified ID for the notebook runtime template." } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a NotebookRuntimeTemplate.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.create", "path": "v1beta1/{+parent}/notebookRuntimeTemplates", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate" } }, "getIamPolicy": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "response": { "$ref": "GoogleIamV1Policy" }, "parameters": { "resource": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "required": true, "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" }, "options.requestedPolicyVersion": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies)." } }, "parameterOrder": [ "resource" ], "id": "aiplatform.projects.locations.notebookRuntimeTemplates.getIamPolicy", "path": "v1beta1/{+resource}:getIamPolicy", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:getIamPolicy" }, "patch": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The resource name of the NotebookRuntimeTemplate." }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Input format: `{paths: \"${updated_field}\"}` Updatable fields: * `encryption_spec.kms_key_name` * `display_name` * `software_config.post_startup_script_config.post_startup_script` * `software_config.post_startup_script_config.post_startup_script_url` * `software_config.post_startup_script_config.post_startup_script_behavior` * `software_config.env` * `software_config.colab_image.release_name` * `software_config.custom_container_config.image_uri`" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate" }, "description": "Updates a NotebookRuntimeTemplate.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.patch" }, "list": { "response": { "$ref": "GoogleCloudAiplatformV1beta1ListNotebookRuntimeTemplatesResponse" }, "description": "Lists NotebookRuntimeTemplates in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "location": "query", "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookRuntimeTemplate` supports = and !=. `notebookRuntimeTemplate` represents the NotebookRuntimeTemplate ID, i.e. the last segment of the NotebookRuntimeTemplate's resource name. * `display_name` supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. * `notebookRuntimeType` supports = and !=. notebookRuntimeType enum: [USER_DEFINED, ONE_CLICK]. * `machineType` supports = and !=. * `acceleratorType` supports = and !=. Some examples: * `notebookRuntimeTemplate=notebookRuntimeTemplate123` * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"` * `notebookRuntimeType=USER_DEFINED` * `machineType=e2-standard-4` * `acceleratorType=NVIDIA_TESLA_T4`", "type": "string" }, "parent": { "location": "path", "description": "Required. The resource name of the Location from which to list the NotebookRuntimeTemplates. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "pageToken": { "type": "string", "description": "Optional. The standard list page token. Typically obtained via ListNotebookRuntimeTemplatesResponse.next_page_token of the previous NotebookService.ListNotebookRuntimeTemplates call.", "location": "query" }, "orderBy": { "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", "type": "string" }, "readMask": { "description": "Optional. Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask", "type": "string" }, "pageSize": { "description": "Optional. The standard list page size.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/notebookRuntimeTemplates", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates" }, "testIamPermissions": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:testIamPermissions", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.testIamPermissions", "path": "v1beta1/{+resource}:testIamPermissions", "httpMethod": "POST", "parameters": { "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "required": true, "type": "string", "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" }, "permissions": { "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", "location": "query", "repeated": true, "type": "string" } }, "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" } }, "delete": { "parameters": { "name": { "location": "path", "description": "Required. The name of the NotebookRuntimeTemplate resource to be deleted. Format: `projects/{project}/locations/{location}/notebookRuntimeTemplates/{notebook_runtime_template}`", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a NotebookRuntimeTemplate.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate" }, "description": "Gets a NotebookRuntimeTemplate.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the NotebookRuntimeTemplate resource. Format: `projects/{project}/locations/{location}/notebookRuntimeTemplates/{notebook_runtime_template}`", "location": "path" } }, "parameterOrder": [ "name" ] } }, "resources": { "operations": { "methods": { "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.cancel", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}" }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}" }, "wait": { "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.list", "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "evaluationRuns": { "methods": { "create": { "path": "v1beta1/{+parent}/evaluationRuns", "httpMethod": "POST", "id": "aiplatform.projects.locations.evaluationRuns.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRun" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationRuns", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRun" }, "description": "Creates an Evaluation Run.", "parameters": { "parent": { "description": "Required. The resource name of the Location to create the Evaluation Run in. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ] }, "list": { "parameters": { "pageSize": { "description": "Optional. The maximum number of Evaluation Runs to return.", "location": "query", "format": "int32", "type": "integer" }, "orderBy": { "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "description": "Optional. A page token, received from a previous `ListEvaluationRuns` call. Provide this to retrieve the subsequent page.", "location": "query" }, "parent": { "location": "path", "description": "Required. The resource name of the Location from which to list the Evaluation Runs. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "filter": { "location": "query", "description": "Optional. Filter expression that matches a subset of the EvaluationRuns to show. For field names both snake_case and camelCase are supported. For more information about filter syntax, see [AIP-160](https://google.aip.dev/160).", "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists Evaluation Runs.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListEvaluationRunsResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationRuns", "id": "aiplatform.projects.locations.evaluationRuns.list", "path": "v1beta1/{+parent}/evaluationRuns", "httpMethod": "GET" }, "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.evaluationRuns.cancel", "request": { "$ref": "GoogleCloudAiplatformV1beta1CancelEvaluationRunRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationRuns/{evaluationRunsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Cancels an Evaluation Run. Attempts to cancel a running Evaluation Run asynchronously. Status of run can be checked via GetEvaluationRun.", "parameters": { "name": { "location": "path", "description": "Required. The name of the EvaluationRun resource to be cancelled. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationRuns/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationRuns/{evaluationRunsId}", "id": "aiplatform.projects.locations.evaluationRuns.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationRuns/[^/]+$", "required": true, "description": "Required. The name of the EvaluationRun resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}`", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes an Evaluation Run.", "response": { "$ref": "GoogleLongrunningOperation" } }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationRuns/{evaluationRunsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationRuns.get", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/evaluationRuns/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the EvaluationRun resource. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}`", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationRun" }, "description": "Gets an Evaluation Run.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "operations": { "methods": { "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationRuns/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.evaluationRuns.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationRuns/{evaluationRunsId}/operations/{operationsId}" }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationRuns/{evaluationRunsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.evaluationRuns.operations.wait", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/evaluationRuns/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationRuns/{evaluationRunsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationRuns.operations.get", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationRuns/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationRuns/[^/]+$", "required": true, "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationRuns/{evaluationRunsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationRuns.operations.list" } } } } }, "batchPredictionJobs": { "methods": { "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs", "path": "v1beta1/{+parent}/batchPredictionJobs", "httpMethod": "GET", "id": "aiplatform.projects.locations.batchPredictionJobs.list", "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token. Typically obtained via ListBatchPredictionJobsResponse.next_page_token of the previous JobService.ListBatchPredictionJobs call." }, "parent": { "description": "Required. The resource name of the Location to list the BatchPredictionJobs from. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "filter": { "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `model_display_name` supports `=`, `!=` comparisons. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", "location": "query", "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "readMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read." } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListBatchPredictionJobsResponse" }, "description": "Lists BatchPredictionJobs in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "create": { "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to create the BatchPredictionJob in. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "parameterOrder": [ "parent" ], "description": "Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start.", "response": { "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJob" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJob" }, "id": "aiplatform.projects.locations.batchPredictionJobs.create", "path": "v1beta1/{+parent}/batchPredictionJobs", "httpMethod": "POST" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", "required": true, "description": "Required. The name of the BatchPredictionJob resource. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a BatchPredictionJob", "response": { "$ref": "GoogleCloudAiplatformV1beta1BatchPredictionJob" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}", "id": "aiplatform.projects.locations.batchPredictionJobs.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "delete": { "parameters": { "name": { "description": "Required. The name of the BatchPredictionJob resource to be deleted. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a BatchPredictionJob. Can only be called on jobs that already finished.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.batchPredictionJobs.delete" }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Cancels a BatchPredictionJob. Starts asynchronous cancellation on the BatchPredictionJob. The server makes the best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetBatchPredictionJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On a successful cancellation, the BatchPredictionJob is not deleted;instead its BatchPredictionJob.state is set to `CANCELLED`. Any files already outputted by the job are not deleted.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the BatchPredictionJob to cancel. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`" } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1CancelBatchPredictionJobRequest" }, "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.batchPredictionJobs.cancel", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}:cancel" } } }, "hyperparameterTuningJobs": { "methods": { "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs", "path": "v1beta1/{+parent}/hyperparameterTuningJobs", "httpMethod": "POST", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1HyperparameterTuningJob" }, "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to create the HyperparameterTuningJob in. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1HyperparameterTuningJob" }, "description": "Creates a HyperparameterTuningJob" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs", "path": "v1beta1/{+parent}/hyperparameterTuningJobs", "httpMethod": "GET", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.list", "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token. Typically obtained via ListHyperparameterTuningJobsResponse.next_page_token of the previous JobService.ListHyperparameterTuningJobs call." }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location to list the HyperparameterTuningJobs from. Format: `projects/{project}/locations/{location}`" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "readMask": { "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListHyperparameterTuningJobsResponse" }, "description": "Lists HyperparameterTuningJobs in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a HyperparameterTuningJob.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "Required. The name of the HyperparameterTuningJob resource to be deleted. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.hyperparameterTuningJobs.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}" }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.cancel", "request": { "$ref": "GoogleCloudAiplatformV1beta1CancelHyperparameterTuningJobRequest" }, "parameters": { "name": { "location": "path", "description": "Required. The name of the HyperparameterTuningJob to cancel. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Cancels a HyperparameterTuningJob. Starts asynchronous cancellation on the HyperparameterTuningJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetHyperparameterTuningJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the HyperparameterTuningJob is not deleted; instead it becomes a job with a HyperparameterTuningJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and HyperparameterTuningJob.state is set to `CANCELLED`." }, "get": { "description": "Gets a HyperparameterTuningJob", "response": { "$ref": "GoogleCloudAiplatformV1beta1HyperparameterTuningJob" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The name of the HyperparameterTuningJob resource. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.hyperparameterTuningJobs.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}" } }, "resources": { "operations": { "methods": { "wait": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "list": { "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", "required": true, "type": "string" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.get", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "extensions": { "methods": { "get": { "parameters": { "name": { "location": "path", "description": "Required. The name of the Extension resource. Format: `projects/{project}/locations/{location}/extensions/{extension}`", "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Extension" }, "description": "Gets an Extension.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.extensions.get" }, "import": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Imports an Extension.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "description": "Required. The resource name of the Location to import the Extension in. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.extensions.import", "path": "v1beta1/{+parent}/extensions:import", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1Extension" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions:import" }, "delete": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the Extension resource to be deleted. Format: `projects/{project}/locations/{location}/extensions/{extension}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes an Extension.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}", "id": "aiplatform.projects.locations.extensions.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "list": { "parameters": { "filter": { "description": "Optional. The standard list filter. Supported fields: * `display_name` * `create_time` * `update_time` More detail in [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to list the Extensions from. Format: `projects/{project}/locations/{location}`", "location": "path" }, "pageToken": { "description": "Optional. The standard list page token.", "location": "query", "type": "string" }, "orderBy": { "type": "string", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", "location": "query" }, "pageSize": { "location": "query", "format": "int32", "description": "Optional. The standard list page size.", "type": "integer" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListExtensionsResponse" }, "description": "Lists Extensions in a location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions", "path": "v1beta1/{+parent}/extensions", "httpMethod": "GET", "id": "aiplatform.projects.locations.extensions.list" }, "patch": { "parameters": { "name": { "location": "path", "description": "Identifier. The resource name of the Extension.", "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", "required": true, "type": "string" }, "updateMask": { "description": "Required. Mask specifying which fields to update. Supported fields: * `display_name` * `description` * `runtime_config` * `tool_use_examples` * `manifest.description`", "location": "query", "format": "google-fieldmask", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates an Extension.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Extension" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}", "id": "aiplatform.projects.locations.extensions.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1beta1Extension" } }, "execute": { "request": { "$ref": "GoogleCloudAiplatformV1beta1ExecuteExtensionRequest" }, "path": "v1beta1/{+name}:execute", "httpMethod": "POST", "id": "aiplatform.projects.locations.extensions.execute", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}:execute", "response": { "$ref": "GoogleCloudAiplatformV1beta1ExecuteExtensionResponse" }, "description": "Executes the request against a given extension.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. Name (identifier) of the extension; Format: `projects/{project}/locations/{location}/extensions/{extension}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "query": { "request": { "$ref": "GoogleCloudAiplatformV1beta1QueryExtensionRequest" }, "id": "aiplatform.projects.locations.extensions.query", "path": "v1beta1/{+name}:query", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}:query", "description": "Queries an extension with a default controller.", "response": { "$ref": "GoogleCloudAiplatformV1beta1QueryExtensionResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", "required": true, "location": "path", "description": "Required. Name (identifier) of the extension; Format: `projects/{project}/locations/{location}/extensions/{extension}`" } }, "parameterOrder": [ "name" ] } }, "resources": { "operations": { "methods": { "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.extensions.operations.wait", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "list": { "id": "aiplatform.projects.locations.extensions.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." } }, "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.extensions.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.extensions.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "get": { "id": "aiplatform.projects.locations.extensions.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensions/{extensionsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/extensions/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] } } } } }, "migratableResources": { "methods": { "search": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources:search", "request": { "$ref": "GoogleCloudAiplatformV1beta1SearchMigratableResourcesRequest" }, "id": "aiplatform.projects.locations.migratableResources.search", "path": "v1beta1/{+parent}/migratableResources:search", "httpMethod": "POST", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The location that the migratable resources should be searched from. It's the Vertex AI location that the resources can be migrated to, not the resources' original location. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "parameterOrder": [ "parent" ], "description": "Searches all of the resources in automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com that can be migrated to Vertex AI's given location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1SearchMigratableResourcesResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "batchMigrate": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Batch migrates resources from ml.googleapis.com, automl.googleapis.com, and datalabeling.googleapis.com to Vertex AI.", "parameters": { "parent": { "description": "Required. The location of the migrated resource will live in. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/migratableResources:batchMigrate", "httpMethod": "POST", "id": "aiplatform.projects.locations.migratableResources.batchMigrate", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchMigrateResourcesRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources:batchMigrate" } }, "resources": { "operations": { "methods": { "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}", "id": "aiplatform.projects.locations.migratableResources.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.migratableResources.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.migratableResources.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+$", "required": true }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.migratableResources.operations.list" }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.migratableResources.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ] } } } } }, "ragCorpora": { "methods": { "delete": { "id": "aiplatform.projects.locations.ragCorpora.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}", "description": "Deletes a RagCorpus.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the RagCorpus resource to be deleted. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`" }, "force": { "type": "boolean", "location": "query", "description": "Optional. If set to true, any RagFiles in this RagCorpus will also be deleted. Otherwise, the request will only work if the RagCorpus has no RagFiles." }, "forceDelete": { "type": "boolean", "description": "Optional. If set to true, any errors generated by external vector database during the deletion will be ignored. The default value is false.", "location": "query" } }, "parameterOrder": [ "name" ] }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the RagCorpus resource. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1RagCorpus" }, "description": "Gets a RagCorpus.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.ragCorpora.get" }, "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora", "path": "v1beta1/{+parent}/ragCorpora", "httpMethod": "POST", "id": "aiplatform.projects.locations.ragCorpora.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1RagCorpus" }, "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location to create the RagCorpus in. Format: `projects/{project}/locations/{location}`" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates a RagCorpus." }, "list": { "id": "aiplatform.projects.locations.ragCorpora.list", "path": "v1beta1/{+parent}/ragCorpora", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists RagCorpora in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListRagCorporaResponse" }, "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location from which to list the RagCorpora. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "pageToken": { "description": "Optional. The standard list page token. Typically obtained via ListRagCorporaResponse.next_page_token of the previous VertexRagDataService.ListRagCorpora call.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The standard list page size. The maximum value is 100. If not specified, a default value of 100 will be used." } }, "parameterOrder": [ "parent" ] }, "patch": { "parameters": { "name": { "location": "path", "description": "Output only. The resource name of the RagCorpus.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Updates a RagCorpus.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1RagCorpus" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.ragCorpora.patch" } }, "resources": { "ragDataSchemas": { "methods": { "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1RagDataSchema" }, "description": "Creates a RagDataSchema.", "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the RagCorpus to create the RagDataSchema in. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "required": true }, "ragDataSchemaId": { "location": "query", "description": "Optional. The ID to use for the RagDataSchema, which will become the final component of the RagDataSchema's resource name if the user chooses to specify. Otherwise, RagDataSchema id will be generated by system. This value should be up to 63 characters, and valid characters are /a-z-/. The first character must be a letter, the last could be a letter or a number.", "type": "string" } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/ragDataSchemas", "httpMethod": "POST", "id": "aiplatform.projects.locations.ragCorpora.ragDataSchemas.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1RagDataSchema" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragDataSchemas" }, "batchDelete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Batch Deletes one or more RagDataSchemas", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the RagCorpus from which to delete the RagDataSchemas. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.ragCorpora.ragDataSchemas.batchDelete", "path": "v1beta1/{+parent}/ragDataSchemas:batchDelete", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchDeleteRagDataSchemasRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragDataSchemas:batchDelete" }, "list": { "parameters": { "pageSize": { "description": "Optional. The standard list page size. The maximum value is 100. If not specified, a default value of 100 will be used.", "location": "query", "format": "int32", "type": "integer" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token. Typically obtained via ListRagDataSchemasResponse.next_page_token of the previous VertexRagDataService.ListRagDataSchemas call." }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the RagCorpus from which to list the RagDataSchemas. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists RagDataSchemas in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListRagDataSchemasResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragDataSchemas", "id": "aiplatform.projects.locations.ragCorpora.ragDataSchemas.list", "path": "v1beta1/{+parent}/ragDataSchemas", "httpMethod": "GET" }, "batchCreate": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragDataSchemas:batchCreate", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchCreateRagDataSchemasRequest" }, "id": "aiplatform.projects.locations.ragCorpora.ragDataSchemas.batchCreate", "path": "v1beta1/{+parent}/ragDataSchemas:batchCreate", "httpMethod": "POST", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the RagCorpus to create the RagDataSchemas in. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`" } }, "parameterOrder": [ "parent" ], "description": "Batch Create one or more RagDataSchemas", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "parameters": { "name": { "description": "Required. The name of the RagDataSchema resource to be deleted. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragDataSchemas/{rag_data_schema}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragDataSchemas/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a RagDataSchema.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragDataSchemas/{ragDataSchemasId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.ragCorpora.ragDataSchemas.delete" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragDataSchemas/[^/]+$", "required": true, "description": "Required. The name of the RagDataSchema resource. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragDataSchemas/{rag_data_schema}`", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1RagDataSchema" }, "description": "Gets a RagDataSchema.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragDataSchemas/{ragDataSchemasId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.ragCorpora.ragDataSchemas.get" } } }, "operations": { "methods": { "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.ragCorpora.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}" }, "cancel": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.ragCorpora.operations.cancel" }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.ragCorpora.operations.delete" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations", "id": "aiplatform.projects.locations.ragCorpora.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "wait": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.ragCorpora.operations.wait" } } }, "ragFiles": { "methods": { "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a RagFile.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the RagFile resource to be deleted. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}`" }, "forceDelete": { "type": "boolean", "description": "Optional. If set to true, any errors generated by external vector database during the deletion will be ignored. The default value is false.", "location": "query" } }, "parameterOrder": [ "name" ] }, "import": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles:import", "request": { "$ref": "GoogleCloudAiplatformV1beta1ImportRagFilesRequest" }, "id": "aiplatform.projects.locations.ragCorpora.ragFiles.import", "path": "v1beta1/{+parent}/ragFiles:import", "httpMethod": "POST", "parameters": { "parent": { "location": "path", "description": "Required. The name of the RagCorpus resource into which to import files. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "description": "Import files from Google Cloud Storage or Google Drive into a RagCorpus.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "parameters": { "name": { "location": "path", "description": "Required. The name of the RagFile resource. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Gets a RagFile.", "response": { "$ref": "GoogleCloudAiplatformV1beta1RagFile" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "list": { "id": "aiplatform.projects.locations.ragCorpora.ragFiles.list", "path": "v1beta1/{+parent}/ragFiles", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists RagFiles in a RagCorpus.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListRagFilesResponse" }, "parameters": { "parent": { "description": "Required. The resource name of the RagCorpus from which to list the RagFiles. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "required": true, "type": "string" }, "pageToken": { "type": "string", "description": "Optional. The standard list page token. Typically obtained via ListRagFilesResponse.next_page_token of the previous VertexRagDataService.ListRagFiles call.", "location": "query" }, "pageSize": { "location": "query", "format": "int32", "description": "Optional. The standard list page size. The maximum value is 100. If not specified, a default value of 100 will be used.", "type": "integer" } }, "parameterOrder": [ "parent" ] } }, "resources": { "operations": { "methods": { "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}" }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.list", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}:wait" } } }, "ragMetadata": { "methods": { "patch": { "description": "Updates a RagMetadata.", "response": { "$ref": "GoogleCloudAiplatformV1beta1RagMetadata" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/ragMetadata/[^/]+$", "required": true, "location": "path", "description": "Identifier. Resource name of the RagMetadata. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}/ragMetadata/{rag_metadata}`" } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1RagMetadata" }, "id": "aiplatform.projects.locations.ragCorpora.ragFiles.ragMetadata.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/ragMetadata/{ragMetadataId}" }, "list": { "parameters": { "pageSize": { "description": "Optional. The standard list page size. The maximum value is 100. If not specified, a default value of 100 will be used.", "location": "query", "format": "int32", "type": "integer" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token. Typically obtained via ListRagMetadataResponse.next_page_token of the previous VertexRagDataService.ListRagMetadata call." }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the RagFile from which to list the RagMetadata. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}`" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListRagMetadataResponse" }, "description": "Lists RagMetadata in a RagFile.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/ragMetadata", "path": "v1beta1/{+parent}/ragMetadata", "httpMethod": "GET", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.ragMetadata.list" }, "create": { "parameters": { "parent": { "location": "path", "description": "Required. The parent resource where this metadata will be created. Format: `projects/{project_number}/locations/{location_id}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$", "required": true }, "ragMetadataId": { "location": "query", "description": "Optional. The ID to use for the metadata, which will become the final component of the metadata's resource name if the user chooses to specify. Otherwise, metadata id will be generated by system. This value should be up to 63 characters, and valid characters are /a-z-/. The first character must be a letter, the last could be a letter or a number.", "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1RagMetadata" }, "description": "Creates a RagMetadata.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/ragMetadata", "path": "v1beta1/{+parent}/ragMetadata", "httpMethod": "POST", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.ragMetadata.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1RagMetadata" } }, "batchDelete": { "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$", "required": true, "description": "Required. The resource name of the RagFile from which to delete the RagMetadata. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}`", "location": "path" } }, "parameterOrder": [ "parent" ], "description": "Batch Deletes one or more RagMetadata.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/ragMetadata:batchDelete", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchDeleteRagMetadataRequest" }, "id": "aiplatform.projects.locations.ragCorpora.ragFiles.ragMetadata.batchDelete", "path": "v1beta1/{+parent}/ragMetadata:batchDelete", "httpMethod": "POST" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/ragMetadata/{ragMetadataId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.ragMetadata.get", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/ragMetadata/[^/]+$", "required": true, "description": "Required. The name of the RagMetadata resource. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}/ragMetadata/{rag_metadata}`", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1RagMetadata" }, "description": "Gets a RagMetadata.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "id": "aiplatform.projects.locations.ragCorpora.ragFiles.ragMetadata.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/ragMetadata/{ragMetadataId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a RagMetadata.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "description": "Required. The name of the RagMetadata resource to be deleted. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}/ragMetadata/{rag_metadata}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/ragMetadata/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "batchCreate": { "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$", "required": true, "type": "string", "description": "Required. The parent resource where the RagMetadata will be created. Format: `projects/{project_number}/locations/{location_id}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}`", "location": "path" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Batch Create one or more RagMetadatas", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/ragMetadata:batchCreate", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchCreateRagMetadataRequest" }, "path": "v1beta1/{+parent}/ragMetadata:batchCreate", "httpMethod": "POST", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.ragMetadata.batchCreate" } } } } } } }, "cachedContents": { "methods": { "delete": { "parameters": { "name": { "location": "path", "description": "Required. The resource name referring to the cached content", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/cachedContents/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes cached content", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/cachedContents/{cachedContentsId}", "id": "aiplatform.projects.locations.cachedContents.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "get": { "parameters": { "name": { "description": "Required. The resource name referring to the cached content", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/cachedContents/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1CachedContent" }, "description": "Gets cached content configurations", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/cachedContents/{cachedContentsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.cachedContents.get" }, "create": { "path": "v1beta1/{+parent}/cachedContents", "httpMethod": "POST", "id": "aiplatform.projects.locations.cachedContents.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1CachedContent" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/cachedContents", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1CachedContent" }, "description": "Creates cached content, this call will initialize the cached content in the data storage, and users need to pay for the cache data storage.", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The parent resource where the cached content will be created", "location": "path" } }, "parameterOrder": [ "parent" ] }, "patch": { "description": "Updates cached content configurations", "response": { "$ref": "GoogleCloudAiplatformV1beta1CachedContent" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/cachedContents/[^/]+$", "required": true, "location": "path", "description": "Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}" }, "updateMask": { "description": "Required. The list of fields to update.", "location": "query", "format": "google-fieldmask", "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1CachedContent" }, "id": "aiplatform.projects.locations.cachedContents.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/cachedContents/{cachedContentsId}" }, "list": { "parameters": { "parent": { "location": "path", "description": "Required. The parent, which owns this collection of cached contents.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "pageToken": { "type": "string", "location": "query", "description": "Optional. A page token, received from a previous `ListCachedContents` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `ListCachedContents` must match the call that provided the page token." }, "pageSize": { "type": "integer", "description": "Optional. The maximum number of cached contents to return. The service may return fewer than this value. If unspecified, some default (under maximum) number of items will be returned. The maximum value is 1000; values above 1000 will be coerced to 1000.", "location": "query", "format": "int32" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListCachedContentsResponse" }, "description": "Lists cached contents in a project", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/cachedContents", "path": "v1beta1/{+parent}/cachedContents", "httpMethod": "GET", "id": "aiplatform.projects.locations.cachedContents.list" } } }, "publishers": { "resources": { "models": { "methods": { "setPublisherModelConfig": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:setPublisherModelConfig", "request": { "$ref": "GoogleCloudAiplatformV1beta1SetPublisherModelConfigRequest" }, "path": "v1beta1/{+name}:setPublisherModelConfig", "httpMethod": "POST", "id": "aiplatform.projects.locations.publishers.models.setPublisherModelConfig", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "description": "Required. The name of the publisher model, in the format of `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Sets (creates or updates) configs of publisher models. For example, sets the request/response logging config.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "serverStreamingPredict": { "parameters": { "endpoint": { "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "parameterOrder": [ "endpoint" ], "description": "Perform a server-side streaming online prediction request for Vertex LLM streaming.", "response": { "$ref": "GoogleCloudAiplatformV1beta1StreamingPredictResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:serverStreamingPredict", "request": { "$ref": "GoogleCloudAiplatformV1beta1StreamingPredictRequest" }, "id": "aiplatform.projects.locations.publishers.models.serverStreamingPredict", "path": "v1beta1/{+endpoint}:serverStreamingPredict", "httpMethod": "POST" }, "fetchPredictOperation": { "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true } }, "parameterOrder": [ "endpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Fetch an asynchronous online prediction operation.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:fetchPredictOperation", "path": "v1beta1/{+endpoint}:fetchPredictOperation", "httpMethod": "POST", "id": "aiplatform.projects.locations.publishers.models.fetchPredictOperation", "request": { "$ref": "GoogleCloudAiplatformV1beta1FetchPredictOperationRequest" } }, "streamGenerateContent": { "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "description": "Generate content with multimodal inputs with streaming support.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "model": { "location": "path", "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true } }, "parameterOrder": [ "model" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "path": "v1beta1/{+model}:streamGenerateContent", "httpMethod": "POST", "id": "aiplatform.projects.locations.publishers.models.streamGenerateContent", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:streamGenerateContent" }, "streamRawPredict": { "response": { "$ref": "GoogleApiHttpBody" }, "description": "Perform a streaming online prediction with an arbitrary HTTP payload.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1StreamRawPredictRequest" }, "path": "v1beta1/{+endpoint}:streamRawPredict", "httpMethod": "POST", "id": "aiplatform.projects.locations.publishers.models.streamRawPredict", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:streamRawPredict" }, "countTokens": { "response": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensResponse" }, "description": "Perform a token counting.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path" } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensRequest" }, "path": "v1beta1/{+endpoint}:countTokens", "httpMethod": "POST", "id": "aiplatform.projects.locations.publishers.models.countTokens", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:countTokens" }, "predict": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1PredictResponse" }, "description": "", "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "parameterOrder": [ "endpoint" ], "path": "v1beta1/{+endpoint}:predict", "httpMethod": "POST", "id": "aiplatform.projects.locations.publishers.models.predict", "request": { "$ref": "GoogleCloudAiplatformV1beta1PredictRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:predict" }, "generateContent": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:generateContent", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "id": "aiplatform.projects.locations.publishers.models.generateContent", "path": "v1beta1/{+model}:generateContent", "httpMethod": "POST", "parameters": { "model": { "location": "path", "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true } }, "parameterOrder": [ "model" ], "description": "Generate content with multimodal inputs.", "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ] }, "embedContent": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:embedContent", "id": "aiplatform.projects.locations.publishers.models.embedContent", "path": "v1beta1/{+model}:embedContent", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1EmbedContentRequest" }, "parameters": { "model": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`" } }, "parameterOrder": [ "model" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Embed content with multimodal inputs.", "response": { "$ref": "GoogleCloudAiplatformV1beta1EmbedContentResponse" } }, "fetchPublisherModelConfig": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Fetches the configs of publisher models.", "response": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelConfig" }, "parameters": { "name": { "description": "Required. The name of the publisher model, in the format of `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.publishers.models.fetchPublisherModelConfig", "path": "v1beta1/{+name}:fetchPublisherModelConfig", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:fetchPublisherModelConfig" }, "rawPredict": { "id": "aiplatform.projects.locations.publishers.models.rawPredict", "path": "v1beta1/{+endpoint}:rawPredict", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1RawPredictRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:rawPredict", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Perform an online prediction with an arbitrary HTTP payload. The response includes the following HTTP headers: * `X-Vertex-AI-Endpoint-Id`: ID of the Endpoint that served this prediction. * `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's DeployedModel that served this prediction.", "response": { "$ref": "GoogleApiHttpBody" }, "parameters": { "endpoint": { "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path" } }, "parameterOrder": [ "endpoint" ] }, "export": { "parameters": { "name": { "location": "path", "description": "Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}@{version_id}`, or `publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001`", "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true, "type": "string" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The Location to export the model weights from Format: `projects/{project}/locations/{location}`" } }, "parameterOrder": [ "parent", "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Exports a publisher model to a user provided Google Cloud Storage bucket.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:export", "path": "v1beta1/{+parent}/{+name}:export", "httpMethod": "POST", "id": "aiplatform.projects.locations.publishers.models.export", "request": { "$ref": "GoogleCloudAiplatformV1beta1ExportPublisherModelRequest" } }, "predictLongRunning": { "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "location": "path" } }, "parameterOrder": [ "endpoint" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:predictLongRunning", "request": { "$ref": "GoogleCloudAiplatformV1beta1PredictLongRunningRequest" }, "path": "v1beta1/{+endpoint}:predictLongRunning", "httpMethod": "POST", "id": "aiplatform.projects.locations.publishers.models.predictLongRunning" }, "computeTokens": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:computeTokens", "id": "aiplatform.projects.locations.publishers.models.computeTokens", "path": "v1beta1/{+endpoint}:computeTokens", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensRequest" }, "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids.", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "endpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Return a list of tokens based on the input text.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensResponse" } }, "getIamPolicy": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleIamV1Policy" }, "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "parameters": { "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "type": "string", "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" }, "options.requestedPolicyVersion": { "type": "integer", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "location": "query", "format": "int32" } }, "parameterOrder": [ "resource" ], "path": "v1beta1/{+resource}:getIamPolicy", "httpMethod": "POST", "id": "aiplatform.projects.locations.publishers.models.getIamPolicy", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:getIamPolicy" } }, "resources": { "invoke": { "methods": { "invoke": { "id": "aiplatform.projects.locations.publishers.models.invoke.invoke", "path": "v1beta1/{+endpoint}/invoke/{+invokeId}", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1InvokeRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}/invoke/{invokeId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request.", "response": { "$ref": "GoogleApiHttpBody" }, "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" }, "invokeId": { "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "endpoint", "invokeId" ] } } } } } } }, "customJobs": { "methods": { "cancel": { "request": { "$ref": "GoogleCloudAiplatformV1beta1CancelCustomJobRequest" }, "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.customJobs.cancel", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Cancels a CustomJob. Starts asynchronous cancellation on the CustomJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetCustomJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the CustomJob is not deleted; instead it becomes a job with a CustomJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and CustomJob.state is set to `CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The name of the CustomJob to cancel. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "delete": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the CustomJob resource to be deleted. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a CustomJob.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}", "id": "aiplatform.projects.locations.customJobs.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a CustomJob.", "response": { "$ref": "GoogleCloudAiplatformV1beta1CustomJob" }, "parameters": { "name": { "description": "Required. The name of the CustomJob resource. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.customJobs.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}" }, "create": { "path": "v1beta1/{+parent}/customJobs", "httpMethod": "POST", "id": "aiplatform.projects.locations.customJobs.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1CustomJob" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1CustomJob" }, "description": "Creates a CustomJob. A created CustomJob right away will be attempted to be run.", "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location to create the CustomJob in. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ] }, "list": { "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to list the CustomJobs from. Format: `projects/{project}/locations/{location}`", "location": "path" }, "filter": { "location": "query", "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", "type": "string" }, "pageToken": { "description": "The standard list page token. Typically obtained via ListCustomJobsResponse.next_page_token of the previous JobService.ListCustomJobs call.", "location": "query", "type": "string" }, "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [ "parent" ], "description": "Lists CustomJobs in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListCustomJobsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs", "id": "aiplatform.projects.locations.customJobs.list", "path": "v1beta1/{+parent}/customJobs", "httpMethod": "GET" } }, "resources": { "operations": { "methods": { "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.customJobs.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "cancel": { "id": "aiplatform.projects.locations.customJobs.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.customJobs.operations.delete", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "id": "aiplatform.projects.locations.customJobs.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", "required": true }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "parameterOrder": [ "name" ] }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.customJobs.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "studies": { "methods": { "create": { "request": { "$ref": "GoogleCloudAiplatformV1beta1Study" }, "path": "v1beta1/{+parent}/studies", "httpMethod": "POST", "id": "aiplatform.projects.locations.studies.create", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies", "response": { "$ref": "GoogleCloudAiplatformV1beta1Study" }, "description": "Creates a Study. A resource name will be generated after creation of the Study.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location to create the CustomJob in. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ] }, "list": { "path": "v1beta1/{+parent}/studies", "httpMethod": "GET", "id": "aiplatform.projects.locations.studies.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListStudiesResponse" }, "description": "Lists all the studies in a region for an associated project.", "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the Location to list the Study from. Format: `projects/{project}/locations/{location}`" }, "pageToken": { "description": "Optional. A page token to request the next page of results. If unspecified, there are no subsequent pages.", "location": "query", "type": "string" }, "pageSize": { "description": "Optional. The maximum number of studies to return per \"page\" of results. If unspecified, service will pick an appropriate default.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [ "parent" ] }, "lookup": { "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location to get the Study from. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Study" }, "description": "Looks a study up using the user-defined display_name field instead of the fully qualified resource name.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies:lookup", "path": "v1beta1/{+parent}/studies:lookup", "httpMethod": "POST", "id": "aiplatform.projects.locations.studies.lookup", "request": { "$ref": "GoogleCloudAiplatformV1beta1LookupStudyRequest" } }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.studies.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a Study.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Study resource to be deleted. Format: `projects/{project}/locations/{location}/studies/{study}`" } }, "parameterOrder": [ "name" ] }, "get": { "id": "aiplatform.projects.locations.studies.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}", "description": "Gets a Study by name.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Study" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the Study resource. Format: `projects/{project}/locations/{location}/studies/{study}`" } }, "parameterOrder": [ "name" ] } }, "resources": { "operations": { "methods": { "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.studies.operations.cancel" }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.studies.operations.delete" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.studies.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "wait": { "id": "aiplatform.projects.locations.studies.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.studies.operations.list", "parameters": { "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "required": true, "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." } } }, "trials": { "methods": { "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}", "id": "aiplatform.projects.locations.studies.trials.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "Required. The name of the Trial resource. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a Trial.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Trial" } }, "listOptimalTrials": { "id": "aiplatform.projects.locations.studies.trials.listOptimalTrials", "path": "v1beta1/{+parent}/trials:listOptimalTrials", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1ListOptimalTrialsRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials:listOptimalTrials", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists the pareto-optimal Trials for multi-objective Study or the optimal Trials for single-objective Study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListOptimalTrialsResponse" }, "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "required": true, "description": "Required. The name of the Study that the optimal Trial belongs to.", "location": "path" } }, "parameterOrder": [ "parent" ] }, "addTrialMeasurement": { "request": { "$ref": "GoogleCloudAiplatformV1beta1AddTrialMeasurementRequest" }, "id": "aiplatform.projects.locations.studies.trials.addTrialMeasurement", "path": "v1beta1/{+trialName}:addTrialMeasurement", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:addTrialMeasurement", "description": "Adds a measurement of the objective metrics to a Trial. This measurement is assumed to have been taken before the Trial is complete.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Trial" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "trialName": { "location": "path", "description": "Required. The name of the trial to add measurement. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "required": true } }, "parameterOrder": [ "trialName" ] }, "checkTrialEarlyStoppingState": { "path": "v1beta1/{+trialName}:checkTrialEarlyStoppingState", "httpMethod": "POST", "id": "aiplatform.projects.locations.studies.trials.checkTrialEarlyStoppingState", "request": { "$ref": "GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:checkTrialEarlyStoppingState", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Checks whether a Trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.", "parameters": { "trialName": { "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "required": true } }, "parameterOrder": [ "trialName" ] }, "delete": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a Trial.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.studies.trials.delete" }, "stop": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:stop", "request": { "$ref": "GoogleCloudAiplatformV1beta1StopTrialRequest" }, "id": "aiplatform.projects.locations.studies.trials.stop", "path": "v1beta1/{+name}:stop", "httpMethod": "POST", "parameters": { "name": { "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Stops a Trial.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Trial" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "parent": { "description": "Required. The resource name of the Study to list the Trial from. Format: `projects/{project}/locations/{location}/studies/{study}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "required": true }, "pageToken": { "location": "query", "description": "Optional. A page token to request the next page of results. If unspecified, there are no subsequent pages.", "type": "string" }, "pageSize": { "type": "integer", "description": "Optional. The number of Trials to retrieve per \"page\" of results. If unspecified, the service will pick an appropriate default.", "location": "query", "format": "int32" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListTrialsResponse" }, "description": "Lists the Trials associated with a Study.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials", "path": "v1beta1/{+parent}/trials", "httpMethod": "GET", "id": "aiplatform.projects.locations.studies.trials.list" }, "complete": { "path": "v1beta1/{+name}:complete", "httpMethod": "POST", "id": "aiplatform.projects.locations.studies.trials.complete", "request": { "$ref": "GoogleCloudAiplatformV1beta1CompleteTrialRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:complete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Trial" }, "description": "Marks a Trial as complete.", "parameters": { "name": { "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "suggest": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials:suggest", "request": { "$ref": "GoogleCloudAiplatformV1beta1SuggestTrialsRequest" }, "path": "v1beta1/{+parent}/trials:suggest", "httpMethod": "POST", "id": "aiplatform.projects.locations.studies.trials.suggest", "parameters": { "parent": { "description": "Required. The project and location that the Study belongs to. Format: `projects/{project}/locations/{location}/studies/{study}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Adds one or more Trials to a Study, with parameter values suggested by Vertex AI Vizier. Returns a long-running operation associated with the generation of Trial suggestions. When this long-running operation succeeds, it will contain a SuggestTrialsResponse.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "create": { "response": { "$ref": "GoogleCloudAiplatformV1beta1Trial" }, "description": "Adds a user provided Trial to a Study.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Study to create the Trial in. Format: `projects/{project}/locations/{location}/studies/{study}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1Trial" }, "path": "v1beta1/{+parent}/trials", "httpMethod": "POST", "id": "aiplatform.projects.locations.studies.trials.create", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials" } }, "resources": { "operations": { "methods": { "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.studies.trials.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.studies.trials.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.studies.trials.operations.get", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." }, "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.studies.trials.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}:wait" }, "list": { "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations", "id": "aiplatform.projects.locations.studies.trials.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" } } } } } } }, "models": { "methods": { "copy": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models:copy", "path": "v1beta1/{+parent}/models:copy", "httpMethod": "POST", "id": "aiplatform.projects.locations.models.copy", "request": { "$ref": "GoogleCloudAiplatformV1beta1CopyModelRequest" }, "parameters": { "parent": { "description": "Required. The resource name of the Location into which to copy the Model. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Copies an already existing Vertex AI Model into the specified Location. The source Model must exist in the same Project. When copying custom Models, the users themselves are responsible for Model.metadata content to be region-agnostic, as well as making sure that any resources (e.g. files) it depends on remain accessible." }, "testIamPermissions": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:testIamPermissions", "id": "aiplatform.projects.locations.models.testIamPermissions", "path": "v1beta1/{+resource}:testIamPermissions", "httpMethod": "POST", "parameters": { "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true, "type": "string", "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" }, "permissions": { "repeated": true, "type": "string", "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", "location": "query" } }, "parameterOrder": [ "resource" ], "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "parameters": { "name": { "description": "Required. The name of the Model resource. Format: `projects/{project}/locations/{location}/models/{model}` In order to retrieve a specific version of the model, also provide the version ID or version alias. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` If no version ID or alias is specified, the \"default\" version will be returned. The \"default\" version alias is created for the first version of the model, and can be moved to other versions later on. There will be exactly one default version.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Model" }, "description": "Gets a Model.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.models.get" }, "list": { "parameters": { "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "readMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token. Typically obtained via ListModelsResponse.next_page_token of the previous ModelService.ListModels call." }, "filter": { "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `model` supports = and !=. `model` represents the Model ID, i.e. the last segment of the Model's resource name. * `display_name` supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. * `base_model_name` only supports = Some examples: * `model=1234` * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"` * `baseModelName=\"text-bison\"`", "location": "query", "type": "string" }, "parent": { "location": "path", "description": "Required. The resource name of the Location to list the Models from. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "description": "Lists Models in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListModelsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models", "id": "aiplatform.projects.locations.models.list", "path": "v1beta1/{+parent}/models", "httpMethod": "GET" }, "setIamPolicy": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:setIamPolicy", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "path": "v1beta1/{+resource}:setIamPolicy", "httpMethod": "POST", "id": "aiplatform.projects.locations.models.setIamPolicy", "parameters": { "resource": { "location": "path", "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "resource" ], "response": { "$ref": "GoogleIamV1Policy" }, "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "mergeVersionAliases": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the model version to merge aliases, with a version ID explicitly included. Example: `projects/{project}/locations/{location}/models/{model}@1234`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Merges a set of aliases for a Model version.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Model" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:mergeVersionAliases", "id": "aiplatform.projects.locations.models.mergeVersionAliases", "path": "v1beta1/{+name}:mergeVersionAliases", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1MergeVersionAliasesRequest" } }, "patch": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1Model" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.models.patch", "parameters": { "name": { "description": "Identifier. The resource name of the Model.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true, "type": "string" }, "updateMask": { "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask.", "location": "query", "format": "google-fieldmask", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Model" }, "description": "Updates a Model.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "listCheckpoints": { "path": "v1beta1/{+name}:listCheckpoints", "httpMethod": "GET", "id": "aiplatform.projects.locations.models.listCheckpoints", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:listCheckpoints", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListModelVersionCheckpointsResponse" }, "description": "Lists checkpoints of the specified model version.", "parameters": { "name": { "location": "path", "description": "Required. The name of the model version to list checkpoints for. `projects/{project}/locations/{location}/models/{model}@{version}` Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` If no version ID or alias is specified, the latest version will be used.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token. Typically obtained via next_page_token of the previous ListModelVersionCheckpoints call." }, "pageSize": { "location": "query", "format": "int32", "description": "Optional. The standard list page size.", "type": "integer" } }, "parameterOrder": [ "name" ] }, "upload": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models:upload", "path": "v1beta1/{+parent}/models:upload", "httpMethod": "POST", "id": "aiplatform.projects.locations.models.upload", "request": { "$ref": "GoogleCloudAiplatformV1beta1UploadModelRequest" }, "parameters": { "parent": { "description": "Required. The resource name of the Location into which to upload the Model. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Uploads a Model artifact into Vertex AI." }, "updateExplanationDataset": { "parameters": { "model": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true, "description": "Required. The resource name of the Model to update. Format: `projects/{project}/locations/{location}/models/{model}`", "location": "path" } }, "parameterOrder": [ "model" ], "description": "Incrementally update the dataset used for an examples model.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:updateExplanationDataset", "request": { "$ref": "GoogleCloudAiplatformV1beta1UpdateExplanationDatasetRequest" }, "id": "aiplatform.projects.locations.models.updateExplanationDataset", "path": "v1beta1/{+model}:updateExplanationDataset", "httpMethod": "POST" }, "export": { "description": "Exports a trained, exportable Model to a location specified by the user. A Model is considered to be exportable if it has at least one supported export format.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The resource name of the Model to export. The resource name may contain version id or version alias to specify the version, if no version is specified, the default version will be exported.", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1ExportModelRequest" }, "id": "aiplatform.projects.locations.models.export", "path": "v1beta1/{+name}:export", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:export" }, "getIamPolicy": { "parameters": { "options.requestedPolicyVersion": { "location": "query", "format": "int32", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "type": "integer" }, "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true, "type": "string", "location": "path", "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." } }, "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "response": { "$ref": "GoogleIamV1Policy" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:getIamPolicy", "id": "aiplatform.projects.locations.models.getIamPolicy", "path": "v1beta1/{+resource}:getIamPolicy", "httpMethod": "POST" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a Model. A model cannot be deleted if any Endpoint resource has a DeployedModel based on the model in its deployed_models field.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "Required. The name of the Model resource to be deleted. Format: `projects/{project}/locations/{location}/models/{model}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.models.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}" }, "listVersions": { "parameters": { "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "name": { "description": "Required. The name of the model to list versions for.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true }, "readMask": { "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token. Typically obtained via next_page_token of the previous ListModelVersions call." }, "orderBy": { "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `create_time` * `update_time` Example: `update_time asc, create_time desc`.", "location": "query", "type": "string" }, "filter": { "location": "query", "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `labels.myKey=\"myValue\"`", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListModelVersionsResponse" }, "description": "Lists versions of the specified model.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:listVersions", "path": "v1beta1/{+name}:listVersions", "httpMethod": "GET", "id": "aiplatform.projects.locations.models.listVersions" }, "deleteVersion": { "parameters": { "name": { "description": "Required. The name of the model version to be deleted, with a version ID explicitly included. Example: `projects/{project}/locations/{location}/models/{model}@1234`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Deletes a Model version. Model version can only be deleted if there are no DeployedModels created from it. Deleting the only version in the Model is not allowed. Use DeleteModel for deleting the Model instead.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:deleteVersion", "id": "aiplatform.projects.locations.models.deleteVersion", "path": "v1beta1/{+name}:deleteVersion", "httpMethod": "DELETE" } }, "resources": { "operations": { "methods": { "get": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.models.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "cancel": { "id": "aiplatform.projects.locations.models.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.models.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.models.operations.list", "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.models.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}:wait" } } }, "evaluations": { "methods": { "import": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations:import", "id": "aiplatform.projects.locations.models.evaluations.import", "path": "v1beta1/{+parent}/evaluations:import", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1ImportModelEvaluationRequest" }, "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the parent model resource. Format: `projects/{project}/locations/{location}/models/{model}`" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Imports an externally generated ModelEvaluation.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluation" } }, "list": { "response": { "$ref": "GoogleCloudAiplatformV1beta1ListModelEvaluationsResponse" }, "description": "Lists ModelEvaluations in a Model.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true, "description": "Required. The resource name of the Model to list the ModelEvaluations from. Format: `projects/{project}/locations/{location}/models/{model}`", "location": "path" }, "pageToken": { "type": "string", "description": "The standard list page token. Typically obtained via ListModelEvaluationsResponse.next_page_token of the previous ModelService.ListModelEvaluations call.", "location": "query" } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/evaluations", "httpMethod": "GET", "id": "aiplatform.projects.locations.models.evaluations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.models.evaluations.get", "parameters": { "name": { "description": "Required. The name of the ModelEvaluation resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluation" }, "description": "Gets a ModelEvaluation.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "slices": { "methods": { "get": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/slices/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the ModelEvaluationSlice resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice}`", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ModelEvaluationSlice" }, "description": "Gets a ModelEvaluationSlice.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices/{slicesId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.models.evaluations.slices.get" }, "list": { "parameters": { "pageToken": { "location": "query", "description": "The standard list page token. Typically obtained via ListModelEvaluationSlicesResponse.next_page_token of the previous ModelService.ListModelEvaluationSlices call.", "type": "string" }, "filter": { "description": "The standard list filter. * `slice.dimension` - for =.", "location": "query", "type": "string" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the ModelEvaluation to list the ModelEvaluationSlices from. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "readMask": { "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask", "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists ModelEvaluationSlices in a ModelEvaluation.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListModelEvaluationSlicesResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices", "id": "aiplatform.projects.locations.models.evaluations.slices.list", "path": "v1beta1/{+parent}/slices", "httpMethod": "GET" }, "batchImport": { "parameters": { "parent": { "location": "path", "description": "Required. The name of the parent ModelEvaluationSlice resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice}`", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/slices/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "description": "Imports a list of externally generated EvaluatedAnnotations.", "response": { "$ref": "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices/{slicesId}:batchImport", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest" }, "id": "aiplatform.projects.locations.models.evaluations.slices.batchImport", "path": "v1beta1/{+parent}:batchImport", "httpMethod": "POST" } } }, "operations": { "methods": { "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.models.evaluations.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" } }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations", "id": "aiplatform.projects.locations.models.evaluations.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$", "required": true }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.models.evaluations.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.models.evaluations.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.models.evaluations.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}" } } } } } } }, "featureGroups": { "methods": { "setIamPolicy": { "parameters": { "resource": { "location": "path", "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "resource" ], "response": { "$ref": "GoogleIamV1Policy" }, "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}:setIamPolicy", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "path": "v1beta1/{+resource}:setIamPolicy", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureGroups.setIamPolicy" }, "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups", "request": { "$ref": "GoogleCloudAiplatformV1beta1FeatureGroup" }, "id": "aiplatform.projects.locations.featureGroups.create", "path": "v1beta1/{+parent}/featureGroups", "httpMethod": "POST", "parameters": { "parent": { "description": "Required. The resource name of the Location to create FeatureGroups. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "featureGroupId": { "type": "string", "location": "query", "description": "Required. The ID to use for this FeatureGroup, which will become the final component of the FeatureGroup's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location." } }, "parameterOrder": [ "parent" ], "description": "Creates a new FeatureGroup in a given project and location.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "getIamPolicy": { "parameters": { "resource": { "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true, "type": "string" }, "options.requestedPolicyVersion": { "location": "query", "format": "int32", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "type": "integer" } }, "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "response": { "$ref": "GoogleIamV1Policy" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}:getIamPolicy", "id": "aiplatform.projects.locations.featureGroups.getIamPolicy", "path": "v1beta1/{+resource}:getIamPolicy", "httpMethod": "POST" }, "patch": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Updates the parameters of a single FeatureGroup.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true, "location": "path", "description": "Identifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`" }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Field mask is used to specify the fields to be overwritten in the FeatureGroup resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `description` * `big_query` * `big_query.entity_id_columns` * `service_agent_type`" } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1FeatureGroup" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.featureGroups.patch", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups", "path": "v1beta1/{+parent}/featureGroups", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureGroups.list", "parameters": { "pageToken": { "description": "A page token, received from a previous FeatureRegistryService.ListFeatureGroups call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureRegistryService.ListFeatureGroups must match the call that provided the page token.", "location": "query", "type": "string" }, "orderBy": { "type": "string", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported Fields: * `create_time` * `update_time`", "location": "query" }, "filter": { "description": "Lists the FeatureGroups that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` FeatureGroups created or updated after 2020-01-01. * `labels.env = \"prod\"` FeatureGroups with label \"env\" set to \"prod\".", "location": "query", "type": "string" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location to list FeatureGroups. Format: `projects/{project}/locations/{location}`" }, "pageSize": { "type": "integer", "description": "The maximum number of FeatureGroups to return. The service may return fewer than this value. If unspecified, at most 100 FeatureGroups will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", "location": "query", "format": "int32" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListFeatureGroupsResponse" }, "description": "Lists FeatureGroups in a given project and location." }, "testIamPermissions": { "path": "v1beta1/{+resource}:testIamPermissions", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureGroups.testIamPermissions", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}:testIamPermissions", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "parameters": { "resource": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true, "location": "path", "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." }, "permissions": { "repeated": true, "type": "string", "location": "query", "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions)." } }, "parameterOrder": [ "resource" ] }, "delete": { "parameters": { "name": { "location": "path", "description": "Required. The name of the FeatureGroup to be deleted. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true }, "force": { "description": "If set to true, any Features under this FeatureGroup will also be deleted. (Otherwise, the request will only work if the FeatureGroup has no Features.)", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a single FeatureGroup.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.featureGroups.delete" }, "get": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the FeatureGroup resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets details of a single FeatureGroup.", "response": { "$ref": "GoogleCloudAiplatformV1beta1FeatureGroup" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}", "id": "aiplatform.projects.locations.featureGroups.get", "path": "v1beta1/{+name}", "httpMethod": "GET" } }, "resources": { "features": { "methods": { "get": { "description": "Gets details of a single Feature.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Feature" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "featureStatsAndAnomalySpec.latestStatsCount": { "type": "integer", "description": "Optional. If set, returns the most recent count of stats. Valid value is [0, 100]. If stats_time_range is set, return most recent count of stats within the stats_time_range.", "location": "query", "format": "int32" }, "name": { "description": "Required. The name of the Feature resource. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", "required": true, "type": "string" }, "featureStatsAndAnomalySpec.statsTimeRange.startTime": { "type": "string", "location": "query", "format": "google-datetime", "description": "Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start." }, "featureStatsAndAnomalySpec.statsTimeRange.endTime": { "type": "string", "location": "query", "format": "google-datetime", "description": "Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featureGroups.features.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}" }, "batchCreate": { "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest" }, "id": "aiplatform.projects.locations.featureGroups.features.batchCreate", "path": "v1beta1/{+parent}/features:batchCreate", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features:batchCreate", "description": "Creates a batch of Features in a given FeatureGroup.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true, "description": "Required. The resource name of the EntityType/FeatureGroup to create the batch of Features under. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "location": "path" } }, "parameterOrder": [ "parent" ] }, "delete": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", "required": true, "description": "Required. The name of the Features to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}`", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a single Feature.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.featureGroups.features.delete" }, "list": { "description": "Lists Features in a given FeatureGroup.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListFeaturesResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "type": "string", "description": "A page token, received from a previous FeaturestoreService.ListFeatures call or FeatureRegistryService.ListFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeatures or FeatureRegistryService.ListFeatures must match the call that provided the page token.", "location": "query" }, "orderBy": { "type": "string", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `feature_id` * `value_type` (Not supported for FeatureRegistry Feature) * `create_time` * `update_time`", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "Lists the Features that match the filter expression. The following filters are supported: * `value_type`: Supports = and != comparisons. * `create_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `update_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `value_type = DOUBLE` --\u003e Features whose type is DOUBLE. * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any Feature which has a label with 'env' as the key." }, "parent": { "description": "Required. The resource name of the Location to list Features. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true, "type": "string" }, "pageSize": { "description": "The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 1000 Features will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", "location": "query", "format": "int32", "type": "integer" }, "latestStatsCount": { "type": "integer", "description": "Only applicable for Vertex AI Feature Store (Legacy). If set, return the most recent ListFeaturesRequest.latest_stats_count of stats for each Feature in response. Valid value is [0, 10]. If number of stats exists \u003c ListFeaturesRequest.latest_stats_count, return all existing stats.", "location": "query", "format": "int32" }, "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.featureGroups.features.list", "path": "v1beta1/{+parent}/features", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features" }, "patch": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Updates the parameters of a single Feature.", "parameters": { "name": { "location": "path", "description": "Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", "required": true, "type": "string" }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Field mask is used to specify the fields to be overwritten in the Features resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `disable_monitoring` (Not supported for FeatureRegistryService Feature) * `point_of_contact` (Not supported for FeaturestoreService FeatureStore)", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.featureGroups.features.patch", "request": { "$ref": "GoogleCloudAiplatformV1beta1Feature" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}" }, "create": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates a new Feature in a given FeatureGroup.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "description": "Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true }, "featureId": { "type": "string", "description": "Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.", "location": "query" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1Feature" }, "path": "v1beta1/{+parent}/features", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureGroups.features.create", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features" } }, "resources": { "operations": { "methods": { "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureGroups.features.operations.get", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations", "id": "aiplatform.projects.locations.featureGroups.features.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", "required": true }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "delete": { "id": "aiplatform.projects.locations.featureGroups.features.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureGroups.features.operations.wait", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "operations": { "methods": { "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureGroups.operations.get", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureGroups.operations.list", "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.featureGroups.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.featureGroups.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" } } } }, "featureMonitors": { "methods": { "patch": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1FeatureMonitor" }, "id": "aiplatform.projects.locations.featureGroups.featureMonitors.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/featureMonitors/[^/]+$", "required": true, "location": "path", "description": "Identifier. Name of the FeatureMonitor. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}/featureMonitors/{featureMonitor}`" }, "updateMask": { "type": "string", "description": "Optional. Field mask is used to specify the fields to be overwritten in the FeatureMonitor resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `description` * `schedule_config` * `feature_selection_config`", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ], "description": "Updates the parameters of a single FeatureMonitor.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "id": "aiplatform.projects.locations.featureGroups.featureMonitors.list", "path": "v1beta1/{+parent}/featureMonitors", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists FeatureGroups in a given project and location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListFeatureMonitorsResponse" }, "parameters": { "pageToken": { "description": "Optional. A page token, received from a previous FeatureRegistryService.ListFeatureMonitors call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureRegistryService.ListFeatureMonitors must match the call that provided the page token.", "location": "query", "type": "string" }, "orderBy": { "type": "string", "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported Fields: * `create_time` * `update_time`" }, "filter": { "type": "string", "location": "query", "description": "Optional. Lists the FeatureMonitors that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` FeatureMonitors created or updated after 2020-01-01. * `labels.env = \"prod\"` FeatureGroups with label \"env\" set to \"prod\"." }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true, "description": "Required. The resource name of the FeatureGroup to list FeatureMonitors. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`", "location": "path" }, "pageSize": { "description": "Optional. The maximum number of FeatureGroups to return. The service may return fewer than this value. If unspecified, at most 100 FeatureMonitors will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [ "parent" ] }, "create": { "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of FeatureGroup to create FeatureMonitor. Format: `projects/{project}/locations/{location}/featureGroups/{featuregroup}`" }, "featureMonitorId": { "description": "Required. The ID to use for this FeatureMonitor, which will become the final component of the FeatureGroup's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the FeatureGroup.", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates a new FeatureMonitor in a given project, location and FeatureGroup.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors", "request": { "$ref": "GoogleCloudAiplatformV1beta1FeatureMonitor" }, "path": "v1beta1/{+parent}/featureMonitors", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureGroups.featureMonitors.create" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}", "id": "aiplatform.projects.locations.featureGroups.featureMonitors.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/featureMonitors/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the FeatureMonitor resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets details of a single FeatureMonitor.", "response": { "$ref": "GoogleCloudAiplatformV1beta1FeatureMonitor" } }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.featureGroups.featureMonitors.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a single FeatureMonitor.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The name of the FeatureMonitor to be deleted. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/featureMonitors/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] } }, "resources": { "operations": { "methods": { "get": { "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/featureMonitors/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.featureGroups.featureMonitors.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureGroups.featureMonitors.operations.list", "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/featureMonitors/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/featureMonitors/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featureGroups.featureMonitors.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}/operations/{operationsId}" }, "wait": { "id": "aiplatform.projects.locations.featureGroups.featureMonitors.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/featureMonitors/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ] } } }, "featureMonitorJobs": { "methods": { "create": { "parameters": { "parent": { "location": "path", "description": "Required. The resource name of FeatureMonitor to create FeatureMonitorJob. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}`", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/featureMonitors/[^/]+$", "required": true, "type": "string" }, "featureMonitorJobId": { "description": "Optional. Output only. System-generated ID for feature monitor job.", "location": "query", "format": "int64", "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1FeatureMonitorJob" }, "description": "Creates a new feature monitor job.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}/featureMonitorJobs", "path": "v1beta1/{+parent}/featureMonitorJobs", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureGroups.featureMonitors.featureMonitorJobs.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1FeatureMonitorJob" } }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}/featureMonitorJobs/{featureMonitorJobsId}", "id": "aiplatform.projects.locations.featureGroups.featureMonitors.featureMonitorJobs.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "description": "Required. The name of the FeatureMonitorJob resource. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_job}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/featureMonitors/[^/]+/featureMonitorJobs/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get a feature monitor job.", "response": { "$ref": "GoogleCloudAiplatformV1beta1FeatureMonitorJob" } }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/featureMonitors/{featureMonitorsId}/featureMonitorJobs", "id": "aiplatform.projects.locations.featureGroups.featureMonitors.featureMonitorJobs.list", "path": "v1beta1/{+parent}/featureMonitorJobs", "httpMethod": "GET", "parameters": { "orderBy": { "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported Fields: * `create_time`", "location": "query", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. A page token, received from a previous FeatureRegistryService.ListFeatureMonitorJobs call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureRegistryService.ListFeatureMonitorJobs must match the call that provided the page token." }, "parent": { "description": "Required. The resource name of the FeatureMonitor to list FeatureMonitorJobs. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/featureMonitors/[^/]+$", "required": true, "type": "string" }, "filter": { "location": "query", "description": "Optional. Lists the FeatureMonitorJobs that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be Examples: * `create_time \u003e \"2020-01-01\"` FeatureMonitorJobs created after 2020-01-01.", "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "Optional. The maximum number of FeatureMonitorJobs to return. The service may return fewer than this value. If unspecified, at most 100 FeatureMonitorJobs will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", "type": "integer" } }, "parameterOrder": [ "parent" ], "description": "List feature monitor jobs.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListFeatureMonitorJobsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } } } }, "trainingPipelines": { "methods": { "list": { "parameters": { "readMask": { "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "type": "string" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "filter": { "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `training_task_definition` `=`, `!=` comparisons, and `:` wildcard. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"PIPELINE_STATE_SUCCEEDED\" AND display_name:\"my_pipeline_*\"` * `state!=\"PIPELINE_STATE_FAILED\" OR display_name=\"my_pipeline\"` * `NOT display_name=\"my_pipeline\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `training_task_definition:\"*automl_text_classification*\"`", "location": "query", "type": "string" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location to list the TrainingPipelines from. Format: `projects/{project}/locations/{location}`" }, "pageToken": { "type": "string", "description": "The standard list page token. Typically obtained via ListTrainingPipelinesResponse.next_page_token of the previous PipelineService.ListTrainingPipelines call.", "location": "query" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists TrainingPipelines in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListTrainingPipelinesResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines", "id": "aiplatform.projects.locations.trainingPipelines.list", "path": "v1beta1/{+parent}/trainingPipelines", "httpMethod": "GET" }, "create": { "description": "Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run.", "response": { "$ref": "GoogleCloudAiplatformV1beta1TrainingPipeline" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location to create the TrainingPipeline in. Format: `projects/{project}/locations/{location}`" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1TrainingPipeline" }, "id": "aiplatform.projects.locations.trainingPipelines.create", "path": "v1beta1/{+parent}/trainingPipelines", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}", "id": "aiplatform.projects.locations.trainingPipelines.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "description": "Required. The name of the TrainingPipeline resource. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Gets a TrainingPipeline.", "response": { "$ref": "GoogleCloudAiplatformV1beta1TrainingPipeline" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}:cancel", "id": "aiplatform.projects.locations.trainingPipelines.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1CancelTrainingPipelineRequest" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the TrainingPipeline to cancel. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Cancels a TrainingPipeline. Starts asynchronous cancellation on the TrainingPipeline. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use PipelineService.GetTrainingPipeline or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the TrainingPipeline is not deleted; instead it becomes a pipeline with a TrainingPipeline.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and TrainingPipeline.state is set to `CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a TrainingPipeline.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "Required. The name of the TrainingPipeline resource to be deleted. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.trainingPipelines.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}" } }, "resources": { "operations": { "methods": { "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.trainingPipelines.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}" }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}", "id": "aiplatform.projects.locations.trainingPipelines.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "cancel": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.trainingPipelines.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.trainingPipelines.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.trainingPipelines.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}:wait" } } } } }, "datasets": { "methods": { "assess": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Assesses the state or validity of the dataset with respect to a given use case.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The name of the Dataset resource. Used only for MULTIMODAL datasets. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1AssessDataRequest" }, "path": "v1beta1/{+name}:assess", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.assess", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:assess" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets", "id": "aiplatform.projects.locations.datasets.list", "path": "v1beta1/{+parent}/datasets", "httpMethod": "GET", "parameters": { "parent": { "location": "path", "description": "Required. The name of the Dataset's parent resource. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "filter": { "type": "string", "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `display_name`: supports = and != * `metadata_schema_uri`: supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"`", "location": "query" }, "orderBy": { "type": "string", "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time`" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "readMask": { "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." } }, "parameterOrder": [ "parent" ], "description": "Lists Datasets in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListDatasetsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "create": { "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Location to create the Dataset in. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates a Dataset.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets", "request": { "$ref": "GoogleCloudAiplatformV1beta1Dataset" }, "path": "v1beta1/{+parent}/datasets", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.create" }, "get": { "parameters": { "readMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read." }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "description": "Required. The name of the Dataset resource.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Gets a Dataset.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Dataset" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}", "id": "aiplatform.projects.locations.datasets.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "testIamPermissions": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:testIamPermissions", "path": "v1beta1/{+resource}:testIamPermissions", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.testIamPermissions", "parameters": { "resource": { "location": "path", "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true }, "permissions": { "location": "query", "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", "repeated": true, "type": "string" } }, "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning." }, "delete": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "description": "Required. The resource name of the Dataset to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a Dataset.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.datasets.delete" }, "getIamPolicy": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:getIamPolicy", "id": "aiplatform.projects.locations.datasets.getIamPolicy", "path": "v1beta1/{+resource}:getIamPolicy", "httpMethod": "POST", "parameters": { "resource": { "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true }, "options.requestedPolicyVersion": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies)." } }, "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "response": { "$ref": "GoogleIamV1Policy" } }, "export": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:export", "path": "v1beta1/{+name}:export", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.export", "request": { "$ref": "GoogleCloudAiplatformV1beta1ExportDataRequest" }, "parameters": { "name": { "location": "path", "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Exports data from a Dataset." }, "import": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Imports data into a Dataset.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.datasets.import", "path": "v1beta1/{+name}:import", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1ImportDataRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:import" }, "patch": { "parameters": { "name": { "location": "path", "description": "Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name` * `description` * `labels`" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Dataset" }, "description": "Updates a Dataset.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1Dataset" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.datasets.patch" }, "searchDataItems": { "parameters": { "fieldMask": { "description": "Mask specifying which fields of DataItemView to read.", "location": "query", "format": "google-fieldmask", "type": "string" }, "orderByDataItem": { "location": "query", "description": "A comma-separated list of data item fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", "type": "string" }, "savedQuery": { "location": "query", "description": "The resource name of a SavedQuery(annotation set in UI). Format: `projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}` All of the search will be done in the context of this SavedQuery.", "deprecated": true, "type": "string" }, "orderByAnnotation.savedQuery": { "type": "string", "description": "Required. Saved query of the Annotation. Only Annotations belong to this saved query will be considered for ordering.", "location": "query" }, "dataset": { "location": "path", "description": "Required. The resource name of the Dataset from which to search DataItems. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true }, "pageSize": { "type": "integer", "description": "Requested page size. Server may return fewer results than requested. Default and maximum page size is 100.", "location": "query", "format": "int32" }, "dataLabelingJob": { "location": "query", "description": "The resource name of a DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}` If this field is set, all of the search will be done in the context of this DataLabelingJob.", "type": "string" }, "orderBy": { "deprecated": true, "type": "string", "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending." }, "orderByAnnotation.orderBy": { "description": "A comma-separated list of annotation fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Must also specify saved_query.", "location": "query", "type": "string" }, "dataItemFilter": { "type": "string", "description": "An expression for filtering the DataItem that will be returned. * `data_item_id` - for = or !=. * `labeled` - for = or !=. * `has_annotation(ANNOTATION_SPEC_ID)` - true only for DataItem that have at least one annotation with annotation_spec_id = `ANNOTATION_SPEC_ID` in the context of SavedQuery or DataLabelingJob. For example: * `data_item=1` * `has_annotation(5)`", "location": "query" }, "annotationsFilter": { "description": "An expression for filtering the Annotations that will be returned per DataItem. * `annotation_spec_id` - for = or !=.", "location": "query", "type": "string", "deprecated": true }, "pageToken": { "location": "query", "description": "A token identifying a page of results for the server to return Typically obtained via SearchDataItemsResponse.next_page_token of the previous DatasetService.SearchDataItems call.", "type": "string" }, "annotationFilters": { "repeated": true, "type": "string", "location": "query", "description": "An expression that specifies what Annotations will be returned per DataItem. Annotations satisfied either of the conditions will be returned. * `annotation_spec_id` - for = or !=. Must specify `saved_query_id=` - saved query id that annotations should belong to." }, "annotationsLimit": { "type": "integer", "location": "query", "format": "int32", "description": "If set, only up to this many of Annotations will be returned per DataItemView. The maximum value is 1000. If not set, the maximum value will be used." } }, "parameterOrder": [ "dataset" ], "description": "Searches DataItems in a Dataset.", "response": { "$ref": "GoogleCloudAiplatformV1beta1SearchDataItemsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:searchDataItems", "id": "aiplatform.projects.locations.datasets.searchDataItems", "path": "v1beta1/{+dataset}:searchDataItems", "httpMethod": "GET" }, "assemble": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:assemble", "request": { "$ref": "GoogleCloudAiplatformV1beta1AssembleDataRequest" }, "path": "v1beta1/{+name}:assemble", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.assemble", "parameters": { "name": { "description": "Required. The name of the Dataset resource (used only for MULTIMODAL datasets). Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Assembles each row of a multimodal dataset and writes the result into a BigQuery table.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "setIamPolicy": { "path": "v1beta1/{+resource}:setIamPolicy", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.setIamPolicy", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:setIamPolicy", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleIamV1Policy" }, "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "parameters": { "resource": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" } }, "parameterOrder": [ "resource" ] } }, "resources": { "annotationSpecs": { "methods": { "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}", "id": "aiplatform.projects.locations.datasets.annotationSpecs.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "readMask": { "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask", "type": "string" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+$", "required": true, "description": "Required. The name of the AnnotationSpec resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}`", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Gets an AnnotationSpec.", "response": { "$ref": "GoogleCloudAiplatformV1beta1AnnotationSpec" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "operations": { "methods": { "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}" }, "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:cancel" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.list", "parameters": { "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+$", "required": true }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "wait": { "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ] } } } } }, "datasetVersions": { "methods": { "get": { "response": { "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" }, "description": "Gets a Dataset version.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "readMask": { "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "type": "string" }, "name": { "location": "path", "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.datasetVersions.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}" }, "restore": { "path": "v1beta1/{+name}:restore", "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.datasetVersions.restore", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}:restore", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Restores a dataset version.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", "required": true, "description": "Required. The name of the DatasetVersion resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "location": "path" } }, "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", "id": "aiplatform.projects.locations.datasets.datasetVersions.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Deletes a Dataset version.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "id": "aiplatform.projects.locations.datasets.datasetVersions.list", "path": "v1beta1/{+parent}/datasetVersions", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions", "description": "Lists DatasetVersions in a Dataset.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListDatasetVersionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "description": "Optional. The standard list page token.", "location": "query", "type": "string" }, "orderBy": { "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", "location": "query", "type": "string" }, "filter": { "description": "Optional. The standard list filter.", "location": "query", "type": "string" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Dataset to list DatasetVersions from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" }, "pageSize": { "type": "integer", "description": "Optional. The standard list page size.", "location": "query", "format": "int32" }, "readMask": { "location": "query", "format": "google-fieldmask", "description": "Optional. Mask specifying which fields to read.", "type": "string" } }, "parameterOrder": [ "parent" ] }, "patch": { "description": "Updates a DatasetVersion.", "response": { "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Output only. Identifier. The resource name of the DatasetVersion. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", "required": true, "type": "string" }, "updateMask": { "type": "string", "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name`", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" }, "id": "aiplatform.projects.locations.datasets.datasetVersions.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}" }, "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Create a version from a Dataset.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "location": "path" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.datasets.datasetVersions.create", "path": "v1beta1/{+parent}/datasetVersions", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1DatasetVersion" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions" } } }, "savedQueries": { "methods": { "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.datasets.savedQueries.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a SavedQuery.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The resource name of the SavedQuery to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}`", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListSavedQueriesResponse" }, "description": "Lists SavedQueries in a Dataset.", "parameters": { "orderBy": { "type": "string", "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending." }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "description": "Required. The resource name of the Dataset to list SavedQueries from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "location": "path" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "readMask": { "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "type": "string" } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/savedQueries", "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.savedQueries.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries" } }, "resources": { "operations": { "methods": { "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.savedQueries.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+$", "required": true, "location": "path", "description": "The name of the operation's parent resource." } }, "parameterOrder": [ "name" ] }, "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.savedQueries.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:wait" }, "get": { "id": "aiplatform.projects.locations.datasets.savedQueries.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.datasets.savedQueries.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", "id": "aiplatform.projects.locations.datasets.savedQueries.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "operations": { "methods": { "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.datasets.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations" }, "wait": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.datasets.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.operations.get" }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.operations.cancel", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}:cancel" }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.datasets.operations.delete", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." } } }, "dataItems": { "methods": { "list": { "path": "v1beta1/{+parent}/dataItems", "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.dataItems.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListDataItemsResponse" }, "description": "Lists DataItems in a Dataset.", "parameters": { "readMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read." }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "parent": { "location": "path", "description": "Required. The resource name of the Dataset to list DataItems from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "orderBy": { "type": "string", "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending." }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ] } }, "resources": { "operations": { "methods": { "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.datasets.dataItems.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}" }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.dataItems.operations.cancel", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:cancel" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.datasets.dataItems.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" } }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.dataItems.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ] }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+$", "required": true }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.datasets.dataItems.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations" } } }, "annotations": { "methods": { "list": { "response": { "$ref": "GoogleCloudAiplatformV1beta1ListAnnotationsResponse" }, "description": "Lists Annotations belongs to a dataitem.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+$", "required": true, "description": "Required. The resource name of the DataItem to list Annotations from. Format: `projects/{project}/locations/{location}/datasets/{dataset}/dataItems/{data_item}`", "location": "path" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "orderBy": { "type": "string", "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending." }, "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/annotations", "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.dataItems.annotations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations" } }, "resources": { "operations": { "methods": { "get": { "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.cancel" }, "delete": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations" }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ] } } } } } } } } }, "modelDeploymentMonitoringJobs": { "methods": { "get": { "response": { "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob" }, "description": "Gets a ModelDeploymentMonitoringJob.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}" }, "resume": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the ModelDeploymentMonitoringJob to resume. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Resumes a paused ModelDeploymentMonitoringJob. It will start to run from next scheduled time. A deleted ModelDeploymentMonitoringJob can't be resumed.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:resume", "request": { "$ref": "GoogleCloudAiplatformV1beta1ResumeModelDeploymentMonitoringJobRequest" }, "path": "v1beta1/{+name}:resume", "httpMethod": "POST", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.resume" }, "delete": { "description": "Deletes a ModelDeploymentMonitoringJob.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the model monitoring job to delete. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}" }, "list": { "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", "location": "query" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The parent of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}`", "location": "path" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "readMask": { "type": "string", "description": "Mask specifying which fields to read", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListModelDeploymentMonitoringJobsResponse" }, "description": "Lists ModelDeploymentMonitoringJobs in a Location.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs", "path": "v1beta1/{+parent}/modelDeploymentMonitoringJobs", "httpMethod": "GET", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.list" }, "patch": { "description": "Updates a ModelDeploymentMonitoringJob.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "required": true, "location": "path", "description": "Output only. Resource name of a ModelDeploymentMonitoringJob." }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Required. The update mask is used to specify the fields to be overwritten in the ModelDeploymentMonitoringJob resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. For the objective config, the user can either provide the update mask for model_deployment_monitoring_objective_configs or any combination of its nested fields, such as: model_deployment_monitoring_objective_configs.objective_config.training_dataset. Updatable fields: * `display_name` * `model_deployment_monitoring_schedule_config` * `model_monitoring_alert_config` * `logging_sampling_strategy` * `labels` * `log_ttl` * `enable_monitoring_pipeline_logs` . and * `model_deployment_monitoring_objective_configs` . or * `model_deployment_monitoring_objective_configs.objective_config.training_dataset` * `model_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_config` * `model_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config`" } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob" }, "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}" }, "create": { "description": "Creates a ModelDeploymentMonitoringJob. It will run periodically on a configured interval.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The parent of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob" }, "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.create", "path": "v1beta1/{+parent}/modelDeploymentMonitoringJobs", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs" }, "searchModelDeploymentMonitoringStatsAnomalies": { "request": { "$ref": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequest" }, "path": "v1beta1/{+modelDeploymentMonitoringJob}:searchModelDeploymentMonitoringStatsAnomalies", "httpMethod": "POST", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.searchModelDeploymentMonitoringStatsAnomalies", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:searchModelDeploymentMonitoringStatsAnomalies", "response": { "$ref": "GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesResponse" }, "description": "Searches Model Monitoring Statistics generated within a given time window.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "modelDeploymentMonitoringJob": { "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. ModelDeploymentMonitoring Job resource name. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`" } }, "parameterOrder": [ "modelDeploymentMonitoringJob" ] }, "pause": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the ModelDeploymentMonitoringJob to pause. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Pauses a ModelDeploymentMonitoringJob. If the job is running, the server makes a best effort to cancel the job. Will mark ModelDeploymentMonitoringJob.state to 'PAUSED'.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:pause", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.pause", "path": "v1beta1/{+name}:pause", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1PauseModelDeploymentMonitoringJobRequest" } } }, "resources": { "operations": { "methods": { "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.cancel", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.delete", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "wait": { "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] }, "list": { "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "required": true, "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ] } } } } }, "notebookRuntimes": { "methods": { "generateAccessToken": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:generateAccessToken", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest" }, "path": "v1beta1/{+name}:generateAccessToken", "httpMethod": "POST", "id": "aiplatform.projects.locations.notebookRuntimes.generateAccessToken", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the resource requesting the OAuth2 token. Format: `projects/{project}/locations/{location}/notebookRuntimes/{notebook_runtime}` `projects/{project}/locations/{location}/notebookExecutionJobs/{notebook_execution_job}`", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateAccessTokenResponse" }, "description": "Internal only: Called from Compute Engine instance to obtain EUC for owner Anonymous access: authenticates caller using VM identity JWT. Design doc: go/colab-on-vertex-euc-dd", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a NotebookRuntime.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the NotebookRuntime resource to be deleted. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.notebookRuntimes.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}" }, "stop": { "parameters": { "name": { "description": "Required. The name of the NotebookRuntime resource to be stopped. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Stops a NotebookRuntime.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:stop", "id": "aiplatform.projects.locations.notebookRuntimes.stop", "path": "v1beta1/{+name}:stop", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1StopNotebookRuntimeRequest" } }, "reportEvent": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the NotebookRuntime resource. Format: `projects/{project}/locations/{location}/notebookRuntimes/{notebook_runtime}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ReportRuntimeEventResponse" }, "description": "", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:reportEvent", "path": "v1beta1/{+name}:reportEvent", "httpMethod": "POST", "id": "aiplatform.projects.locations.notebookRuntimes.reportEvent", "request": { "$ref": "GoogleCloudAiplatformV1beta1ReportRuntimeEventRequest" } }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes", "path": "v1beta1/{+parent}/notebookRuntimes", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookRuntimes.list", "parameters": { "pageSize": { "description": "Optional. The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "readMask": { "location": "query", "format": "google-fieldmask", "description": "Optional. Mask specifying which fields to read.", "type": "string" }, "pageToken": { "location": "query", "description": "Optional. The standard list page token. Typically obtained via ListNotebookRuntimesResponse.next_page_token of the previous NotebookService.ListNotebookRuntimes call.", "type": "string" }, "orderBy": { "type": "string", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", "location": "query" }, "filter": { "location": "query", "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookRuntime` supports = and !=. `notebookRuntime` represents the NotebookRuntime ID, i.e. the last segment of the NotebookRuntime's resource name. * `displayName` supports = and != and regex. * `notebookRuntimeTemplate` supports = and !=. `notebookRuntimeTemplate` represents the NotebookRuntimeTemplate ID, i.e. the last segment of the NotebookRuntimeTemplate's resource name. * `healthState` supports = and !=. healthState enum: [HEALTHY, UNHEALTHY, HEALTH_STATE_UNSPECIFIED]. * `runtimeState` supports = and !=. runtimeState enum: [RUNTIME_STATE_UNSPECIFIED, RUNNING, BEING_STARTED, BEING_STOPPED, STOPPED, BEING_UPGRADED, ERROR, INVALID]. * `runtimeUser` supports = and !=. * API version is UI only: `uiState` supports = and !=. uiState enum: [UI_RESOURCE_STATE_UNSPECIFIED, UI_RESOURCE_STATE_BEING_CREATED, UI_RESOURCE_STATE_ACTIVE, UI_RESOURCE_STATE_BEING_DELETED, UI_RESOURCE_STATE_CREATION_FAILED]. * `notebookRuntimeType` supports = and !=. notebookRuntimeType enum: [USER_DEFINED, ONE_CLICK]. * `machineType` supports = and !=. * `acceleratorType` supports = and !=. Some examples: * `notebookRuntime=\"notebookRuntime123\"` * `displayName=\"myDisplayName\"` and `displayName=~\"myDisplayNameRegex\"` * `notebookRuntimeTemplate=\"notebookRuntimeTemplate321\"` * `healthState=HEALTHY` * `runtimeState=RUNNING` * `runtimeUser=\"test@google.com\"` * `uiState=UI_RESOURCE_STATE_BEING_DELETED` * `notebookRuntimeType=USER_DEFINED` * `machineType=e2-standard-4` * `acceleratorType=NVIDIA_TESLA_T4`", "type": "string" }, "parent": { "description": "Required. The resource name of the Location from which to list the NotebookRuntimes. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListNotebookRuntimesResponse" }, "description": "Lists NotebookRuntimes in a Location." }, "upgrade": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:upgrade", "request": { "$ref": "GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeRequest" }, "path": "v1beta1/{+name}:upgrade", "httpMethod": "POST", "id": "aiplatform.projects.locations.notebookRuntimes.upgrade", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the NotebookRuntime resource to be upgrade. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Upgrades a NotebookRuntime.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1NotebookRuntime" }, "description": "Gets a NotebookRuntime.", "parameters": { "name": { "description": "Required. The name of the NotebookRuntime resource. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookRuntimes.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}" }, "start": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Starts a NotebookRuntime.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The name of the NotebookRuntime resource to be started. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1StartNotebookRuntimeRequest" }, "path": "v1beta1/{+name}:start", "httpMethod": "POST", "id": "aiplatform.projects.locations.notebookRuntimes.start", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:start" }, "assign": { "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location to get the NotebookRuntime assignment. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "description": "Assigns a NotebookRuntime to a user for a particular Notebook file. This method will either returns an existing assignment or generates a new one.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes:assign", "request": { "$ref": "GoogleCloudAiplatformV1beta1AssignNotebookRuntimeRequest" }, "id": "aiplatform.projects.locations.notebookRuntimes.assign", "path": "v1beta1/{+parent}/notebookRuntimes:assign", "httpMethod": "POST" } }, "resources": { "operations": { "methods": { "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations", "id": "aiplatform.projects.locations.notebookRuntimes.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.notebookRuntimes.operations.wait", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookRuntimes.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.notebookRuntimes.operations.delete", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." }, "cancel": { "id": "aiplatform.projects.locations.notebookRuntimes.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ] } } } } }, "operations": { "methods": { "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}:cancel" }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "id": "aiplatform.projects.locations.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "wait": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/operations" } } }, "nasJobs": { "methods": { "create": { "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Location to create the NasJob in. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a NasJob", "response": { "$ref": "GoogleCloudAiplatformV1beta1NasJob" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs", "id": "aiplatform.projects.locations.nasJobs.create", "path": "v1beta1/{+parent}/nasJobs", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1NasJob" } }, "list": { "id": "aiplatform.projects.locations.nasJobs.list", "path": "v1beta1/{+parent}/nasJobs", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs", "description": "Lists NasJobs in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListNasJobsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`" }, "parent": { "location": "path", "description": "Required. The resource name of the Location to list the NasJobs from. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token. Typically obtained via ListNasJobsResponse.next_page_token of the previous JobService.ListNasJobs call.", "location": "query" }, "readMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read." }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." } }, "parameterOrder": [ "parent" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.nasJobs.cancel", "request": { "$ref": "GoogleCloudAiplatformV1beta1CancelNasJobRequest" }, "parameters": { "name": { "description": "Required. The name of the NasJob to cancel. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Cancels a NasJob. Starts asynchronous cancellation on the NasJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetNasJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the NasJob is not deleted; instead it becomes a job with a NasJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and NasJob.state is set to `CANCELLED`." }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a NasJob.", "parameters": { "name": { "location": "path", "description": "Required. The name of the NasJob resource to be deleted. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.nasJobs.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.nasJobs.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}", "response": { "$ref": "GoogleCloudAiplatformV1beta1NasJob" }, "description": "Gets a NasJob", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "name": { "description": "Required. The name of the NasJob resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] } }, "resources": { "nasTrialDetails": { "methods": { "list": { "description": "List top NasTrialDetails of a NasJob.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListNasTrialDetailsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "description": "Required. The name of the NasJob resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", "required": true, "type": "string" }, "pageToken": { "description": "The standard list page token. Typically obtained via ListNasTrialDetailsResponse.next_page_token of the previous JobService.ListNasTrialDetails call.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.nasJobs.nasTrialDetails.list", "path": "v1beta1/{+parent}/nasTrialDetails", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}/nasTrialDetails" }, "get": { "description": "Gets a NasTrialDetail.", "response": { "$ref": "GoogleCloudAiplatformV1beta1NasTrialDetail" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The name of the NasTrialDetail resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}/nasTrialDetails/{nas_trial_detail}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+/nasTrialDetails/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.nasJobs.nasTrialDetails.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}/nasTrialDetails/{nasTrialDetailsId}" } } } } }, "evaluationItems": { "methods": { "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationItems", "request": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationItem" }, "path": "v1beta1/{+parent}/evaluationItems", "httpMethod": "POST", "id": "aiplatform.projects.locations.evaluationItems.create", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location to create the Evaluation Item in. Format: `projects/{project}/locations/{location}`" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationItem" }, "description": "Creates an Evaluation Item.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes an Evaluation Item.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationItems/[^/]+$", "required": true, "description": "Required. The name of the EvaluationItem resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}`", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.evaluationItems.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationItems/{evaluationItemsId}" }, "list": { "parameters": { "pageToken": { "type": "string", "location": "query", "description": "Optional. A page token, received from a previous `ListEvaluationItems` call. Provide this to retrieve the subsequent page." }, "orderBy": { "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending.", "type": "string" }, "filter": { "location": "query", "description": "Optional. Filter expression that matches a subset of the EvaluationItems to show. For field names both snake_case and camelCase are supported. For more information about filter syntax, see [AIP-160](https://google.aip.dev/160).", "type": "string" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location from which to list the Evaluation Items. Format: `projects/{project}/locations/{location}`" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The maximum number of Evaluation Items to return." } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListEvaluationItemsResponse" }, "description": "Lists Evaluation Items.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationItems", "path": "v1beta1/{+parent}/evaluationItems", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationItems.list" }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets an Evaluation Item.", "response": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationItem" }, "parameters": { "name": { "location": "path", "description": "Required. The name of the EvaluationItem resource. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationItems/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.evaluationItems.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationItems/{evaluationItemsId}" } }, "resources": { "operations": { "methods": { "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/evaluationItems/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationItems.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationItems/{evaluationItemsId}/operations" }, "get": { "id": "aiplatform.projects.locations.evaluationItems.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationItems/{evaluationItemsId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationItems/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "wait": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationItems/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationItems/{evaluationItemsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.evaluationItems.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/evaluationItems/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.evaluationItems.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationItems/{evaluationItemsId}/operations/{operationsId}" } } } } }, "evaluationSets": { "methods": { "patch": { "response": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationSet" }, "description": "Updates an Evaluation Set.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationSets/[^/]+$", "required": true, "location": "path", "description": "Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`" }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Optional. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask." } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationSet" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.evaluationSets.patch", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationSets/{evaluationSetsId}" }, "list": { "path": "v1beta1/{+parent}/evaluationSets", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationSets.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationSets", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListEvaluationSetsResponse" }, "description": "Lists Evaluation Sets.", "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "Optional. The maximum number of Evaluation Sets to return.", "type": "integer" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location from which to list the Evaluation Sets. Format: `projects/{project}/locations/{location}`" }, "filter": { "description": "Optional. Filter expression that matches a subset of the EvaluationSets to show. For field names both snake_case and camelCase are supported. For more information about filter syntax, see [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" }, "orderBy": { "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending.", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. A page token, received from a previous `ListEvaluationSets` call. Provide this to retrieve the subsequent page." } }, "parameterOrder": [ "parent" ] }, "create": { "id": "aiplatform.projects.locations.evaluationSets.create", "path": "v1beta1/{+parent}/evaluationSets", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationSet" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationSets", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates an Evaluation Set.", "response": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationSet" }, "parameters": { "parent": { "description": "Required. The resource name of the Location to create the Evaluation Set in. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ] }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationSets/{evaluationSetsId}", "id": "aiplatform.projects.locations.evaluationSets.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "Required. The name of the EvaluationSet resource. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationSets/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Gets an Evaluation Set.", "response": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationSet" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationSets/{evaluationSetsId}", "id": "aiplatform.projects.locations.evaluationSets.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationSets/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the EvaluationSet resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`" } }, "parameterOrder": [ "name" ], "description": "Deletes an Evaluation Set.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "operations": { "methods": { "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.evaluationSets.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationSets/{evaluationSetsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/evaluationSets/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ] }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationSets/{evaluationSetsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.evaluationSets.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationSets/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" } }, "get": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationSets/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationSets/{evaluationSetsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.evaluationSets.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationSets/{evaluationSetsId}/operations", "id": "aiplatform.projects.locations.evaluationSets.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationSets/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "pipelineJobs": { "methods": { "create": { "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "pipelineJobId": { "type": "string", "description": "The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.", "location": "query" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a PipelineJob. A PipelineJob will run immediately when created.", "response": { "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs", "id": "aiplatform.projects.locations.pipelineJobs.create", "path": "v1beta1/{+parent}/pipelineJobs", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" } }, "batchDelete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs:batchDelete", "path": "v1beta1/{+parent}/pipelineJobs:batchDelete", "httpMethod": "POST", "id": "aiplatform.projects.locations.pipelineJobs.batchDelete", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest" }, "parameters": { "parent": { "description": "Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Batch deletes PipelineJobs The Operation is atomic. If it fails, none of the PipelineJobs are deleted. If it succeeds, all of the PipelineJobs are deleted." }, "batchCancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Batch cancel PipelineJobs. Firstly the server will check if all the jobs are in non-terminal states, and skip the jobs that are already terminated. If the operation failed, none of the pipeline jobs are cancelled. The server will poll the states of all the pipeline jobs periodically to check the cancellation status. This operation will return an LRO.", "parameters": { "parent": { "location": "path", "description": "Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/pipelineJobs:batchCancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.pipelineJobs.batchCancel", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs:batchCancel" }, "list": { "id": "aiplatform.projects.locations.pipelineJobs.list", "path": "v1beta1/{+parent}/pipelineJobs", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs", "description": "Lists PipelineJobs in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListPipelineJobsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "type": "string", "description": "Lists the PipelineJobs that match the filter expression. The following fields are supported: * `pipeline_name`: Supports `=` and `!=` comparisons. * `display_name`: Supports `=`, `!=` comparisons, and `:` wildcard. * `pipeline_job_user_id`: Supports `=`, `!=` comparisons, and `:` wildcard. for example, can check if pipeline's display_name contains *step* by doing display_name:\\\"*step*\\\" * `state`: Supports `=` and `!=` comparisons. * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `end_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. * `template_uri`: Supports `=`, `!=` comparisons, and `:` wildcard. * `template_metadata.version`: Supports `=`, `!=` comparisons, and `:` wildcard. Filter expressions can be combined together using logical operators (`AND` & `OR`). For example: `pipeline_name=\"test\" AND create_time\u003e\"2020-05-18T13:30:00Z\"`. The syntax to define filter expression is based on https://google.aip.dev/160. Examples: * `create_time\u003e\"2021-05-18T00:00:00Z\" OR update_time\u003e\"2020-05-18T00:00:00Z\"` PipelineJobs created or updated after 2020-05-18 00:00:00 UTC. * `labels.env = \"prod\"` PipelineJobs with label \"env\" set to \"prod\".", "location": "query" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to list the PipelineJobs from. Format: `projects/{project}/locations/{location}`", "location": "path" }, "pageToken": { "location": "query", "description": "The standard list page token. Typically obtained via ListPipelineJobsResponse.next_page_token of the previous PipelineService.ListPipelineJobs call.", "type": "string" }, "orderBy": { "location": "query", "description": "A comma-separated list of fields to order by. The default sort order is in ascending order. Use \"desc\" after a field name for descending. You can have multiple order_by fields provided e.g. \"create_time desc, end_time\", \"end_time, start_time, update_time\" For example, using \"create_time desc, end_time\" will order results by create time in descending order, and if there are multiple jobs having the same create time, order them by the end time in ascending order. if order_by is not specified, it will order by default order is create time in descending order. Supported fields: * `create_time` * `update_time` * `end_time` * `start_time`", "type": "string" }, "readMask": { "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." } }, "parameterOrder": [ "parent" ] }, "delete": { "id": "aiplatform.projects.locations.pipelineJobs.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}", "description": "Deletes a PipelineJob.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the PipelineJob resource to be deleted. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`" } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}:cancel", "id": "aiplatform.projects.locations.pipelineJobs.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1CancelPipelineJobRequest" }, "parameters": { "name": { "location": "path", "description": "Required. The name of the PipelineJob to cancel. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`", "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Cancels a PipelineJob. Starts asynchronous cancellation on the PipelineJob. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use PipelineService.GetPipelineJob or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the PipelineJob is not deleted; instead it becomes a pipeline with a PipelineJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and PipelineJob.state is set to `CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.pipelineJobs.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1PipelineJob" }, "description": "Gets a PipelineJob.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", "required": true, "description": "Required. The name of the PipelineJob resource. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`", "location": "path" } }, "parameterOrder": [ "name" ] } }, "resources": { "operations": { "methods": { "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.pipelineJobs.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:wait" }, "list": { "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", "required": true, "type": "string" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.pipelineJobs.operations.list" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.pipelineJobs.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}" }, "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.pipelineJobs.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:cancel" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.pipelineJobs.operations.get", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." } } } } }, "onlineEvaluators": { "methods": { "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators", "id": "aiplatform.projects.locations.onlineEvaluators.create", "path": "v1beta1/{+parent}/onlineEvaluators", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluator" }, "parameters": { "parent": { "location": "path", "description": "Required. The parent resource where the OnlineEvaluator will be created. Format: projects/{project}/locations/{location}.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates an OnlineEvaluator in the given project and location.", "response": { "$ref": "GoogleLongrunningOperation" } }, "suspend": { "request": { "$ref": "GoogleCloudAiplatformV1beta1SuspendOnlineEvaluatorRequest" }, "path": "v1beta1/{+name}:suspend", "httpMethod": "POST", "id": "aiplatform.projects.locations.onlineEvaluators.suspend", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}:suspend", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Suspends an OnlineEvaluator. When an OnlineEvaluator is suspended, it won't run any evaluations until it is activated again.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the OnlineEvaluator to suspend. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}.", "location": "path" } }, "parameterOrder": [ "name" ] }, "patch": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluator" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.onlineEvaluators.patch", "parameters": { "name": { "description": "Identifier. The resource name of the OnlineEvaluator. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+$", "required": true }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Optional. Field mask is used to control which fields get updated. If the mask is not present, all fields will be updated.", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Updates the fields of an OnlineEvaluator.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators", "id": "aiplatform.projects.locations.onlineEvaluators.list", "path": "v1beta1/{+parent}/onlineEvaluators", "httpMethod": "GET", "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "Optional. The maximum number of OnlineEvaluators to return. The service may return fewer than this value. If unspecified, at most 50 OnlineEvaluators will be returned. The maximum value is 100; values above 100 will be coerced to 100. Based on aip.dev/158.", "type": "integer" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The parent resource of the OnlineEvaluators to list. Format: projects/{project}/locations/{location}.", "location": "path" }, "filter": { "type": "string", "description": "Optional. Standard list filter. Supported fields: * `create_time` * `update_time` * `agent_resource` Example: `create_time\u003e\"2026-01-01T00:00:00-04:00\"` where the timestamp is in RFC 3339 format) Based on aip.dev/160.", "location": "query" }, "orderBy": { "type": "string", "description": "Optional. A comma-separated list of fields to order by. The default sorting order is ascending. Use \"desc\" after a field name for descending. Supported fields: * `create_time` * `update_time` Example: `create_time desc`. Based on aip.dev/132.", "location": "query" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. A token identifying a page of results the server should return. Based on aip.dev/158." } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists the OnlineEvaluators for the given project and location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListOnlineEvaluatorsResponse" } }, "activate": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the OnlineEvaluator to activate. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}." } }, "parameterOrder": [ "name" ], "description": "Activates an OnlineEvaluator.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}:activate", "request": { "$ref": "GoogleCloudAiplatformV1beta1ActivateOnlineEvaluatorRequest" }, "id": "aiplatform.projects.locations.onlineEvaluators.activate", "path": "v1beta1/{+name}:activate", "httpMethod": "POST" }, "delete": { "parameters": { "name": { "description": "Required. The name of the OnlineEvaluator to delete. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes an OnlineEvaluator.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}", "id": "aiplatform.projects.locations.onlineEvaluators.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.onlineEvaluators.get", "parameters": { "name": { "location": "path", "description": "Required. The name of the OnlineEvaluator to retrieve. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}.", "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1OnlineEvaluator" }, "description": "Gets details of an OnlineEvaluator." } }, "resources": { "operations": { "methods": { "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.onlineEvaluators.operations.get", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.onlineEvaluators.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}" }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.onlineEvaluators.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+$", "required": true }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}/operations", "id": "aiplatform.projects.locations.onlineEvaluators.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.onlineEvaluators.operations.wait", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." } } } } }, "featurestores": { "methods": { "testIamPermissions": { "request": { "$ref": "GoogleIamV1TestIamPermissionsRequest" }, "path": "v1beta1/{+resource}:testIamPermissions", "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.testIamPermissions", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:testIamPermissions", "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "resource": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "required": true, "location": "path", "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." } }, "parameterOrder": [ "resource" ] }, "get": { "parameters": { "name": { "location": "path", "description": "Required. The name of the Featurestore resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Gets details of a single Featurestore.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Featurestore" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}", "id": "aiplatform.projects.locations.featurestores.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "setIamPolicy": { "parameters": { "resource": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "required": true, "location": "path", "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." } }, "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleIamV1Policy" }, "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:setIamPolicy", "path": "v1beta1/{+resource}:setIamPolicy", "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.setIamPolicy", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" } }, "patch": { "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.featurestores.patch", "request": { "$ref": "GoogleCloudAiplatformV1beta1Featurestore" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Updates the parameters of a single Featurestore.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "required": true, "type": "string", "description": "Output only. Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", "location": "path" }, "updateMask": { "description": "Field mask is used to specify the fields to be overwritten in the Featurestore resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `online_serving_config.fixed_node_count` * `online_serving_config.scaling` * `online_storage_ttl_days`", "location": "query", "format": "google-fieldmask", "type": "string" } }, "parameterOrder": [ "name" ] }, "delete": { "id": "aiplatform.projects.locations.featurestores.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a single Featurestore. The Featurestore must not contain any EntityTypes or `force` must be set to true for the request to succeed.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the Featurestore to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", "location": "path" }, "force": { "type": "boolean", "location": "query", "description": "If set to true, any EntityTypes and Features for this Featurestore will also be deleted. (Otherwise, the request will only work if the Featurestore has no EntityTypes.)" } }, "parameterOrder": [ "name" ] }, "create": { "description": "Creates a new Featurestore in a given project and location.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location to create Featurestores. Format: `projects/{project}/locations/{location}`" }, "featurestoreId": { "type": "string", "description": "Required. The ID to use for this Featurestore, which will become the final component of the Featurestore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.", "location": "query" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1Featurestore" }, "id": "aiplatform.projects.locations.featurestores.create", "path": "v1beta1/{+parent}/featurestores", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores", "id": "aiplatform.projects.locations.featurestores.list", "path": "v1beta1/{+parent}/featurestores", "httpMethod": "GET", "parameters": { "filter": { "location": "query", "description": "Lists the featurestores that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `online_serving_config.fixed_node_count`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` Featurestores created or updated after 2020-01-01. * `labels.env = \"prod\"` Featurestores with label \"env\" set to \"prod\".", "type": "string" }, "parent": { "description": "Required. The resource name of the Location to list Featurestores. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "pageToken": { "location": "query", "description": "A page token, received from a previous FeaturestoreService.ListFeaturestores call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeaturestores must match the call that provided the page token.", "type": "string" }, "orderBy": { "type": "string", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported Fields: * `create_time` * `update_time` * `online_serving_config.fixed_node_count`", "location": "query" }, "readMask": { "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask", "type": "string" }, "pageSize": { "description": "The maximum number of Featurestores to return. The service may return fewer than this value. If unspecified, at most 100 Featurestores will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [ "parent" ], "description": "Lists Featurestores in a given project and location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListFeaturestoresResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "batchReadFeatureValues": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Batch reads Feature values from a Featurestore. This API enables batch reading Feature values, where each read instance in the batch may read Feature values of entities from one or more EntityTypes. Point-in-time correctness is guaranteed for Feature values of each read instance as of each instance's read timestamp.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "featurestore": { "description": "Required. The resource name of the Featurestore from which to query Feature values. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "required": true } }, "parameterOrder": [ "featurestore" ], "id": "aiplatform.projects.locations.featurestores.batchReadFeatureValues", "path": "v1beta1/{+featurestore}:batchReadFeatureValues", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:batchReadFeatureValues" }, "searchFeatures": { "response": { "$ref": "GoogleCloudAiplatformV1beta1SearchFeaturesResponse" }, "description": "Searches Features matching a query in a given project.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "location": { "location": "path", "description": "Required. The resource name of the Location to search Features. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "pageToken": { "location": "query", "description": "A page token, received from a previous FeaturestoreService.SearchFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.SearchFeatures, except `page_size`, must match the call that provided the page token.", "type": "string" }, "query": { "description": "Query string that is a conjunction of field-restricted queries and/or field-restricted filters. Field-restricted queries and filters can be combined using `AND` to form a conjunction. A field query is in the form FIELD:QUERY. This implicitly checks if QUERY exists as a substring within Feature's FIELD. The QUERY and the FIELD are converted to a sequence of words (i.e. tokens) for comparison. This is done by: * Removing leading/trailing whitespace and tokenizing the search value. Characters that are not one of alphanumeric `[a-zA-Z0-9]`, underscore `_`, or asterisk `*` are treated as delimiters for tokens. `*` is treated as a wildcard that matches characters within a token. * Ignoring case. * Prepending an asterisk to the first and appending an asterisk to the last token in QUERY. A QUERY must be either a singular token or a phrase. A phrase is one or multiple words enclosed in double quotation marks (\"). With phrases, the order of the words is important. Words in the phrase must be matching in order and consecutively. Supported FIELDs for field-restricted queries: * `feature_id` * `description` * `entity_type_id` Examples: * `feature_id: foo` --\u003e Matches a Feature with ID containing the substring `foo` (eg. `foo`, `foofeature`, `barfoo`). * `feature_id: foo*feature` --\u003e Matches a Feature with ID containing the substring `foo*feature` (eg. `foobarfeature`). * `feature_id: foo AND description: bar` --\u003e Matches a Feature with ID containing the substring `foo` and description containing the substring `bar`. Besides field queries, the following exact-match filters are supported. The exact-match filters do not support wildcards. Unlike field-restricted queries, exact-match filters are case-sensitive. * `feature_id`: Supports = comparisons. * `description`: Supports = comparisons. Multi-token filters should be enclosed in quotes. * `entity_type_id`: Supports = comparisons. * `value_type`: Supports = and != comparisons. * `labels`: Supports key-value equality as well as key presence. * `featurestore_id`: Supports = comparisons. Examples: * `description = \"foo bar\"` --\u003e Any Feature with description exactly equal to `foo bar` * `value_type = DOUBLE` --\u003e Features whose type is DOUBLE. * `labels.active = yes AND labels.env = prod` --\u003e Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any Feature which has a label with `env` as the key.", "location": "query", "type": "string" }, "pageSize": { "description": "The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 100 Features will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [ "location" ], "path": "v1beta1/{+location}/featurestores:searchFeatures", "httpMethod": "GET", "id": "aiplatform.projects.locations.featurestores.searchFeatures", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores:searchFeatures" }, "getIamPolicy": { "request": { "$ref": "GoogleIamV1GetIamPolicyRequest" }, "id": "aiplatform.projects.locations.featurestores.getIamPolicy", "path": "v1beta1/{+resource}:getIamPolicy", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:getIamPolicy", "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "response": { "$ref": "GoogleIamV1Policy" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "resource": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "required": true, "location": "path", "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." } }, "parameterOrder": [ "resource" ] } }, "resources": { "entityTypes": { "methods": { "create": { "description": "Creates a new EntityType in a given Featurestore.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "required": true, "description": "Required. The resource name of the Featurestore to create EntityTypes. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", "location": "path" }, "entityTypeId": { "type": "string", "location": "query", "description": "Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a featurestore." } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1EntityType" }, "id": "aiplatform.projects.locations.featurestores.entityTypes.create", "path": "v1beta1/{+parent}/entityTypes", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes" }, "importFeatureValues": { "parameters": { "entityType": { "location": "path", "description": "Required. The resource name of the EntityType grouping the Features for which values are being imported. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "entityType" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Imports Feature values into the Featurestore from a source storage. The progress of the import is tracked by the returned operation. The imported features are guaranteed to be visible to subsequent read operations after the operation is marked as successfully done. If an import operation fails, the Feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same import request again and wait till the new operation returned is marked as successfully done. There are also scenarios where the caller can cause inconsistency. - Source data for import contains multiple distinct Feature values for the same entity ID and timestamp. - Source is modified during an import. This includes adding, updating, or removing source data and/or metadata. Examples of updating metadata include but are not limited to changing storage location, storage class, or retention policy. - Online serving cluster is under-provisioned.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:importFeatureValues", "id": "aiplatform.projects.locations.featurestores.entityTypes.importFeatureValues", "path": "v1beta1/{+entityType}:importFeatureValues", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1ImportFeatureValuesRequest" } }, "list": { "parameters": { "orderBy": { "type": "string", "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `entity_type_id` * `create_time` * `update_time`" }, "pageToken": { "type": "string", "location": "query", "description": "A page token, received from a previous FeaturestoreService.ListEntityTypes call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListEntityTypes must match the call that provided the page token." }, "parent": { "location": "path", "description": "Required. The resource name of the Featurestore to list EntityTypes. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "required": true, "type": "string" }, "filter": { "type": "string", "location": "query", "description": "Lists the EntityTypes that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e EntityTypes having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any EntityType which has a label with 'env' as the key." }, "pageSize": { "location": "query", "format": "int32", "description": "The maximum number of EntityTypes to return. The service may return fewer than this value. If unspecified, at most 1000 EntityTypes will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", "type": "integer" }, "readMask": { "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListEntityTypesResponse" }, "description": "Lists EntityTypes in a given Featurestore.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes", "path": "v1beta1/{+parent}/entityTypes", "httpMethod": "GET", "id": "aiplatform.projects.locations.featurestores.entityTypes.list" }, "testIamPermissions": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:testIamPermissions", "id": "aiplatform.projects.locations.featurestores.entityTypes.testIamPermissions", "path": "v1beta1/{+resource}:testIamPermissions", "httpMethod": "POST", "parameters": { "resource": { "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true }, "permissions": { "location": "query", "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", "repeated": true, "type": "string" } }, "parameterOrder": [ "resource" ], "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "parameters": { "name": { "description": "Required. The name of the EntityType resource. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Gets details of a single EntityType.", "response": { "$ref": "GoogleCloudAiplatformV1beta1EntityType" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}", "id": "aiplatform.projects.locations.featurestores.entityTypes.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a single EntityType. The EntityType must not have any Features or `force` must be set to true for the request to succeed.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "description": "Required. The name of the EntityType to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`", "location": "path" }, "force": { "type": "boolean", "location": "query", "description": "If set to true, any Features for this EntityType will also be deleted. (Otherwise, the request will only work if the EntityType has no Features.)" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featurestores.entityTypes.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}" }, "writeFeatureValues": { "path": "v1beta1/{+entityType}:writeFeatureValues", "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.entityTypes.writeFeatureValues", "request": { "$ref": "GoogleCloudAiplatformV1beta1WriteFeatureValuesRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:writeFeatureValues", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1WriteFeatureValuesResponse" }, "description": "Writes Feature values of one or more entities of an EntityType. The Feature values are merged into existing entities if any. The Feature values to be written must have timestamp within the online storage retention.", "parameters": { "entityType": { "location": "path", "description": "Required. The resource name of the EntityType for the entities being written. Value format: `projects/{project}/locations/{location}/featurestores/ {featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`.", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "entityType" ] }, "getIamPolicy": { "parameters": { "options.requestedPolicyVersion": { "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "location": "query", "format": "int32", "type": "integer" }, "resource": { "location": "path", "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true } }, "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "response": { "$ref": "GoogleIamV1Policy" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:getIamPolicy", "id": "aiplatform.projects.locations.featurestores.entityTypes.getIamPolicy", "path": "v1beta1/{+resource}:getIamPolicy", "httpMethod": "POST" }, "streamingReadFeatureValues": { "description": "Reads Feature values for multiple entities. Depending on their size, data for different entities may be broken up across multiple responses.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "entityType": { "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the entities' type. Value format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`." } }, "parameterOrder": [ "entityType" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1StreamingReadFeatureValuesRequest" }, "id": "aiplatform.projects.locations.featurestores.entityTypes.streamingReadFeatureValues", "path": "v1beta1/{+entityType}:streamingReadFeatureValues", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:streamingReadFeatureValues" }, "deleteFeatureValues": { "request": { "$ref": "GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequest" }, "path": "v1beta1/{+entityType}:deleteFeatureValues", "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.entityTypes.deleteFeatureValues", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:deleteFeatureValues", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Delete Feature values from Featurestore. The progress of the deletion is tracked by the returned operation. The deleted feature values are guaranteed to be invisible to subsequent read operations after the operation is marked as successfully done. If a delete feature values operation fails, the feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same delete request again and wait till the new operation returned is marked as successfully done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "entityType": { "description": "Required. The resource name of the EntityType grouping the Features for which values are being deleted from. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true } }, "parameterOrder": [ "entityType" ] }, "setIamPolicy": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleIamV1Policy" }, "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "parameters": { "resource": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "location": "path", "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." } }, "parameterOrder": [ "resource" ], "path": "v1beta1/{+resource}:setIamPolicy", "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.entityTypes.setIamPolicy", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:setIamPolicy" }, "readFeatureValues": { "parameters": { "entityType": { "description": "Required. The resource name of the EntityType for the entity being read. Value format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "entityType" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesResponse" }, "description": "Reads Feature values of a specific entity of an EntityType. For reading feature values of multiple entities of an EntityType, please use StreamingReadFeatureValues.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:readFeatureValues", "request": { "$ref": "GoogleCloudAiplatformV1beta1ReadFeatureValuesRequest" }, "path": "v1beta1/{+entityType}:readFeatureValues", "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.entityTypes.readFeatureValues" }, "patch": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1EntityType" }, "id": "aiplatform.projects.locations.featurestores.entityTypes.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "parameters": { "name": { "location": "path", "description": "Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Field mask is used to specify the fields to be overwritten in the EntityType resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `monitoring_config.snapshot_analysis.disabled` * `monitoring_config.snapshot_analysis.monitoring_interval_days` * `monitoring_config.snapshot_analysis.staleness_days` * `monitoring_config.import_features_analysis.state` * `monitoring_config.import_features_analysis.anomaly_detection_baseline` * `monitoring_config.numerical_threshold_config.value` * `monitoring_config.categorical_threshold_config.value` * `offline_storage_ttl_days`" } }, "parameterOrder": [ "name" ], "description": "Updates the parameters of a single EntityType.", "response": { "$ref": "GoogleCloudAiplatformV1beta1EntityType" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "exportFeatureValues": { "id": "aiplatform.projects.locations.featurestores.entityTypes.exportFeatureValues", "path": "v1beta1/{+entityType}:exportFeatureValues", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1ExportFeatureValuesRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:exportFeatureValues", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Exports Feature values from all the entities of a target EntityType.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "entityType": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "description": "Required. The resource name of the EntityType from which to export Feature values. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`", "location": "path" } }, "parameterOrder": [ "entityType" ] } }, "resources": { "operations": { "methods": { "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:cancel" }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.delete", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." }, "get": { "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:wait" }, "list": { "parameters": { "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.list" } } }, "features": { "methods": { "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features", "path": "v1beta1/{+parent}/features", "httpMethod": "GET", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.list", "parameters": { "orderBy": { "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `feature_id` * `value_type` (Not supported for FeatureRegistry Feature) * `create_time` * `update_time`", "type": "string" }, "pageToken": { "location": "query", "description": "A page token, received from a previous FeaturestoreService.ListFeatures call or FeatureRegistryService.ListFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeatures or FeatureRegistryService.ListFeatures must match the call that provided the page token.", "type": "string" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the Location to list Features. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`" }, "filter": { "type": "string", "location": "query", "description": "Lists the Features that match the filter expression. The following filters are supported: * `value_type`: Supports = and != comparisons. * `create_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `update_time`: Supports =, !=, \u003c, \u003e, \u003e=, and \u003c= comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `value_type = DOUBLE` --\u003e Features whose type is DOUBLE. * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any Feature which has a label with 'env' as the key." }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 1000 Features will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000." }, "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask" }, "latestStatsCount": { "location": "query", "format": "int32", "description": "Only applicable for Vertex AI Feature Store (Legacy). If set, return the most recent ListFeaturesRequest.latest_stats_count of stats for each Feature in response. Valid value is [0, 10]. If number of stats exists \u003c ListFeaturesRequest.latest_stats_count, return all existing stats.", "type": "integer" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListFeaturesResponse" }, "description": "Lists Features in a given EntityType." }, "patch": { "id": "aiplatform.projects.locations.featurestores.entityTypes.features.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1beta1Feature" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates the parameters of a single Feature.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Feature" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type." }, "updateMask": { "type": "string", "description": "Field mask is used to specify the fields to be overwritten in the Features resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `disable_monitoring` (Not supported for FeatureRegistryService Feature) * `point_of_contact` (Not supported for FeaturestoreService FeatureStore)", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ] }, "create": { "request": { "$ref": "GoogleCloudAiplatformV1beta1Feature" }, "path": "v1beta1/{+parent}/features", "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.create", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates a new Feature in a given EntityType.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`" }, "featureId": { "type": "string", "description": "Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.", "location": "query" } }, "parameterOrder": [ "parent" ] }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Feature resource. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`" }, "featureStatsAndAnomalySpec.latestStatsCount": { "type": "integer", "description": "Optional. If set, returns the most recent count of stats. Valid value is [0, 100]. If stats_time_range is set, return most recent count of stats within the stats_time_range.", "location": "query", "format": "int32" }, "featureStatsAndAnomalySpec.statsTimeRange.startTime": { "type": "string", "location": "query", "format": "google-datetime", "description": "Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start." }, "featureStatsAndAnomalySpec.statsTimeRange.endTime": { "description": "Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end.", "location": "query", "format": "google-datetime", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Gets details of a single Feature.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Feature" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "batchCreate": { "id": "aiplatform.projects.locations.featurestores.entityTypes.features.batchCreate", "path": "v1beta1/{+parent}/features:batchCreate", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features:batchCreate", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a batch of Features in a given EntityType.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "description": "Required. The resource name of the EntityType/FeatureGroup to create the batch of Features under. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "location": "path" } }, "parameterOrder": [ "parent" ] }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a single Feature.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The name of the Features to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] } }, "resources": { "operations": { "methods": { "wait": { "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ] }, "list": { "parameters": { "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.delete", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.get", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." } } } } } } }, "operations": { "methods": { "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.featurestores.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}" }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.featurestores.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}" }, "cancel": { "id": "aiplatform.projects.locations.featurestores.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "list": { "id": "aiplatform.projects.locations.featurestores.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" } }, "parameterOrder": [ "name" ] }, "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}:wait" } } } } }, "evaluationTasks": { "resources": { "operations": { "methods": { "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationTasks.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationTasks/{evaluationTasksId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationTasks/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationTasks/[^/]+$", "required": true, "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationTasks.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationTasks/{evaluationTasksId}/operations" }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationTasks/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.evaluationTasks.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationTasks/{evaluationTasksId}/operations/{operationsId}" }, "wait": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/evaluationTasks/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationTasks/{evaluationTasksId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.evaluationTasks.operations.wait" } } } } }, "metadataStores": { "methods": { "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}", "id": "aiplatform.projects.locations.metadataStores.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the MetadataStore to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Retrieves a specific MetadataStore.", "response": { "$ref": "GoogleCloudAiplatformV1beta1MetadataStore" } }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores", "path": "v1beta1/{+parent}/metadataStores", "httpMethod": "GET", "id": "aiplatform.projects.locations.metadataStores.list", "parameters": { "parent": { "description": "Required. The Location whose MetadataStores should be listed. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The maximum number of Metadata Stores to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100.", "type": "integer" }, "pageToken": { "type": "string", "description": "A page token, received from a previous MetadataService.ListMetadataStores call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)", "location": "query" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListMetadataStoresResponse" }, "description": "Lists MetadataStores for a Location." }, "delete": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a single MetadataStore and all its child resources (Artifacts, Executions, and Contexts).", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The resource name of the MetadataStore to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "type": "string" }, "force": { "description": "Deprecated: Field is no longer supported.", "location": "query", "type": "boolean", "deprecated": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.metadataStores.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}" }, "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores", "request": { "$ref": "GoogleCloudAiplatformV1beta1MetadataStore" }, "path": "v1beta1/{+parent}/metadataStores", "httpMethod": "POST", "id": "aiplatform.projects.locations.metadataStores.create", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Location where the MetadataStore should be created. Format: `projects/{project}/locations/{location}/`", "location": "path" }, "metadataStoreId": { "location": "query", "description": "The {metadatastore} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataStores in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataStore.)", "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Initializes a MetadataStore, including allocation of resources.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "artifacts": { "methods": { "create": { "request": { "$ref": "GoogleCloudAiplatformV1beta1Artifact" }, "path": "v1beta1/{+parent}/artifacts", "httpMethod": "POST", "id": "aiplatform.projects.locations.metadataStores.artifacts.create", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts", "response": { "$ref": "GoogleCloudAiplatformV1beta1Artifact" }, "description": "Creates an Artifact associated with a MetadataStore.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "description": "Required. The resource name of the MetadataStore where the Artifact should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "location": "path" }, "artifactId": { "description": "The {artifact} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}` If not provided, the Artifact's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Artifacts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Artifact.)", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ] }, "patch": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1Artifact" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.metadataStores.artifacts.patch", "parameters": { "name": { "location": "path", "description": "Output only. The resource name of the Artifact.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", "required": true }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Optional. A FieldMask indicating which fields should be updated.", "type": "string" }, "allowMissing": { "type": "boolean", "description": "If set to true, and the Artifact is not found, a new Artifact is created.", "location": "query" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Artifact" }, "description": "Updates a stored Artifact.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListArtifactsResponse" }, "description": "Lists Artifacts in the MetadataStore.", "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The maximum number of Artifacts to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100." }, "filter": { "type": "string", "description": "Filter specifying the boolean condition for the Artifacts to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. The supported set of filters include the following: * **Attribute filtering**: For example: `display_name = \"test\"`. Supported fields include: `name`, `display_name`, `uri`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"` * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` * **Context based filtering**: To filter Artifacts based on the contexts to which they belong, use the function operator with the full resource name `in_context()`. For example: `in_context(\"projects//locations//metadataStores//contexts/\")` Each of the above supported filter types can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`.", "location": "query" }, "parent": { "description": "Required. The MetadataStore whose Artifacts should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "type": "string" }, "pageToken": { "type": "string", "description": "A page token, received from a previous MetadataService.ListArtifacts call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)", "location": "query" }, "orderBy": { "location": "query", "description": "How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a \" desc\" suffix; for example: \"foo desc, bar\". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details.", "type": "string" } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/artifacts", "httpMethod": "GET", "id": "aiplatform.projects.locations.metadataStores.artifacts.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts" }, "purge": { "parameters": { "parent": { "location": "path", "description": "Required. The metadata store to purge Artifacts from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Purges Artifacts.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts:purge", "path": "v1beta1/{+parent}/artifacts:purge", "httpMethod": "POST", "id": "aiplatform.projects.locations.metadataStores.artifacts.purge", "request": { "$ref": "GoogleCloudAiplatformV1beta1PurgeArtifactsRequest" } }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.metadataStores.artifacts.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes an Artifact.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The resource name of the Artifact to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", "required": true, "type": "string" }, "etag": { "type": "string", "description": "Optional. The etag of the Artifact to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION.", "location": "query" } }, "parameterOrder": [ "name" ] }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}", "id": "aiplatform.projects.locations.metadataStores.artifacts.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "description": "Required. The resource name of the Artifact to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Retrieves a specific Artifact.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Artifact" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "queryArtifactLineageSubgraph": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}:queryArtifactLineageSubgraph", "id": "aiplatform.projects.locations.metadataStores.artifacts.queryArtifactLineageSubgraph", "path": "v1beta1/{+artifact}:queryArtifactLineageSubgraph", "httpMethod": "GET", "parameters": { "artifact": { "location": "path", "description": "Required. The resource name of the Artifact whose Lineage needs to be retrieved as a LineageSubgraph. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}` The request may error with FAILED_PRECONDITION if the number of Artifacts, the number of Executions, or the number of Events that would be returned for the Context exceeds 1000.", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", "required": true, "type": "string" }, "maxHops": { "type": "integer", "description": "Specifies the size of the lineage graph in terms of number of hops from the specified artifact. Negative Value: INVALID_ARGUMENT error is returned 0: Only input artifact is returned. No value: Transitive closure is performed to return the complete graph.", "location": "query", "format": "int32" }, "filter": { "type": "string", "location": "query", "description": "Filter specifying the boolean condition for the Artifacts to satisfy in order to be part of the Lineage Subgraph. The syntax to define filter query is based on https://google.aip.dev/160. The supported set of filters include the following: * **Attribute filtering**: For example: `display_name = \"test\"` Supported fields include: `name`, `display_name`, `uri`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"` * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` Each of the above supported filter types can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`." } }, "parameterOrder": [ "artifact" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Retrieves lineage of an Artifact represented through Artifacts and Executions connected by Event edges and returned as a LineageSubgraph.", "response": { "$ref": "GoogleCloudAiplatformV1beta1LineageSubgraph" } } }, "resources": { "operations": { "methods": { "get": { "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.get" }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "cancel": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.cancel" }, "list": { "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations", "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "wait": { "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" } } } } }, "operations": { "methods": { "wait": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.metadataStores.operations.wait" }, "list": { "id": "aiplatform.projects.locations.metadataStores.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "parameterOrder": [ "name" ] }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.metadataStores.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}:cancel" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.metadataStores.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] } } }, "metadataSchemas": { "methods": { "create": { "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.create", "path": "v1beta1/{+parent}/metadataSchemas", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1MetadataSchema" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a MetadataSchema.", "response": { "$ref": "GoogleCloudAiplatformV1beta1MetadataSchema" }, "parameters": { "parent": { "description": "Required. The resource name of the MetadataStore where the MetadataSchema should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "type": "string" }, "metadataSchemaId": { "type": "string", "location": "query", "description": "The {metadata_schema} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataSchemas in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataSchema.)" } }, "parameterOrder": [ "parent" ] }, "list": { "parameters": { "parent": { "description": "Required. The MetadataStore whose MetadataSchemas should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "type": "string" }, "filter": { "description": "A query to filter available MetadataSchemas for matching results.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "description": "The maximum number of MetadataSchemas to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100.", "location": "query", "format": "int32" }, "pageToken": { "location": "query", "description": "A page token, received from a previous MetadataService.ListMetadataSchemas call. Provide this to retrieve the next page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)", "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists MetadataSchemas.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListMetadataSchemasResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas", "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.list", "path": "v1beta1/{+parent}/metadataSchemas", "httpMethod": "GET" }, "get": { "parameters": { "name": { "description": "Required. The resource name of the MetadataSchema to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/metadataSchemas/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Retrieves a specific MetadataSchema.", "response": { "$ref": "GoogleCloudAiplatformV1beta1MetadataSchema" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas/{metadataSchemasId}", "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.get", "path": "v1beta1/{+name}", "httpMethod": "GET" } } }, "contexts": { "methods": { "patch": { "parameters": { "allowMissing": { "location": "query", "description": "If set to true, and the Context is not found, a new Context is created.", "type": "boolean" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "required": true, "location": "path", "description": "Immutable. The resource name of the Context." }, "updateMask": { "description": "Optional. A FieldMask indicating which fields should be updated.", "location": "query", "format": "google-fieldmask", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Context" }, "description": "Updates a stored Context.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.metadataStores.contexts.patch", "request": { "$ref": "GoogleCloudAiplatformV1beta1Context" } }, "addContextChildren": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:addContextChildren", "request": { "$ref": "GoogleCloudAiplatformV1beta1AddContextChildrenRequest" }, "path": "v1beta1/{+context}:addContextChildren", "httpMethod": "POST", "id": "aiplatform.projects.locations.metadataStores.contexts.addContextChildren", "parameters": { "context": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the parent Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", "location": "path" } }, "parameterOrder": [ "context" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1AddContextChildrenResponse" }, "description": "Adds a set of Contexts as children to a parent Context. If any of the child Contexts have already been added to the parent Context, they are simply skipped. If this call would create a cycle or cause any Context to have more than 10 parents, the request will fail with an INVALID_ARGUMENT error.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}", "id": "aiplatform.projects.locations.metadataStores.contexts.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "description": "Required. The resource name of the Context to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Retrieves a specific Context.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Context" } }, "removeContextChildren": { "parameters": { "context": { "description": "Required. The resource name of the parent Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "required": true } }, "parameterOrder": [ "context" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Remove a set of children contexts from a parent Context. If any of the child Contexts were NOT added to the parent Context, they are simply skipped.", "response": { "$ref": "GoogleCloudAiplatformV1beta1RemoveContextChildrenResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:removeContextChildren", "id": "aiplatform.projects.locations.metadataStores.contexts.removeContextChildren", "path": "v1beta1/{+context}:removeContextChildren", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1RemoveContextChildrenRequest" } }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists Contexts on the MetadataStore.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListContextsResponse" }, "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "The maximum number of Contexts to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100.", "type": "integer" }, "pageToken": { "type": "string", "location": "query", "description": "A page token, received from a previous MetadataService.ListContexts call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)" }, "orderBy": { "location": "query", "description": "How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a \" desc\" suffix; for example: \"foo desc, bar\". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details.", "type": "string" }, "filter": { "type": "string", "description": "Filter specifying the boolean condition for the Contexts to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. Following are the supported set of filters: * **Attribute filtering**: For example: `display_name = \"test\"`. Supported fields include: `name`, `display_name`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"`. * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0`. In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` * **Parent Child filtering**: To filter Contexts based on parent-child relationship use the HAS operator as follows: ``` parent_contexts: \"projects//locations//metadataStores//contexts/\" child_contexts: \"projects//locations//metadataStores//contexts/\" ``` Each of the above supported filters can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`.", "location": "query" }, "parent": { "location": "path", "description": "Required. The MetadataStore whose Contexts should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.metadataStores.contexts.list", "path": "v1beta1/{+parent}/contexts", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts" }, "purge": { "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The metadata store to purge Contexts from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" } }, "parameterOrder": [ "parent" ], "description": "Purges Contexts.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts:purge", "request": { "$ref": "GoogleCloudAiplatformV1beta1PurgeContextsRequest" }, "id": "aiplatform.projects.locations.metadataStores.contexts.purge", "path": "v1beta1/{+parent}/contexts:purge", "httpMethod": "POST" }, "create": { "path": "v1beta1/{+parent}/contexts", "httpMethod": "POST", "id": "aiplatform.projects.locations.metadataStores.contexts.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1Context" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Context" }, "description": "Creates a Context associated with a MetadataStore.", "parameters": { "contextId": { "type": "string", "description": "The {context} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`. If not provided, the Context's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Contexts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Context.)", "location": "query" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the MetadataStore where the Context should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" } }, "parameterOrder": [ "parent" ] }, "addContextArtifactsAndExecutions": { "parameters": { "context": { "location": "path", "description": "Required. The resource name of the Context that the Artifacts and Executions belong to. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "required": true } }, "parameterOrder": [ "context" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsResponse" }, "description": "Adds a set of Artifacts and Executions to a Context. If any of the Artifacts or Executions have already been added to a Context, they are simply skipped.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:addContextArtifactsAndExecutions", "path": "v1beta1/{+context}:addContextArtifactsAndExecutions", "httpMethod": "POST", "id": "aiplatform.projects.locations.metadataStores.contexts.addContextArtifactsAndExecutions", "request": { "$ref": "GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsRequest" } }, "delete": { "id": "aiplatform.projects.locations.metadataStores.contexts.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}", "description": "Deletes a stored Context.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "etag": { "type": "string", "description": "Optional. The etag of the Context to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION.", "location": "query" }, "name": { "description": "Required. The resource name of the Context to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "required": true, "type": "string" }, "force": { "description": "The force deletion semantics is still undefined. Users should not use this field.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ] }, "queryContextLineageSubgraph": { "path": "v1beta1/{+context}:queryContextLineageSubgraph", "httpMethod": "GET", "id": "aiplatform.projects.locations.metadataStores.contexts.queryContextLineageSubgraph", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:queryContextLineageSubgraph", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1LineageSubgraph" }, "description": "Retrieves Artifacts and Executions within the specified Context, connected by Event edges and returned as a LineageSubgraph.", "parameters": { "context": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Context whose Artifacts and Executions should be retrieved as a LineageSubgraph. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}` The request may error with FAILED_PRECONDITION if the number of Artifacts, the number of Executions, or the number of Events that would be returned for the Context exceeds 1000." } }, "parameterOrder": [ "context" ] } }, "resources": { "operations": { "methods": { "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations", "id": "aiplatform.projects.locations.metadataStores.contexts.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.metadataStores.contexts.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" } }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.metadataStores.contexts.operations.get", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." }, "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.contexts.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:cancel" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.contexts.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}" } } } } }, "executions": { "methods": { "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions", "id": "aiplatform.projects.locations.metadataStores.executions.create", "path": "v1beta1/{+parent}/executions", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1Execution" }, "parameters": { "executionId": { "description": "The {execution} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}` If not provided, the Execution's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Executions in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Execution.)", "location": "query", "type": "string" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the MetadataStore where the Execution should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates an Execution associated with a MetadataStore.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Execution" } }, "list": { "description": "Lists Executions in the MetadataStore.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListExecutionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "type": "integer", "description": "The maximum number of Executions to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100.", "location": "query", "format": "int32" }, "filter": { "type": "string", "location": "query", "description": "Filter specifying the boolean condition for the Executions to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. Following are the supported set of filters: * **Attribute filtering**: For example: `display_name = \"test\"`. Supported fields include: `name`, `display_name`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = \"2020-11-19T11:30:00-04:00\"`. * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..` For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata.\"field:1\".number_value = 10.0` * **Context based filtering**: To filter Executions based on the contexts to which they belong use the function operator with the full resource name: `in_context()`. For example: `in_context(\"projects//locations//metadataStores//contexts/\")` Each of the above supported filters can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = \"test\" AND metadata.field1.bool_value = true`." }, "parent": { "description": "Required. The MetadataStore whose Executions should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true }, "pageToken": { "location": "query", "description": "A page token, received from a previous MetadataService.ListExecutions call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with an INVALID_ARGUMENT error.)", "type": "string" }, "orderBy": { "type": "string", "description": "How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a \" desc\" suffix; for example: \"foo desc, bar\". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details.", "location": "query" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.metadataStores.executions.list", "path": "v1beta1/{+parent}/executions", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions" }, "purge": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Purges Executions.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "description": "Required. The metadata store to purge Executions from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "location": "path" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.metadataStores.executions.purge", "path": "v1beta1/{+parent}/executions:purge", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1PurgeExecutionsRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions:purge" }, "patch": { "parameters": { "name": { "description": "Output only. The resource name of the Execution.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", "required": true }, "updateMask": { "description": "Optional. A FieldMask indicating which fields should be updated.", "location": "query", "format": "google-fieldmask", "type": "string" }, "allowMissing": { "location": "query", "description": "If set to true, and the Execution is not found, a new Execution is created.", "type": "boolean" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Execution" }, "description": "Updates a stored Execution.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.metadataStores.executions.patch", "request": { "$ref": "GoogleCloudAiplatformV1beta1Execution" } }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.metadataStores.executions.delete", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Execution to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`", "location": "path" }, "etag": { "type": "string", "location": "query", "description": "Optional. The etag of the Execution to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes an Execution." }, "addExecutionEvents": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1AddExecutionEventsResponse" }, "description": "Adds Events to the specified Execution. An Event indicates whether an Artifact was used as an input or output for an Execution. If an Event already exists between the Execution and the Artifact, the Event is skipped.", "parameters": { "execution": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", "required": true, "description": "Required. The resource name of the Execution that the Events connect Artifacts with. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`", "location": "path" } }, "parameterOrder": [ "execution" ], "path": "v1beta1/{+execution}:addExecutionEvents", "httpMethod": "POST", "id": "aiplatform.projects.locations.metadataStores.executions.addExecutionEvents", "request": { "$ref": "GoogleCloudAiplatformV1beta1AddExecutionEventsRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}:addExecutionEvents" }, "queryExecutionInputsAndOutputs": { "path": "v1beta1/{+execution}:queryExecutionInputsAndOutputs", "httpMethod": "GET", "id": "aiplatform.projects.locations.metadataStores.executions.queryExecutionInputsAndOutputs", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}:queryExecutionInputsAndOutputs", "response": { "$ref": "GoogleCloudAiplatformV1beta1LineageSubgraph" }, "description": "Obtains the set of input and output Artifacts for this Execution, in the form of LineageSubgraph that also contains the Execution and connecting Events.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "execution": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the Execution whose input and output Artifacts should be retrieved as a LineageSubgraph. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`" } }, "parameterOrder": [ "execution" ] }, "get": { "parameters": { "name": { "location": "path", "description": "Required. The resource name of the Execution to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Retrieves a specific Execution.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Execution" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", "id": "aiplatform.projects.locations.metadataStores.executions.get", "path": "v1beta1/{+name}", "httpMethod": "GET" } }, "resources": { "operations": { "methods": { "cancel": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.metadataStores.executions.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.metadataStores.executions.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}" }, "get": { "id": "aiplatform.projects.locations.metadataStores.executions.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ] }, "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.executions.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:wait" }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.executions.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations" } } } } } } }, "exampleStores": { "methods": { "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.exampleStores.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ExampleStore" }, "description": "Get an ExampleStore.", "parameters": { "name": { "description": "Required. The resource name of the ExampleStore. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "searchExamples": { "response": { "$ref": "GoogleCloudAiplatformV1beta1SearchExamplesResponse" }, "description": "Search for similar Examples for given selection criteria.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "exampleStore": { "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the ExampleStore resource that examples are retrieved from. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}`", "location": "path" } }, "parameterOrder": [ "exampleStore" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1SearchExamplesRequest" }, "path": "v1beta1/{+exampleStore}:searchExamples", "httpMethod": "POST", "id": "aiplatform.projects.locations.exampleStores.searchExamples", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}:searchExamples" }, "patch": { "parameters": { "name": { "location": "path", "description": "Identifier. The resource name of the ExampleStore. This is a unique identifier. Format: projects/{project}/locations/{location}/exampleStores/{example_store}", "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+$", "required": true, "type": "string" }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Optional. Mask specifying which fields to update. Supported fields: * `display_name` * `description`", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Update an ExampleStore.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.exampleStores.patch", "request": { "$ref": "GoogleCloudAiplatformV1beta1ExampleStore" } }, "upsertExamples": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Create or update Examples in the Example Store.", "response": { "$ref": "GoogleCloudAiplatformV1beta1UpsertExamplesResponse" }, "parameters": { "exampleStore": { "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the ExampleStore resource that examples are added to or updated in. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}`" } }, "parameterOrder": [ "exampleStore" ], "id": "aiplatform.projects.locations.exampleStores.upsertExamples", "path": "v1beta1/{+exampleStore}:upsertExamples", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1UpsertExamplesRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}:upsertExamples" }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}", "id": "aiplatform.projects.locations.exampleStores.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+$", "required": true, "description": "Required. The resource name of the ExampleStore to be deleted. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}`", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Delete an ExampleStore.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "response": { "$ref": "GoogleCloudAiplatformV1beta1ListExampleStoresResponse" }, "description": "List ExampleStores in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" }, "parent": { "description": "Required. The resource name of the Location to list the ExampleStores from. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "pageToken": { "type": "string", "description": "Optional. The standard list page token.", "location": "query" }, "pageSize": { "description": "Optional. The standard list page size.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/exampleStores", "httpMethod": "GET", "id": "aiplatform.projects.locations.exampleStores.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores" }, "removeExamples": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}:removeExamples", "path": "v1beta1/{+exampleStore}:removeExamples", "httpMethod": "POST", "id": "aiplatform.projects.locations.exampleStores.removeExamples", "request": { "$ref": "GoogleCloudAiplatformV1beta1RemoveExamplesRequest" }, "parameters": { "exampleStore": { "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the ExampleStore resource that the examples should be removed from. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}`", "location": "path" } }, "parameterOrder": [ "exampleStore" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1RemoveExamplesResponse" }, "description": "Remove Examples from the Example Store." }, "fetchExamples": { "request": { "$ref": "GoogleCloudAiplatformV1beta1FetchExamplesRequest" }, "path": "v1beta1/{+exampleStore}:fetchExamples", "httpMethod": "POST", "id": "aiplatform.projects.locations.exampleStores.fetchExamples", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}:fetchExamples", "response": { "$ref": "GoogleCloudAiplatformV1beta1FetchExamplesResponse" }, "description": "Get Examples from the Example Store.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "exampleStore": { "location": "path", "description": "Required. The name of the ExampleStore resource that the examples should be fetched from. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}`", "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "exampleStore" ] }, "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores:create", "id": "aiplatform.projects.locations.exampleStores.create", "path": "v1beta1/{+parent}/exampleStores:create", "httpMethod": "POST", "parameters": { "exampleStore.displayName": { "type": "string", "description": "Required. Display name of the ExampleStore.", "location": "query" }, "exampleStore.exampleStoreConfig.vertexEmbeddingModel": { "type": "string", "description": "Required. The embedding model to be used for vector embedding. Immutable. Supported models: * \"text-embedding-005\" * \"text-multilingual-embedding-002\"", "location": "query" }, "exampleStore.createTime": { "type": "string", "location": "query", "format": "google-datetime", "description": "Output only. Timestamp when this ExampleStore was created." }, "exampleStore.updateTime": { "type": "string", "description": "Output only. Timestamp when this ExampleStore was most recently updated.", "location": "query", "format": "google-datetime" }, "exampleStore.description": { "description": "Optional. Description of the ExampleStore.", "location": "query", "type": "string" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location to create the ExampleStore in. Format: `projects/{project}/locations/{location}`" }, "exampleStore.name": { "type": "string", "location": "query", "description": "Identifier. The resource name of the ExampleStore. This is a unique identifier. Format: projects/{project}/locations/{location}/exampleStores/{example_store}" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Create an ExampleStore.", "response": { "$ref": "GoogleLongrunningOperation" } } }, "resources": { "operations": { "methods": { "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.exampleStores.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}/operations/{operationsId}" }, "delete": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}/operations/{operationsId}", "id": "aiplatform.projects.locations.exampleStores.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.exampleStores.operations.cancel", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." }, "list": { "id": "aiplatform.projects.locations.exampleStores.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+$", "required": true }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ] }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.exampleStores.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/exampleStores/{exampleStoresId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/exampleStores/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ] } } } } }, "schedules": { "methods": { "resume": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Resumes a paused Schedule to start scheduling new runs. Will mark Schedule.state to 'ACTIVE'. Only paused Schedule can be resumed. When the Schedule is resumed, new runs will be scheduled starting from the next execution time after the current time based on the time_specification in the Schedule. If Schedule.catch_up is set up true, all missed runs will be scheduled for backfill first.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The name of the Schedule resource to be resumed. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1ResumeScheduleRequest" }, "path": "v1beta1/{+name}:resume", "httpMethod": "POST", "id": "aiplatform.projects.locations.schedules.resume", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}:resume" }, "delete": { "description": "Deletes a Schedule.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The name of the Schedule resource to be deleted. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.schedules.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}" }, "get": { "description": "Gets a Schedule.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Schedule" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Schedule resource. Format: `projects/{project}/locations/{location}/schedules/{schedule}`" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.schedules.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}" }, "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Schedule" }, "description": "Creates a Schedule.", "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location to create the Schedule in. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/schedules", "httpMethod": "POST", "id": "aiplatform.projects.locations.schedules.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1Schedule" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules" }, "pause": { "description": "Pauses a Schedule. Will mark Schedule.state to 'PAUSED'. If the schedule is paused, no new runs will be created. Already created runs will NOT be paused or canceled.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The name of the Schedule resource to be paused. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1PauseScheduleRequest" }, "id": "aiplatform.projects.locations.schedules.pause", "path": "v1beta1/{+name}:pause", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}:pause" }, "list": { "path": "v1beta1/{+parent}/schedules", "httpMethod": "GET", "id": "aiplatform.projects.locations.schedules.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListSchedulesResponse" }, "description": "Lists Schedules in a Location.", "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location to list the Schedules from. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "filter": { "location": "query", "description": "Lists the Schedules that match the filter expression. The following fields are supported: * `display_name`: Supports `=`, `!=` comparisons, and `:` wildcard. * `state`: Supports `=` and `!=` comparisons. * `request`: Supports existence of the check. (e.g. `create_pipeline_job_request:*` --\u003e Schedule has create_pipeline_job_request). * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `start_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `end_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, `\u003e=` comparisons and `:*` existence check. Values must be in RFC 3339 format. * `next_run_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. Filter expressions can be combined together using logical operators (`NOT`, `AND` & `OR`). The syntax to define filter expression is based on https://google.aip.dev/160. Examples: * `state=\"ACTIVE\" AND display_name:\"my_schedule_*\"` * `NOT display_name=\"my_schedule\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `end_time\u003e\"2021-05-18T00:00:00Z\" OR NOT end_time:*` * `create_pipeline_job_request:*`", "type": "string" }, "orderBy": { "type": "string", "description": "A comma-separated list of fields to order by. The default sort order is in ascending order. Use \"desc\" after a field name for descending. You can have multiple order_by fields provided. For example, using \"create_time desc, end_time\" will order results by create time in descending order, and if there are multiple schedules having the same create time, order them by the end time in ascending order. If order_by is not specified, it will order by default with create_time in descending order. Supported fields: * `create_time` * `start_time` * `end_time` * `next_run_time`", "location": "query" }, "pageToken": { "type": "string", "description": "The standard list page token. Typically obtained via ListSchedulesResponse.next_page_token of the previous ScheduleService.ListSchedules call.", "location": "query" }, "pageSize": { "type": "integer", "description": "The standard list page size. Default to 100 if not specified.", "location": "query", "format": "int32" } }, "parameterOrder": [ "parent" ] }, "patch": { "parameters": { "name": { "location": "path", "description": "Immutable. The resource name of the Schedule.", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", "required": true, "type": "string" }, "updateMask": { "type": "string", "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask.", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ], "description": "Updates an active or paused Schedule. When the Schedule is updated, new runs will be scheduled starting from the updated next execution time after the update time based on the time_specification in the updated Schedule. All unstarted runs before the update time will be skipped while already created runs will NOT be paused or canceled.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Schedule" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1Schedule" }, "id": "aiplatform.projects.locations.schedules.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH" } }, "resources": { "operations": { "methods": { "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.schedules.operations.get", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.schedules.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.schedules.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}" }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", "required": true, "type": "string" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.schedules.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations" }, "wait": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.schedules.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" } } } } }, "solvers": { "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/solvers/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/solvers/{solversId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.solvers.operations.delete" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/solvers/{solversId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.solvers.operations.get", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/solvers/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/solvers/{solversId}/operations", "id": "aiplatform.projects.locations.solvers.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/solvers/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } } } } } }, "indexes": { "methods": { "upsertDatapoints": { "parameters": { "index": { "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the Index resource to be updated. Format: `projects/{project}/locations/{location}/indexes/{index}`" } }, "parameterOrder": [ "index" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1UpsertDatapointsResponse" }, "description": "Add/update Datapoints into an Index.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}:upsertDatapoints", "path": "v1beta1/{+index}:upsertDatapoints", "httpMethod": "POST", "id": "aiplatform.projects.locations.indexes.upsertDatapoints", "request": { "$ref": "GoogleCloudAiplatformV1beta1UpsertDatapointsRequest" } }, "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes", "request": { "$ref": "GoogleCloudAiplatformV1beta1Index" }, "path": "v1beta1/{+parent}/indexes", "httpMethod": "POST", "id": "aiplatform.projects.locations.indexes.create", "parameters": { "parent": { "description": "Required. The resource name of the Location to create the Index in. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates an Index.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1Index" }, "id": "aiplatform.projects.locations.indexes.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Output only. The resource name of the Index." }, "updateMask": { "type": "string", "description": "The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask.", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ], "description": "Updates an Index.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes", "path": "v1beta1/{+parent}/indexes", "httpMethod": "GET", "id": "aiplatform.projects.locations.indexes.list", "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask" }, "pageToken": { "description": "The standard list page token. Typically obtained via ListIndexesResponse.next_page_token of the previous IndexService.ListIndexes call.", "location": "query", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location from which to list the Indexes. Format: `projects/{project}/locations/{location}`" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListIndexesResponse" }, "description": "Lists Indexes in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes an Index. An Index can only be deleted when all its DeployedIndexes had been undeployed.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Index resource to be deleted. Format: `projects/{project}/locations/{location}/indexes/{index}`" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.indexes.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}" }, "import": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Index resource to import data to. Format: `projects/{project}/locations/{location}/indexes/{index}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Imports an Index from an external source (e.g., BigQuery).", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}:import", "path": "v1beta1/{+name}:import", "httpMethod": "POST", "id": "aiplatform.projects.locations.indexes.import", "request": { "$ref": "GoogleCloudAiplatformV1beta1ImportIndexRequest" } }, "get": { "id": "aiplatform.projects.locations.indexes.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}", "description": "Gets an Index.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Index" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The name of the Index resource. Format: `projects/{project}/locations/{location}/indexes/{index}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "removeDatapoints": { "description": "Remove Datapoints from an Index.", "response": { "$ref": "GoogleCloudAiplatformV1beta1RemoveDatapointsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "index": { "description": "Required. The name of the Index resource to be updated. Format: `projects/{project}/locations/{location}/indexes/{index}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "required": true } }, "parameterOrder": [ "index" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1RemoveDatapointsRequest" }, "id": "aiplatform.projects.locations.indexes.removeDatapoints", "path": "v1beta1/{+index}:removeDatapoints", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}:removeDatapoints" } }, "resources": { "operations": { "methods": { "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.indexes.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations", "id": "aiplatform.projects.locations.indexes.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.indexes.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.indexes.operations.delete" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}", "id": "aiplatform.projects.locations.indexes.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" } } } } }, "persistentResources": { "methods": { "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}", "id": "aiplatform.projects.locations.persistentResources.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the PersistentResource to be deleted. Format: `projects/{project}/locations/{location}/persistentResources/{persistent_resource}`", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Deletes a PersistentResource.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}", "id": "aiplatform.projects.locations.persistentResources.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", "required": true, "description": "Required. The name of the PersistentResource resource. Format: `projects/{project_id_or_number}/locations/{location_id}/persistentResources/{persistent_resource_id}`", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Gets a PersistentResource.", "response": { "$ref": "GoogleCloudAiplatformV1beta1PersistentResource" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "reboot": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Reboots a PersistentResource.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the PersistentResource resource. Format: `projects/{project_id_or_number}/locations/{location_id}/persistentResources/{persistent_resource_id}`", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.persistentResources.reboot", "path": "v1beta1/{+name}:reboot", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1RebootPersistentResourceRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}:reboot" }, "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates a PersistentResource.", "parameters": { "parent": { "description": "Required. The resource name of the Location to create the PersistentResource in. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "persistentResourceId": { "type": "string", "description": "Required. The ID to use for the PersistentResource, which become the final component of the PersistentResource's resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.", "location": "query" } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/persistentResources", "httpMethod": "POST", "id": "aiplatform.projects.locations.persistentResources.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1PersistentResource" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources" }, "patch": { "request": { "$ref": "GoogleCloudAiplatformV1beta1PersistentResource" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.persistentResources.patch", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Updates a PersistentResource.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", "required": true, "type": "string", "description": "Immutable. Resource name of a PersistentResource.", "location": "path" }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Required. Specify the fields to be overwritten in the PersistentResource by the update method.", "type": "string" } }, "parameterOrder": [ "name" ] }, "list": { "description": "Lists PersistentResources in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListPersistentResourcesResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to list the PersistentResources from. Format: `projects/{project}/locations/{location}`", "location": "path" }, "pageSize": { "location": "query", "format": "int32", "description": "Optional. The standard list page size.", "type": "integer" }, "pageToken": { "location": "query", "description": "Optional. The standard list page token. Typically obtained via ListPersistentResourcesResponse.next_page_token of the previous PersistentResourceService.ListPersistentResource call.", "type": "string" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.persistentResources.list", "path": "v1beta1/{+parent}/persistentResources", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources" } }, "resources": { "operations": { "methods": { "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations", "id": "aiplatform.projects.locations.persistentResources.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "wait": { "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.persistentResources.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "get": { "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.persistentResources.operations.get" }, "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.persistentResources.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.persistentResources.operations.delete" } } } } }, "apps": { "resources": { "operations": { "methods": { "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/apps/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.apps.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/apps/{appsId}/operations" }, "wait": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/apps/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/apps/{appsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.apps.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/apps/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/apps/{appsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.apps.operations.get" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/apps/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.apps.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/apps/{appsId}/operations/{operationsId}" }, "cancel": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/apps/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/apps/{appsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.apps.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" } } } } }, "specialistPools": { "methods": { "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.specialistPools.delete", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the SpecialistPool to delete. Format: `projects/{project}/locations/{location}/specialistPools/{specialist_pool}`" }, "force": { "location": "query", "description": "If set to true, any specialist managers in this SpecialistPool will also be deleted. (Otherwise, the request will only work if the SpecialistPool has no specialist managers.)", "type": "boolean" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a SpecialistPool as well as all Specialists in the pool.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1SpecialistPool" }, "description": "Gets a SpecialistPool.", "parameters": { "name": { "location": "path", "description": "Required. The name of the SpecialistPool resource. The form is `projects/{project}/locations/{location}/specialistPools/{specialist_pool}`.", "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.specialistPools.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}" }, "create": { "path": "v1beta1/{+parent}/specialistPools", "httpMethod": "POST", "id": "aiplatform.projects.locations.specialistPools.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1SpecialistPool" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates a SpecialistPool.", "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "location": "path", "description": "Required. The parent Project name for the new SpecialistPool. The form is `projects/{project}/locations/{location}`." } }, "parameterOrder": [ "parent" ] }, "patch": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the SpecialistPool.", "location": "path" }, "updateMask": { "type": "string", "description": "Required. The update mask applies to the resource.", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Updates a SpecialistPool.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1SpecialistPool" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.specialistPools.patch" }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListSpecialistPoolsResponse" }, "description": "Lists SpecialistPools in a Location.", "parameters": { "pageToken": { "location": "query", "description": "The standard list page token. Typically obtained by ListSpecialistPoolsResponse.next_page_token of the previous SpecialistPoolService.ListSpecialistPools call. Return first page if empty.", "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The name of the SpecialistPool's parent resource. Format: `projects/{project}/locations/{location}`", "location": "path" }, "readMask": { "description": "Mask specifying which fields to read. FieldMask represents a set of", "location": "query", "format": "google-fieldmask", "type": "string" } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/specialistPools", "httpMethod": "GET", "id": "aiplatform.projects.locations.specialistPools.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools" } }, "resources": { "operations": { "methods": { "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.specialistPools.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}" }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.specialistPools.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}" }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.specialistPools.operations.cancel", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." }, "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.specialistPools.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.specialistPools.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}:wait" } } } } }, "evaluationMetrics": { "methods": { "delete": { "parameters": { "name": { "location": "path", "description": "Required. The name of the EvaluationMetric resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}`", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationMetrics/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes an EvaluationMetric.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationMetrics/{evaluationMetricsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.evaluationMetrics.delete" }, "create": { "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Location to create the EvaluationMetric in. Format: `projects/{project}/locations/{location}`", "location": "path" }, "evaluationMetricId": { "type": "string", "location": "query", "description": "Optional. The ID to use for the EvaluationMetric, which will become the final component of the EvaluationMetric's resource name. This value should be 1-63 characters, and valid characters are /a-z-/. The first character must be a lowercase letter, and the last character must be a lowercase letter or number." } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationMetric" }, "description": "Creates an EvaluationMetric.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationMetrics", "path": "v1beta1/{+parent}/evaluationMetrics", "httpMethod": "POST", "id": "aiplatform.projects.locations.evaluationMetrics.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationMetric" } }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationMetrics.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationMetrics/{evaluationMetricsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1EvaluationMetric" }, "description": "Gets an EvaluationMetric.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/evaluationMetrics/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the EvaluationMetric resource. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}`" } }, "parameterOrder": [ "name" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationMetrics", "id": "aiplatform.projects.locations.evaluationMetrics.list", "path": "v1beta1/{+parent}/evaluationMetrics", "httpMethod": "GET", "parameters": { "filter": { "description": "Optional. Filter expression that matches a subset of the EvaluationMetrics to show. For field names both snake_case and camelCase are supported. For more information about filter syntax, see [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the Location from which to list the EvaluationMetrics. Format: `projects/{project}/locations/{location}`" }, "pageToken": { "location": "query", "description": "Optional. A page token, received from a previous `ListEvaluationMetrics` call. Provide this to retrieve the subsequent page.", "type": "string" }, "orderBy": { "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending.", "location": "query", "type": "string" }, "pageSize": { "description": "Optional. The maximum number of EvaluationMetrics to return.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists EvaluationMetrics.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListEvaluationMetricsResponse" } } }, "resources": { "operations": { "methods": { "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/evaluationMetrics/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.evaluationMetrics.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationMetrics/{evaluationMetricsId}/operations/{operationsId}" }, "get": { "id": "aiplatform.projects.locations.evaluationMetrics.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationMetrics/{evaluationMetricsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationMetrics/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationMetrics.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/evaluationMetrics/{evaluationMetricsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationMetrics/[^/]+$", "required": true }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "ragEngineConfig": { "resources": { "operations": { "methods": { "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.ragEngineConfig.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig/operations", "id": "aiplatform.projects.locations.ragEngineConfig.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.ragEngineConfig.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.ragEngineConfig.operations.delete" }, "get": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig/operations/{operationsId}", "id": "aiplatform.projects.locations.ragEngineConfig.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" } } } } }, "agents": { "resources": { "operations": { "methods": { "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.agents.operations.wait", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.agents.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "parameterOrder": [ "name" ] }, "delete": { "id": "aiplatform.projects.locations.agents.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.agents.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.agents.operations.get" } } } } }, "tensorboards": { "methods": { "delete": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "required": true, "description": "Required. The name of the Tensorboard to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Deletes a Tensorboard.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}", "id": "aiplatform.projects.locations.tensorboards.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "readSize": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:readSize", "path": "v1beta1/{+tensorboard}:readSize", "httpMethod": "GET", "id": "aiplatform.projects.locations.tensorboards.readSize", "parameters": { "tensorboard": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`" } }, "parameterOrder": [ "tensorboard" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardSizeResponse" }, "description": "Returns the storage size for a given TensorBoard instance." }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.tensorboards.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Tensorboard" }, "description": "Gets a Tensorboard.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`" } }, "parameterOrder": [ "name" ] }, "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards", "path": "v1beta1/{+parent}/tensorboards", "httpMethod": "POST", "id": "aiplatform.projects.locations.tensorboards.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1Tensorboard" }, "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to create the Tensorboard in. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates a Tensorboard." }, "batchRead": { "parameters": { "tensorboard": { "location": "path", "description": "Required. The resource name of the Tensorboard containing TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`. The TensorboardTimeSeries referenced by time_series must be sub resources of this Tensorboard.", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "required": true, "type": "string" }, "timeSeries": { "location": "query", "description": "Required. The resource names of the TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", "repeated": true, "type": "string" } }, "parameterOrder": [ "tensorboard" ], "description": "Reads multiple TensorboardTimeSeries' data. The data point number limit is 1000 for scalars, 100 for tensors and blob references. If the number of data points stored is less than the limit, all data is returned. Otherwise, the number limit of data points is randomly selected from this time series and returned.", "response": { "$ref": "GoogleCloudAiplatformV1beta1BatchReadTensorboardTimeSeriesDataResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:batchRead", "id": "aiplatform.projects.locations.tensorboards.batchRead", "path": "v1beta1/{+tensorboard}:batchRead", "httpMethod": "GET" }, "list": { "id": "aiplatform.projects.locations.tensorboards.list", "path": "v1beta1/{+parent}/tensorboards", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Lists Tensorboards in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListTensorboardsResponse" }, "parameters": { "pageSize": { "description": "The maximum number of Tensorboards to return. The service may return fewer than this value. If unspecified, at most 100 Tensorboards are returned. The maximum value is 100; values above 100 are coerced to 100.", "location": "query", "format": "int32", "type": "integer" }, "readMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read." }, "pageToken": { "description": "A page token, received from a previous TensorboardService.ListTensorboards call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboards must match the call that provided the page token.", "location": "query", "type": "string" }, "orderBy": { "type": "string", "location": "query", "description": "Field to use to sort the list." }, "filter": { "location": "query", "description": "Lists the Tensorboards that match the filter expression.", "type": "string" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location to list Tensorboards. Format: `projects/{project}/locations/{location}`" } }, "parameterOrder": [ "parent" ] }, "patch": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates a Tensorboard.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "required": true, "type": "string", "description": "Output only. Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "location": "path" }, "updateMask": { "description": "Required. Field mask is used to specify the fields to be overwritten in the Tensorboard resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", "location": "query", "format": "google-fieldmask", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.tensorboards.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1beta1Tensorboard" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}" }, "readUsage": { "description": "Returns a list of monthly active users for a given TensorBoard instance.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "tensorboard": { "location": "path", "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "tensorboard" ], "id": "aiplatform.projects.locations.tensorboards.readUsage", "path": "v1beta1/{+tensorboard}:readUsage", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:readUsage" } }, "resources": { "operations": { "methods": { "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations", "id": "aiplatform.projects.locations.tensorboards.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "required": true, "type": "string" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.tensorboards.operations.wait" }, "get": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.tensorboards.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "delete": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.tensorboards.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "cancel": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.tensorboards.operations.cancel" } } }, "experiments": { "methods": { "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}", "id": "aiplatform.projects.locations.tensorboards.experiments.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "Required. The name of the TensorboardExperiment resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Gets a TensorboardExperiment.", "response": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" } }, "batchCreate": { "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesRequest" }, "id": "aiplatform.projects.locations.tensorboards.experiments.batchCreate", "path": "v1beta1/{+parent}:batchCreate", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}:batchCreate", "description": "Batch create TensorboardTimeSeries that belong to a TensorboardExperiment.", "response": { "$ref": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}` The TensorboardRuns referenced by the parent fields in the CreateTensorboardTimeSeriesRequest messages must be sub resources of this TensorboardExperiment.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a TensorboardExperiment.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "Required. The name of the TensorboardExperiment to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.tensorboards.experiments.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}" }, "list": { "path": "v1beta1/{+parent}/experiments", "httpMethod": "GET", "id": "aiplatform.projects.locations.tensorboards.experiments.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListTensorboardExperimentsResponse" }, "description": "Lists TensorboardExperiments in a Location.", "parameters": { "filter": { "location": "query", "description": "Lists the TensorboardExperiments that match the filter expression.", "type": "string" }, "parent": { "description": "Required. The resource name of the Tensorboard to list TensorboardExperiments. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "required": true }, "pageToken": { "description": "A page token, received from a previous TensorboardService.ListTensorboardExperiments call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardExperiments must match the call that provided the page token.", "location": "query", "type": "string" }, "orderBy": { "type": "string", "location": "query", "description": "Field to use to sort the list." }, "readMask": { "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The maximum number of TensorboardExperiments to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardExperiments are returned. The maximum value is 1000; values above 1000 are coerced to 1000.", "type": "integer" } }, "parameterOrder": [ "parent" ] }, "patch": { "request": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.tensorboards.experiments.patch", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}", "response": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" }, "description": "Updates a TensorboardExperiment.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Output only. Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "required": true, "type": "string" }, "updateMask": { "type": "string", "description": "Required. Field mask is used to specify the fields to be overwritten in the TensorboardExperiment resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ] }, "create": { "parameters": { "tensorboardExperimentId": { "type": "string", "description": "Required. The ID to use for the Tensorboard experiment, which becomes the final component of the Tensorboard experiment's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.", "location": "query" }, "parent": { "description": "Required. The resource name of the Tensorboard to create the TensorboardExperiment in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a TensorboardExperiment.", "response": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments", "id": "aiplatform.projects.locations.tensorboards.experiments.create", "path": "v1beta1/{+parent}/experiments", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardExperiment" } }, "write": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}:write", "path": "v1beta1/{+tensorboardExperiment}:write", "httpMethod": "POST", "id": "aiplatform.projects.locations.tensorboards.experiments.write", "request": { "$ref": "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataRequest" }, "parameters": { "tensorboardExperiment": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the TensorboardExperiment to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`" } }, "parameterOrder": [ "tensorboardExperiment" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataResponse" }, "description": "Write time series data points of multiple TensorboardTimeSeries in multiple TensorboardRun's. If any data fail to be ingested, an error is returned." } }, "resources": { "operations": { "methods": { "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations", "id": "aiplatform.projects.locations.tensorboards.experiments.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "wait": { "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.tensorboards.experiments.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.tensorboards.experiments.operations.get" }, "cancel": { "id": "aiplatform.projects.locations.tensorboards.experiments.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "delete": { "id": "aiplatform.projects.locations.tensorboards.experiments.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] } } }, "runs": { "methods": { "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a TensorboardRun.", "parameters": { "name": { "location": "path", "description": "Required. The name of the TensorboardRun to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}" }, "batchCreate": { "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRuns in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}` The parent field in the CreateTensorboardRunRequest messages must match this field." } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Batch create TensorboardRuns.", "response": { "$ref": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs:batchCreate", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.batchCreate", "path": "v1beta1/{+parent}/runs:batchCreate", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsRequest" } }, "get": { "description": "Gets a TensorboardRun.", "response": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the TensorboardRun resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.tensorboards.experiments.runs.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}" }, "write": { "parameters": { "tensorboardRun": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the TensorboardRun to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`" } }, "parameterOrder": [ "tensorboardRun" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataResponse" }, "description": "Write time series data points into multiple TensorboardTimeSeries under a TensorboardRun. If any data fail to be ingested, an error is returned.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}:write", "path": "v1beta1/{+tensorboardRun}:write", "httpMethod": "POST", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.write", "request": { "$ref": "GoogleCloudAiplatformV1beta1WriteTensorboardRunDataRequest" } }, "create": { "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "required": true }, "tensorboardRunId": { "location": "query", "description": "Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.", "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" }, "description": "Creates a TensorboardRun.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs", "request": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" }, "path": "v1beta1/{+parent}/runs", "httpMethod": "POST", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.create" }, "patch": { "response": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" }, "description": "Updates a TensorboardRun.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "required": true }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Required. Field mask is used to specify the fields to be overwritten in the TensorboardRun resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified." } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardRun" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.patch", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.list", "path": "v1beta1/{+parent}/runs", "httpMethod": "GET", "parameters": { "parent": { "description": "Required. The resource name of the TensorboardExperiment to list TensorboardRuns. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "required": true, "type": "string" }, "filter": { "type": "string", "location": "query", "description": "Lists the TensorboardRuns that match the filter expression." }, "orderBy": { "description": "Field to use to sort the list.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "A page token, received from a previous TensorboardService.ListTensorboardRuns call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardRuns must match the call that provided the page token." }, "readMask": { "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask", "type": "string" }, "pageSize": { "description": "The maximum number of TensorboardRuns to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardRuns are returned. The maximum value is 1000; values above 1000 are coerced to 1000.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Lists TensorboardRuns in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListTensorboardRunsResponse" } } }, "resources": { "operations": { "methods": { "list": { "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "parameterOrder": [ "name" ] }, "wait": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}" }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.cancel", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "timeSeries": { "methods": { "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a TensorboardTimeSeries.", "response": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" }, "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the TensorboardRun to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`" }, "tensorboardTimeSeriesId": { "type": "string", "location": "query", "description": "Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match \"a-z0-9{0, 127}\"" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.create", "path": "v1beta1/{+parent}/timeSeries", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries" }, "list": { "parameters": { "readMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read." }, "pageSize": { "location": "query", "format": "int32", "description": "The maximum number of TensorboardTimeSeries to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardTimeSeries are returned. The maximum value is 1000; values above 1000 are coerced to 1000.", "type": "integer" }, "parent": { "location": "path", "description": "Required. The resource name of the TensorboardRun to list TensorboardTimeSeries. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "required": true, "type": "string" }, "filter": { "description": "Lists the TensorboardTimeSeries that match the filter expression.", "location": "query", "type": "string" }, "orderBy": { "type": "string", "location": "query", "description": "Field to use to sort the list." }, "pageToken": { "type": "string", "location": "query", "description": "A page token, received from a previous TensorboardService.ListTensorboardTimeSeries call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardTimeSeries must match the call that provided the page token." } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Lists TensorboardTimeSeries in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListTensorboardTimeSeriesResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.list", "path": "v1beta1/{+parent}/timeSeries", "httpMethod": "GET" }, "patch": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "required": true, "description": "Output only. Name of the TensorboardTimeSeries.", "location": "path" }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Required. Field mask is used to specify the fields to be overwritten in the TensorboardTimeSeries resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates a TensorboardTimeSeries.", "response": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" } }, "exportTensorboardTimeSeries": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:exportTensorboardTimeSeries", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.exportTensorboardTimeSeries", "path": "v1beta1/{+tensorboardTimeSeries}:exportTensorboardTimeSeries", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataRequest" }, "parameters": { "tensorboardTimeSeries": { "description": "Required. The resource name of the TensorboardTimeSeries to export data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "required": true } }, "parameterOrder": [ "tensorboardTimeSeries" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Exports a TensorboardTimeSeries' data. Data is returned in paginated responses.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataResponse" } }, "delete": { "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}", "description": "Deletes a TensorboardTimeSeries.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the TensorboardTimeSeries to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`" } }, "parameterOrder": [ "name" ] }, "read": { "path": "v1beta1/{+tensorboardTimeSeries}:read", "httpMethod": "GET", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.read", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:read", "response": { "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardTimeSeriesDataResponse" }, "description": "Reads a TensorboardTimeSeries' data. By default, if the number of data points stored is less than 1000, all data is returned. Otherwise, 1000 data points is randomly selected from this time series and returned. This value can be changed by changing max_data_points, which can't be greater than 10k.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "filter": { "location": "query", "description": "Reads the TensorboardTimeSeries' data that match the filter expression.", "type": "string" }, "tensorboardTimeSeries": { "description": "Required. The resource name of the TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "required": true }, "maxDataPoints": { "description": "The maximum number of TensorboardTimeSeries' data to return. This value should be a positive integer. This value can be set to -1 to return all data.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [ "tensorboardTimeSeries" ] }, "readBlobData": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Gets bytes of TensorboardBlobs. This is to allow reading blob data stored in consumer project's Cloud Storage bucket without users having to obtain Cloud Storage access permission.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ReadTensorboardBlobDataResponse" }, "parameters": { "timeSeries": { "description": "Required. The resource name of the TensorboardTimeSeries to list Blobs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "required": true }, "blobIds": { "location": "query", "description": "IDs of the blobs to read.", "repeated": true, "type": "string" } }, "parameterOrder": [ "timeSeries" ], "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.readBlobData", "path": "v1beta1/{+timeSeries}:readBlobData", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:readBlobData" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "description": "Required. The name of the TensorboardTimeSeries resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Gets a TensorboardTimeSeries.", "response": { "$ref": "GoogleCloudAiplatformV1beta1TensorboardTimeSeries" } } }, "resources": { "operations": { "methods": { "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}" }, "cancel": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.cancel" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.get" }, "wait": { "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "required": true, "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } } } } } } } }, "endpoints": { "methods": { "update": { "request": { "$ref": "GoogleCloudAiplatformV1beta1UpdateEndpointLongRunningRequest" }, "id": "aiplatform.projects.locations.endpoints.update", "path": "v1beta1/{+name}:update", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:update", "description": "Updates an Endpoint with a long running operation.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "location": "path", "description": "Identifier. The resource name of the Endpoint." } }, "parameterOrder": [ "name" ] }, "explain": { "response": { "$ref": "GoogleCloudAiplatformV1beta1ExplainResponse" }, "description": "Perform an online explanation. If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have explanation_spec populated.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Endpoint requested to serve the explanation. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1ExplainRequest" }, "path": "v1beta1/{+endpoint}:explain", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.explain", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:explain" }, "setIamPolicy": { "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "path": "v1beta1/{+resource}:setIamPolicy", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.setIamPolicy", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:setIamPolicy", "response": { "$ref": "GoogleIamV1Policy" }, "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "type": "string", "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" } }, "parameterOrder": [ "resource" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes an Endpoint.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "description": "Required. The name of the Endpoint resource to be deleted. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.endpoints.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}" }, "computeTokens": { "response": { "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensResponse" }, "description": "Return a list of tokens based on the input text.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "endpoint": { "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids.", "location": "path" } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1ComputeTokensRequest" }, "path": "v1beta1/{+endpoint}:computeTokens", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.computeTokens", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:computeTokens" }, "serverStreamingPredict": { "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "parameterOrder": [ "endpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Perform a server-side streaming online prediction request for Vertex LLM streaming.", "response": { "$ref": "GoogleCloudAiplatformV1beta1StreamingPredictResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:serverStreamingPredict", "id": "aiplatform.projects.locations.endpoints.serverStreamingPredict", "path": "v1beta1/{+endpoint}:serverStreamingPredict", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1StreamingPredictRequest" } }, "fetchPredictOperation": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Fetch an asynchronous online prediction operation.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "location": "path" } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1FetchPredictOperationRequest" }, "path": "v1beta1/{+endpoint}:fetchPredictOperation", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.fetchPredictOperation", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:fetchPredictOperation" }, "streamGenerateContent": { "path": "v1beta1/{+model}:streamGenerateContent", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.streamGenerateContent", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:streamGenerateContent", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "description": "Generate content with multimodal inputs with streaming support.", "parameters": { "model": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "location": "path", "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "parameterOrder": [ "model" ] }, "testIamPermissions": { "parameters": { "resource": { "location": "path", "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "type": "string" }, "permissions": { "repeated": true, "type": "string", "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", "location": "query" } }, "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:testIamPermissions", "path": "v1beta1/{+resource}:testIamPermissions", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.testIamPermissions" }, "deployModel": { "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint resource into which to deploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "endpoint" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deploys a Model into this Endpoint, creating a DeployedModel within it.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:deployModel", "request": { "$ref": "GoogleCloudAiplatformV1beta1DeployModelRequest" }, "path": "v1beta1/{+endpoint}:deployModel", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.deployModel" }, "predict": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "", "response": { "$ref": "GoogleCloudAiplatformV1beta1PredictResponse" }, "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "parameterOrder": [ "endpoint" ], "id": "aiplatform.projects.locations.endpoints.predict", "path": "v1beta1/{+endpoint}:predict", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1PredictRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:predict" }, "streamRawPredict": { "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`" } }, "parameterOrder": [ "endpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Perform a streaming online prediction with an arbitrary HTTP payload.", "response": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:streamRawPredict", "id": "aiplatform.projects.locations.endpoints.streamRawPredict", "path": "v1beta1/{+endpoint}:streamRawPredict", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1StreamRawPredictRequest" } }, "directPredict": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:directPredict", "path": "v1beta1/{+endpoint}:directPredict", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.directPredict", "request": { "$ref": "GoogleCloudAiplatformV1beta1DirectPredictRequest" }, "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true } }, "parameterOrder": [ "endpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1DirectPredictResponse" }, "description": "Perform an unary online prediction request to a gRPC model server for Vertex first-party products and frameworks." }, "directRawPredict": { "description": "Perform an unary online prediction request to a gRPC model server for custom containers.", "response": { "$ref": "GoogleCloudAiplatformV1beta1DirectRawPredictResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1DirectRawPredictRequest" }, "id": "aiplatform.projects.locations.endpoints.directRawPredict", "path": "v1beta1/{+endpoint}:directRawPredict", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:directRawPredict" }, "list": { "id": "aiplatform.projects.locations.endpoints.list", "path": "v1beta1/{+parent}/endpoints", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints", "description": "Lists Endpoints in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListEndpointsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "description": "Optional. The standard list page token. Typically obtained via ListEndpointsResponse.next_page_token of the previous EndpointService.ListEndpoints call.", "location": "query", "type": "string" }, "parent": { "location": "path", "description": "Required. The resource name of the Location from which to list the Endpoints. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "filter": { "type": "string", "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `endpoint` supports `=` and `!=`. `endpoint` represents the Endpoint ID, i.e. the last segment of the Endpoint's resource name. * `display_name` supports `=` and `!=`. * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:*` or `labels:key` - key existence * A key including a space must be quoted. `labels.\"a key\"`. * `base_model_name` only supports `=`. Some examples: * `endpoint=1` * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"` * `baseModelName=\"text-bison\"`", "location": "query" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The standard list page size." }, "readMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Optional. Mask specifying which fields to read." }, "gdcZone": { "location": "query", "description": "Optional. Configures the Google Distributed Cloud (GDC) environment for online prediction. Only set this field when the Endpoint is to be deployed in a GDC environment.", "type": "string" } }, "parameterOrder": [ "parent" ] }, "undeployModel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Undeploys a Model from an Endpoint, removing a DeployedModel from it, and freeing all resources it's using.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the Endpoint resource from which to undeploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "parameterOrder": [ "endpoint" ], "id": "aiplatform.projects.locations.endpoints.undeployModel", "path": "v1beta1/{+endpoint}:undeployModel", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1UndeployModelRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:undeployModel" }, "patch": { "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.endpoints.patch", "request": { "$ref": "GoogleCloudAiplatformV1beta1Endpoint" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Endpoint" }, "description": "Updates an Endpoint.", "parameters": { "name": { "description": "Identifier. The resource name of the Endpoint.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "type": "string" }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask.", "type": "string" } }, "parameterOrder": [ "name" ] }, "rawPredict": { "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path" } }, "parameterOrder": [ "endpoint" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Perform an online prediction with an arbitrary HTTP payload. The response includes the following HTTP headers: * `X-Vertex-AI-Endpoint-Id`: ID of the Endpoint that served this prediction. * `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's DeployedModel that served this prediction.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:rawPredict", "request": { "$ref": "GoogleCloudAiplatformV1beta1RawPredictRequest" }, "path": "v1beta1/{+endpoint}:rawPredict", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.rawPredict" }, "getIamPolicy": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "response": { "$ref": "GoogleIamV1Policy" }, "parameters": { "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "type": "string", "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" }, "options.requestedPolicyVersion": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies)." } }, "parameterOrder": [ "resource" ], "id": "aiplatform.projects.locations.endpoints.getIamPolicy", "path": "v1beta1/{+resource}:getIamPolicy", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:getIamPolicy" }, "predictLongRunning": { "request": { "$ref": "GoogleCloudAiplatformV1beta1PredictLongRunningRequest" }, "id": "aiplatform.projects.locations.endpoints.predictLongRunning", "path": "v1beta1/{+endpoint}:predictLongRunning", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:predictLongRunning", "description": "", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "location": "path" } }, "parameterOrder": [ "endpoint" ] }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.endpoints.get", "parameters": { "name": { "location": "path", "description": "Required. The name of the Endpoint resource. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Endpoint" }, "description": "Gets an Endpoint.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "countTokens": { "response": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensResponse" }, "description": "Perform a token counting.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensRequest" }, "path": "v1beta1/{+endpoint}:countTokens", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.countTokens", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:countTokens" }, "generateContent": { "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "id": "aiplatform.projects.locations.endpoints.generateContent", "path": "v1beta1/{+model}:generateContent", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:generateContent", "description": "Generate content with multimodal inputs.", "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "model": { "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "type": "string", "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path" } }, "parameterOrder": [ "model" ] }, "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates an Endpoint.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "endpointId": { "type": "string", "description": "Immutable. The ID to use for endpoint, which will become the final component of the endpoint resource name. If not provided, Vertex AI will generate a value for this ID. If the first character is a letter, this value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The last character must be a letter or number. If the first character is a number, this value may be up to 9 characters, and valid characters are `[0-9]` with no leading zeros. When using HTTP/JSON, this field is populated based on a query string argument, such as `?endpoint_id=12345`. This is the fallback for fields that are not included in either the URI or the body.", "location": "query" }, "parent": { "location": "path", "description": "Required. The resource name of the Location to create the Endpoint in. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.endpoints.create", "path": "v1beta1/{+parent}/endpoints", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1Endpoint" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints" }, "mutateDeployedModel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates an existing deployed model. Updatable fields include `min_replica_count`, `max_replica_count`, `required_replica_count`, `autoscaling_metric_specs`, `disable_container_logging` (v1 only), and `enable_container_logging` (v1beta1 only).", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint resource into which to mutate a DeployedModel. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "endpoint" ], "id": "aiplatform.projects.locations.endpoints.mutateDeployedModel", "path": "v1beta1/{+endpoint}:mutateDeployedModel", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1MutateDeployedModelRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:mutateDeployedModel" } }, "resources": { "openapi": { "methods": { "responses": { "response": { "$ref": "GoogleApiHttpBody" }, "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/openapi$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" }, "deployedModelId": { "type": "string", "location": "query", "description": "ID of the DeployedModel that serves the invoke request." } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleApiHttpBody" }, "path": "v1beta1/{+endpoint}/responses", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.openapi.responses", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/openapi/responses" }, "embeddings": { "response": { "$ref": "GoogleApiHttpBody" }, "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/openapi$", "required": true, "type": "string" }, "deployedModelId": { "type": "string", "description": "ID of the DeployedModel that serves the invoke request.", "location": "query" } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleApiHttpBody" }, "path": "v1beta1/{+endpoint}/embeddings", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.openapi.embeddings", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/openapi/embeddings" }, "completions": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/openapi/completions", "path": "v1beta1/{+endpoint}/completions", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.openapi.completions", "request": { "$ref": "GoogleApiHttpBody" }, "parameters": { "endpoint": { "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/openapi$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" }, "deployedModelId": { "type": "string", "description": "ID of the DeployedModel that serves the invoke request.", "location": "query" } }, "parameterOrder": [ "endpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request." } } }, "google": { "resources": { "science": { "methods": { "inference": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/google/science/inference", "request": { "$ref": "GoogleApiHttpBody" }, "id": "aiplatform.projects.locations.endpoints.google.science.inference", "path": "v1beta1/{+endpoint}/science/inference", "httpMethod": "POST", "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/google$", "required": true, "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path" }, "deployedModelId": { "location": "query", "description": "ID of the DeployedModel that serves the invoke request.", "type": "string" } }, "parameterOrder": [ "endpoint" ], "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request.", "response": { "$ref": "GoogleApiHttpBody" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ] } } } } }, "operations": { "methods": { "list": { "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.endpoints.operations.list" }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.operations.wait", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.endpoints.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.endpoints.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}" }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.endpoints.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "chat": { "methods": { "completions": { "path": "v1beta1/{+endpoint}/chat/completions", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.chat.completions", "request": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/chat/completions", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Exposes an OpenAI-compatible endpoint for chat completions.", "parameters": { "endpoint": { "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "parameterOrder": [ "endpoint" ] } } }, "deployedModels": { "resources": { "invoke": { "methods": { "invoke": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/deployedModels/{deployedModelId}/invoke/{invokeId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1InvokeRequest" }, "id": "aiplatform.projects.locations.endpoints.deployedModels.invoke.invoke", "path": "v1beta1/{+endpoint}/deployedModels/{deployedModelId}/invoke/{+invokeId}", "httpMethod": "POST", "parameters": { "invokeId": { "location": "path", "required": true, "type": "string" }, "endpoint": { "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true }, "deployedModelId": { "location": "path", "description": "ID of the DeployedModel that serves the invoke request.", "required": true, "type": "string" } }, "parameterOrder": [ "endpoint", "deployedModelId", "invokeId" ], "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request.", "response": { "$ref": "GoogleApiHttpBody" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ] } } } } }, "invoke": { "methods": { "invoke": { "request": { "$ref": "GoogleCloudAiplatformV1beta1InvokeRequest" }, "id": "aiplatform.projects.locations.endpoints.invoke.invoke", "path": "v1beta1/{+endpoint}/invoke/{+invokeId}", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/invoke/{invokeId}", "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request.", "response": { "$ref": "GoogleApiHttpBody" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path" }, "invokeId": { "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "endpoint", "invokeId" ] } } } } }, "tuningJobs": { "methods": { "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Cancels a tuning job. Starts an asynchronous cancellation request. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use GenAiTuningService.GetTuningJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the tuning job is not deleted. Instead, its state is set to `CANCELLED`, and `error` is set to a status with a `google.rpc.Status.code` of 1, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the tuning job to cancel. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.tuningJobs.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1CancelTuningJobRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}:cancel" }, "optimizePrompt": { "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the location to optimize the prompt in. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Optimizes a prompt. Given a prompt, this method returns a stream of optimized prompts expanded from the original prompt.", "response": { "$ref": "GoogleCloudAiplatformV1beta1OptimizePromptResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tuningJobs:optimizePrompt", "id": "aiplatform.projects.locations.tuningJobs.optimizePrompt", "path": "v1beta1/{+parent}/tuningJobs:optimizePrompt", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1OptimizePromptRequest" } }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+$", "required": true, "description": "Required. The name of the tuning job to retrieve. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Gets a tuning job.", "response": { "$ref": "GoogleCloudAiplatformV1beta1TuningJob" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}", "id": "aiplatform.projects.locations.tuningJobs.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "rebaseTunedModel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tuningJobs:rebaseTunedModel", "id": "aiplatform.projects.locations.tuningJobs.rebaseTunedModel", "path": "v1beta1/{+parent}/tuningJobs:rebaseTunedModel", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1RebaseTunedModelRequest" }, "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the location in which to rebase the Model. Format: `projects/{project}/locations/{location}`" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Rebase a tuned model. A rebase operation takes a model that was previously tuned on a base model version, and retunes it on a new base model version. The rebase operation creates a new tuning job and a new tuned model.", "response": { "$ref": "GoogleLongrunningOperation" } }, "create": { "path": "v1beta1/{+parent}/tuningJobs", "httpMethod": "POST", "id": "aiplatform.projects.locations.tuningJobs.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1TuningJob" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tuningJobs", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1TuningJob" }, "description": "Creates a tuning job. A created tuning job will be subsequently executed to start the model tuning process.", "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the location to create the tuning job in. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ] }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListTuningJobsResponse" }, "description": "Lists tuning jobs in a location.", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the location to list the tuning jobs from. Format: `projects/{project}/locations/{location}`" }, "filter": { "description": "Optional. The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The standard list page size." }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token. Typically obtained from ListTuningJobsResponse.next_page_token of the previous GenAiTuningService.ListTuningJobs call." } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/tuningJobs", "httpMethod": "GET", "id": "aiplatform.projects.locations.tuningJobs.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tuningJobs" } }, "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.tuningJobs.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" } } } } }, "featureOnlineStores": { "methods": { "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStore" }, "description": "Gets details of a single FeatureOnlineStore.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the FeatureOnlineStore resource." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureOnlineStores.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}" }, "testIamPermissions": { "parameters": { "resource": { "location": "path", "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "required": true }, "permissions": { "repeated": true, "type": "string", "location": "query", "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions)." } }, "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}:testIamPermissions", "id": "aiplatform.projects.locations.featureOnlineStores.testIamPermissions", "path": "v1beta1/{+resource}:testIamPermissions", "httpMethod": "POST" }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.featureOnlineStores.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a single FeatureOnlineStore. The FeatureOnlineStore must not contain any FeatureViews.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The name of the FeatureOnlineStore to be deleted. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}`", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "required": true, "type": "string" }, "force": { "description": "If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted. (Otherwise, the request will only work if the FeatureOnlineStore has no FeatureViews.)", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores", "path": "v1beta1/{+parent}/featureOnlineStores", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureOnlineStores.list", "parameters": { "pageSize": { "type": "integer", "description": "The maximum number of FeatureOnlineStores to return. The service may return fewer than this value. If unspecified, at most 100 FeatureOnlineStores will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", "location": "query", "format": "int32" }, "filter": { "type": "string", "description": "Lists the FeatureOnlineStores that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` FeatureOnlineStores created or updated after 2020-01-01. * `labels.env = \"prod\"` FeatureOnlineStores with label \"env\" set to \"prod\".", "location": "query" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to list FeatureOnlineStores. Format: `projects/{project}/locations/{location}`", "location": "path" }, "pageToken": { "type": "string", "description": "A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureOnlineStores call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureOnlineStores must match the call that provided the page token.", "location": "query" }, "orderBy": { "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported Fields: * `create_time` * `update_time`", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListFeatureOnlineStoresResponse" }, "description": "Lists FeatureOnlineStores in a given project and location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "getIamPolicy": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}:getIamPolicy", "id": "aiplatform.projects.locations.featureOnlineStores.getIamPolicy", "path": "v1beta1/{+resource}:getIamPolicy", "httpMethod": "POST", "parameters": { "options.requestedPolicyVersion": { "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "location": "query", "format": "int32", "type": "integer" }, "resource": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "required": true, "location": "path", "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." } }, "parameterOrder": [ "resource" ], "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "response": { "$ref": "GoogleIamV1Policy" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "request": { "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStore" }, "id": "aiplatform.projects.locations.featureOnlineStores.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}", "description": "Updates the parameters of a single FeatureOnlineStore.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Identifier. Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "required": true }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Field mask is used to specify the fields to be overwritten in the FeatureOnlineStore resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `description` * `bigtable` * `bigtable.auto_scaling` * `bigtable.enable_multi_region_replica`", "type": "string" } }, "parameterOrder": [ "name" ] }, "setIamPolicy": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}:setIamPolicy", "id": "aiplatform.projects.locations.featureOnlineStores.setIamPolicy", "path": "v1beta1/{+resource}:setIamPolicy", "httpMethod": "POST", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "parameters": { "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "required": true, "type": "string", "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" } }, "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "response": { "$ref": "GoogleIamV1Policy" } }, "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores", "request": { "$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStore" }, "path": "v1beta1/{+parent}/featureOnlineStores", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureOnlineStores.create", "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to create FeatureOnlineStores. Format: `projects/{project}/locations/{location}`", "location": "path" }, "featureOnlineStoreId": { "description": "Required. The ID to use for this FeatureOnlineStore, which will become the final component of the FeatureOnlineStore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates a new FeatureOnlineStore in a given project and location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "featureViews": { "methods": { "setIamPolicy": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:setIamPolicy", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "path": "v1beta1/{+resource}:setIamPolicy", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.setIamPolicy", "parameters": { "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "type": "string", "location": "path", "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." } }, "parameterOrder": [ "resource" ], "response": { "$ref": "GoogleIamV1Policy" }, "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1FeatureView" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.patch", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "type": "string", "description": "Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", "location": "path" }, "updateMask": { "type": "string", "description": "Field mask is used to specify the fields to be overwritten in the FeatureView resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `service_agent_type` * `big_query_source` * `big_query_source.uri` * `big_query_source.entity_id_columns` * `feature_registry_source` * `feature_registry_source.feature_groups` * `sync_config` * `sync_config.cron` * `optimized_config.automatic_resources`", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Updates the parameters of a single FeatureView.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "streamingFetchFeatureValues": { "parameters": { "featureView": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "description": "Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", "location": "path" } }, "parameterOrder": [ "featureView" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Bidirectional streaming RPC to fetch feature values under a FeatureView. Requests may not have a one-to-one mapping to responses and responses may be returned out-of-order to reduce latency.", "response": { "$ref": "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:streamingFetchFeatureValues", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.streamingFetchFeatureValues", "path": "v1beta1/{+featureView}:streamingFetchFeatureValues", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesRequest" } }, "getIamPolicy": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "response": { "$ref": "GoogleIamV1Policy" }, "parameters": { "options.requestedPolicyVersion": { "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "location": "query", "format": "int32", "type": "integer" }, "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "type": "string", "location": "path", "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." } }, "parameterOrder": [ "resource" ], "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.getIamPolicy", "path": "v1beta1/{+resource}:getIamPolicy", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:getIamPolicy" }, "sync": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:sync", "request": { "$ref": "GoogleCloudAiplatformV1beta1SyncFeatureViewRequest" }, "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.sync", "path": "v1beta1/{+featureView}:sync", "httpMethod": "POST", "parameters": { "featureView": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "type": "string", "description": "Required. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", "location": "path" } }, "parameterOrder": [ "featureView" ], "description": "Triggers on-demand sync for the FeatureView.", "response": { "$ref": "GoogleCloudAiplatformV1beta1SyncFeatureViewResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "description": "Required. The name of the FeatureView to be deleted. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a single FeatureView.", "response": { "$ref": "GoogleLongrunningOperation" } }, "directWrite": { "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.directWrite", "path": "v1beta1/{+featureView}:directWrite", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:directWrite", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Bidirectional streaming RPC to directly write to feature values in a feature view. Requests may not have a one-to-one mapping to responses and responses may be returned out-of-order to reduce latency.", "response": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewDirectWriteResponse" }, "parameters": { "featureView": { "location": "path", "description": "FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true } }, "parameterOrder": [ "featureView" ] }, "generateFetchAccessToken": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:generateFetchAccessToken", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateFetchAccessTokenRequest" }, "path": "v1beta1/{+featureView}:generateFetchAccessToken", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.generateFetchAccessToken", "parameters": { "featureView": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "location": "path", "description": "FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`" } }, "parameterOrder": [ "featureView" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateFetchAccessTokenResponse" }, "description": "RPC to generate an access token for the given feature view. FeatureViews under the same FeatureOnlineStore share the same access token.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "testIamPermissions": { "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "resource": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "location": "path", "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." }, "permissions": { "location": "query", "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", "repeated": true, "type": "string" } }, "parameterOrder": [ "resource" ], "path": "v1beta1/{+resource}:testIamPermissions", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.testIamPermissions", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:testIamPermissions" }, "searchNearestEntities": { "description": "Search the nearest entities under a FeatureView. Search only works for indexable feature view; if a feature view isn't indexable, returns Invalid argument response.", "response": { "$ref": "GoogleCloudAiplatformV1beta1SearchNearestEntitiesResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "featureView": { "description": "Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "featureView" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1SearchNearestEntitiesRequest" }, "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.searchNearestEntities", "path": "v1beta1/{+featureView}:searchNearestEntities", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:searchNearestEntities" }, "get": { "parameters": { "name": { "location": "path", "description": "Required. The name of the FeatureView resource. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1FeatureView" }, "description": "Gets details of a single FeatureView.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.get" }, "create": { "parameters": { "featureViewId": { "description": "Required. The ID to use for the FeatureView, which will become the final component of the FeatureView's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a FeatureOnlineStore.", "location": "query", "type": "string" }, "runSyncImmediately": { "description": "Immutable. If set to true, one on demand sync will be run immediately, regardless whether the FeatureView.sync_config is configured or not.", "location": "query", "type": "boolean" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the FeatureOnlineStore to create FeatureViews. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}`" } }, "parameterOrder": [ "parent" ], "description": "Creates a new FeatureView in a given FeatureOnlineStore.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews", "request": { "$ref": "GoogleCloudAiplatformV1beta1FeatureView" }, "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.create", "path": "v1beta1/{+parent}/featureViews", "httpMethod": "POST" }, "fetchFeatureValues": { "request": { "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesRequest" }, "path": "v1beta1/{+featureView}:fetchFeatureValues", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.fetchFeatureValues", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:fetchFeatureValues", "response": { "$ref": "GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse" }, "description": "Fetch feature values under a FeatureView.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "featureView": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "type": "string", "description": "Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", "location": "path" } }, "parameterOrder": [ "featureView" ] }, "list": { "path": "v1beta1/{+parent}/featureViews", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListFeatureViewsResponse" }, "description": "Lists FeatureViews in a given FeatureOnlineStore.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "orderBy": { "type": "string", "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `feature_view_id` * `create_time` * `update_time`" }, "pageToken": { "type": "string", "description": "A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureViews call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureViews must match the call that provided the page token.", "location": "query" }, "parent": { "description": "Required. The resource name of the FeatureOnlineStore to list FeatureViews. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "required": true }, "filter": { "location": "query", "description": "Lists the FeatureViews that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e FeatureViews created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e FeatureViews having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any FeatureView which has a label with 'env' as the key.", "type": "string" }, "pageSize": { "type": "integer", "description": "The maximum number of FeatureViews to return. The service may return fewer than this value. If unspecified, at most 1000 FeatureViews will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", "location": "query", "format": "int32" } }, "parameterOrder": [ "parent" ] } }, "resources": { "operations": { "methods": { "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "type": "string" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}:wait" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}" } } }, "featureViewSyncs": { "methods": { "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/featureViewSyncs/{featureViewSyncsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.featureViewSyncs.get", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/featureViewSyncs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the FeatureViewSync resource. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1FeatureViewSync" }, "description": "Gets details of a single FeatureViewSync." }, "list": { "path": "v1beta1/{+parent}/featureViewSyncs", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.featureViewSyncs.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/featureViewSyncs", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListFeatureViewSyncsResponse" }, "description": "Lists FeatureViewSyncs in a given FeatureView.", "parameters": { "pageSize": { "type": "integer", "description": "The maximum number of FeatureViewSyncs to return. The service may return fewer than this value. If unspecified, at most 1000 FeatureViewSyncs will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", "location": "query", "format": "int32" }, "orderBy": { "type": "string", "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `create_time`" }, "pageToken": { "type": "string", "location": "query", "description": "A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureViewSyncs call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureViewSyncs must match the call that provided the page token." }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "description": "Required. The resource name of the FeatureView to list FeatureViewSyncs. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", "location": "path" }, "filter": { "type": "string", "description": "Lists the FeatureViewSyncs that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. Examples: * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e FeatureViewSyncs created after 2020-01-31T15:30:00.000000Z.", "location": "query" } }, "parameterOrder": [ "parent" ] } } } } }, "operations": { "methods": { "get": { "id": "aiplatform.projects.locations.featureOnlineStores.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "list": { "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.featureOnlineStores.operations.list" }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}", "id": "aiplatform.projects.locations.featureOnlineStores.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureOnlineStores.operations.wait", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "semanticGovernancePolicyEngine": { "resources": { "operations": { "methods": { "list": { "parameters": { "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicyEngine$", "required": true, "type": "string" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicyEngine/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.semanticGovernancePolicyEngine.operations.list" }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.semanticGovernancePolicyEngine.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicyEngine/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicyEngine/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicyEngine/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.semanticGovernancePolicyEngine.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicyEngine/operations/{operationsId}" }, "delete": { "id": "aiplatform.projects.locations.semanticGovernancePolicyEngine.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicyEngine/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicyEngine/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicyEngine/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicyEngine/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.semanticGovernancePolicyEngine.operations.cancel" } } } } }, "indexEndpoints": { "methods": { "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints", "request": { "$ref": "GoogleCloudAiplatformV1beta1IndexEndpoint" }, "path": "v1beta1/{+parent}/indexEndpoints", "httpMethod": "POST", "id": "aiplatform.projects.locations.indexEndpoints.create", "parameters": { "parent": { "description": "Required. The resource name of the Location to create the IndexEndpoint in. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates an IndexEndpoint.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "findNeighbors": { "parameters": { "indexEndpoint": { "location": "path", "description": "Required. The name of the index endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "indexEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Finds the nearest neighbors of each vector within the request.", "response": { "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:findNeighbors", "id": "aiplatform.projects.locations.indexEndpoints.findNeighbors", "path": "v1beta1/{+indexEndpoint}:findNeighbors", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1FindNeighborsRequest" } }, "list": { "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location from which to list the IndexEndpoints. Format: `projects/{project}/locations/{location}`", "location": "path" }, "filter": { "type": "string", "location": "query", "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `index_endpoint` supports = and !=. `index_endpoint` represents the IndexEndpoint ID, ie. the last segment of the IndexEndpoint's resourcename. * `display_name` supports =, != and regex() (uses [re2](https://github.com/google/re2/wiki/Syntax) syntax) * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* or labels:key - key existence A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `index_endpoint=\"1\"` * `display_name=\"myDisplayName\"` * `regex(display_name, \"^A\") -\u003e The display name starts with an A. * `labels.myKey=\"myValue\"`" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token. Typically obtained via ListIndexEndpointsResponse.next_page_token of the previous IndexEndpointService.ListIndexEndpoints call." }, "readMask": { "location": "query", "format": "google-fieldmask", "description": "Optional. Mask specifying which fields to read.", "type": "string" }, "pageSize": { "type": "integer", "description": "Optional. The standard list page size.", "location": "query", "format": "int32" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListIndexEndpointsResponse" }, "description": "Lists IndexEndpoints in a Location.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints", "path": "v1beta1/{+parent}/indexEndpoints", "httpMethod": "GET", "id": "aiplatform.projects.locations.indexEndpoints.list" }, "mutateDeployedIndex": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:mutateDeployedIndex", "id": "aiplatform.projects.locations.indexEndpoints.mutateDeployedIndex", "path": "v1beta1/{+indexEndpoint}:mutateDeployedIndex", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1DeployedIndex" }, "parameters": { "indexEndpoint": { "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "location": "path" } }, "parameterOrder": [ "indexEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Update an existing DeployedIndex under an IndexEndpoint.", "response": { "$ref": "GoogleLongrunningOperation" } }, "delete": { "parameters": { "name": { "description": "Required. The name of the IndexEndpoint resource to be deleted. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes an IndexEndpoint.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.indexEndpoints.delete" }, "patch": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1IndexEndpoint" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.indexEndpoints.patch", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "required": true, "description": "Output only. The resource name of the IndexEndpoint.", "location": "path" }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1IndexEndpoint" }, "description": "Updates an IndexEndpoint.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "deployIndex": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:deployIndex", "request": { "$ref": "GoogleCloudAiplatformV1beta1DeployIndexRequest" }, "id": "aiplatform.projects.locations.indexEndpoints.deployIndex", "path": "v1beta1/{+indexEndpoint}:deployIndex", "httpMethod": "POST", "parameters": { "indexEndpoint": { "location": "path", "description": "Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "required": true } }, "parameterOrder": [ "indexEndpoint" ], "description": "Deploys an Index into this IndexEndpoint, creating a DeployedIndex within it.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "readIndexDatapoints": { "parameters": { "indexEndpoint": { "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the index endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`" } }, "parameterOrder": [ "indexEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ReadIndexDatapointsResponse" }, "description": "Reads the datapoints/vectors of the given IDs. A maximum of 1000 datapoints can be retrieved in a batch.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:readIndexDatapoints", "path": "v1beta1/{+indexEndpoint}:readIndexDatapoints", "httpMethod": "POST", "id": "aiplatform.projects.locations.indexEndpoints.readIndexDatapoints", "request": { "$ref": "GoogleCloudAiplatformV1beta1ReadIndexDatapointsRequest" } }, "undeployIndex": { "parameters": { "indexEndpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "required": true, "description": "Required. The name of the IndexEndpoint resource from which to undeploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "location": "path" } }, "parameterOrder": [ "indexEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Undeploys an Index from an IndexEndpoint, removing a DeployedIndex from it, and freeing all resources it's using.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:undeployIndex", "path": "v1beta1/{+indexEndpoint}:undeployIndex", "httpMethod": "POST", "id": "aiplatform.projects.locations.indexEndpoints.undeployIndex", "request": { "$ref": "GoogleCloudAiplatformV1beta1UndeployIndexRequest" } }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1IndexEndpoint" }, "description": "Gets an IndexEndpoint.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the IndexEndpoint resource. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.indexEndpoints.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}" } }, "resources": { "operations": { "methods": { "cancel": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.indexEndpoints.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.indexEndpoints.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.indexEndpoints.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}" }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.indexEndpoints.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}:wait" }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.indexEndpoints.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "reasoningEngines": { "methods": { "getIamPolicy": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:getIamPolicy", "path": "v1beta1/{+resource}:getIamPolicy", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.getIamPolicy", "parameters": { "resource": { "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" }, "options.requestedPolicyVersion": { "location": "query", "format": "int32", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "type": "integer" } }, "parameterOrder": [ "resource" ], "response": { "$ref": "GoogleIamV1Policy" }, "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "Optional. The standard list page size.", "type": "integer" }, "pageToken": { "location": "query", "description": "Optional. The standard list page token.", "type": "string" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Location to list the ReasoningEngines from. Format: `projects/{project}/locations/{location}`", "location": "path" }, "filter": { "type": "string", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "location": "query" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListReasoningEnginesResponse" }, "description": "Lists reasoning engines in a location.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines", "path": "v1beta1/{+parent}/reasoningEngines", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.list" }, "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines", "request": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngine" }, "id": "aiplatform.projects.locations.reasoningEngines.create", "path": "v1beta1/{+parent}/reasoningEngines", "httpMethod": "POST", "parameters": { "parent": { "description": "Required. The resource name of the Location to create the ReasoningEngine in. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "description": "Creates a reasoning engine.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "streamQuery": { "parameters": { "name": { "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Streams queries using a reasoning engine.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:streamQuery", "request": { "$ref": "GoogleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest" }, "path": "v1beta1/{+name}:streamQuery", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.streamQuery" }, "delete": { "description": "Deletes a reasoning engine.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The name of the ReasoningEngine resource to be deleted. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" }, "force": { "type": "boolean", "location": "query", "description": "Optional. If set to true, child resources of this reasoning engine will also be deleted. Otherwise, the request will fail with FAILED_PRECONDITION error when the reasoning engine has undeleted child resources." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}" }, "executeCode": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:executeCode", "path": "v1beta1/{+name}:executeCode", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.executeCode", "request": { "$ref": "GoogleCloudAiplatformV1beta1ExecuteCodeRequest" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ExecuteCodeResponse" }, "description": "Executes code statelessly." }, "patch": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngine" }, "id": "aiplatform.projects.locations.reasoningEngines.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Identifier. The resource name of the ReasoningEngine. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "updateMask": { "type": "string", "description": "Optional. Mask specifying which fields to update.", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ], "description": "Updates a reasoning engine.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "setIamPolicy": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:setIamPolicy", "id": "aiplatform.projects.locations.reasoningEngines.setIamPolicy", "path": "v1beta1/{+resource}:setIamPolicy", "httpMethod": "POST", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "parameters": { "resource": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" } }, "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "response": { "$ref": "GoogleIamV1Policy" } }, "query": { "id": "aiplatform.projects.locations.reasoningEngines.query", "path": "v1beta1/{+name}:query", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:query", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Queries using a reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1beta1QueryReasoningEngineResponse" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "name" ] }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}", "response": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngine" }, "description": "Gets a reasoning engine.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The name of the ReasoningEngine resource. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "testIamPermissions": { "parameters": { "resource": { "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true }, "permissions": { "repeated": true, "type": "string", "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", "location": "query" } }, "parameterOrder": [ "resource" ], "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:testIamPermissions", "path": "v1beta1/{+resource}:testIamPermissions", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.testIamPermissions" } }, "resources": { "a2a": { "methods": { "tasks": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "historyLength": { "type": "string", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query" }, "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "type": "string", "pattern": "^tasks$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/tasks", "id": "aiplatform.projects.locations.reasoningEngines.a2a.tasks", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET" }, "extendedAgentCard": { "parameters": { "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "pattern": "^extendedAgentCard$", "required": true, "type": "string" }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/extendedAgentCard", "id": "aiplatform.projects.locations.reasoningEngines.a2a.extendedAgentCard", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET" }, "card": { "parameters": { "a2aEndpoint": { "pattern": "^card$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/card", "id": "aiplatform.projects.locations.reasoningEngines.a2a.card", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET" } }, "resources": { "message": { "methods": { "stream": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/message:stream", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:stream", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.a2a.message.stream", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "parameters": { "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. e.g., v1/message:stream.", "location": "path", "pattern": "^message$", "required": true, "type": "string" }, "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Streams queries using a reasoning engine instance via the A2A streaming protocol apis." }, "send": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/message:send", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:send", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.a2a.message.send", "parameters": { "a2aEndpoint": { "pattern": "^message$", "required": true, "type": "string", "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "location": "path" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "tasks": { "methods": { "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "parameters": { "a2aEndpoint": { "type": "string", "pattern": "^tasks/[^/]+$", "required": true, "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "location": "path" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.a2a.tasks.cancel", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/tasks/{tasksId}:cancel" }, "a2aGetReasoningEngine": { "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.a2a.tasks.a2aGetReasoningEngine", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/tasks/{tasksId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "parameters": { "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" }, "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "type": "string", "pattern": "^tasks/[^/]+$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "pushNotificationConfigs": { "id": "aiplatform.projects.locations.reasoningEngines.a2a.tasks.pushNotificationConfigs", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/tasks/{tasksId}/pushNotificationConfigs", "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true }, "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" }, "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "type": "string", "pattern": "^tasks/[^/]+/pushNotificationConfigs$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "subscribe": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." }, "a2aEndpoint": { "pattern": "^tasks/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123:subscribe`." } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Stream get request for reasoning engine instance via the A2A stream get protocol apis.", "response": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/tasks/{tasksId}:subscribe", "id": "aiplatform.projects.locations.reasoningEngines.a2a.tasks.subscribe", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:subscribe", "httpMethod": "GET" } }, "resources": { "pushNotificationConfigs": { "methods": { "a2aGetReasoningEngine": { "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.a2a.tasks.pushNotificationConfigs.a2aGetReasoningEngine", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/tasks/{tasksId}/pushNotificationConfigs/{pushNotificationConfigsId}", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "pattern": "^tasks/[^/]+/pushNotificationConfigs/[^/]+$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" }, "historyLength": { "type": "string", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ] } } } } }, "v1": { "methods": { "card": { "parameters": { "a2aEndpoint": { "pattern": "^v1/card$", "required": true, "type": "string", "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`" }, "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true }, "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/v1/card", "id": "aiplatform.projects.locations.reasoningEngines.a2a.v1.card", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET" }, "tasks": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks", "id": "aiplatform.projects.locations.reasoningEngines.a2a.v1.tasks", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "parameters": { "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" }, "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" }, "a2aEndpoint": { "type": "string", "pattern": "^v1/tasks$", "required": true, "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "extendedAgentCard": { "parameters": { "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true }, "historyLength": { "type": "string", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query" }, "a2aEndpoint": { "pattern": "^v1/extendedAgentCard$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/v1/extendedAgentCard", "id": "aiplatform.projects.locations.reasoningEngines.a2a.v1.extendedAgentCard", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET" } }, "resources": { "message": { "methods": { "stream": { "response": { "$ref": "GoogleApiHttpBody" }, "description": "Streams queries using a reasoning engine instance via the A2A streaming protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." }, "a2aEndpoint": { "pattern": "^v1/message$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. e.g., v1/message:stream.", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:stream", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.a2a.v1.message.stream", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/v1/message:stream" }, "send": { "parameters": { "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" }, "a2aEndpoint": { "location": "path", "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "pattern": "^v1/message$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/v1/message:send", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:send", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.a2a.v1.message.send", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } } }, "tasks": { "methods": { "cancel": { "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "pattern": "^v1/tasks/[^/]+$", "required": true, "type": "string", "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "location": "path" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "id": "aiplatform.projects.locations.reasoningEngines.a2a.v1.tasks.cancel", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks/{tasksId}:cancel" }, "a2aGetReasoningEngine": { "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.a2a.v1.tasks.a2aGetReasoningEngine", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks/{tasksId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "parameters": { "historyLength": { "type": "string", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "type": "string", "pattern": "^v1/tasks/[^/]+$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "subscribe": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks/{tasksId}:subscribe", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:subscribe", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.a2a.v1.tasks.subscribe", "parameters": { "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123:subscribe`.", "location": "path", "pattern": "^v1/tasks/[^/]+$", "required": true, "type": "string" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Stream get request for reasoning engine instance via the A2A stream get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "pushNotificationConfigs": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks/{tasksId}/pushNotificationConfigs", "id": "aiplatform.projects.locations.reasoningEngines.a2a.v1.tasks.pushNotificationConfigs", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "parameters": { "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "pattern": "^v1/tasks/[^/]+/pushNotificationConfigs$", "required": true, "type": "string" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" }, "historyLength": { "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "resources": { "pushNotificationConfigs": { "methods": { "a2aGetReasoningEngine": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks/{tasksId}/pushNotificationConfigs/{pushNotificationConfigsId}", "id": "aiplatform.projects.locations.reasoningEngines.a2a.v1.tasks.pushNotificationConfigs.a2aGetReasoningEngine", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "parameters": { "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "pattern": "^v1/tasks/[^/]+/pushNotificationConfigs/[^/]+$", "required": true, "type": "string" }, "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } } } } } }, "sessions": { "methods": { "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions", "request": { "$ref": "GoogleCloudAiplatformV1beta1Session" }, "id": "aiplatform.projects.locations.reasoningEngines.sessions.create", "path": "v1beta1/{+parent}/sessions", "httpMethod": "POST", "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the location to create the session in. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "sessionId": { "location": "query", "description": "Optional. The user defined ID to use for session, which will become the final component of the session resource name. If not provided, Vertex AI will generate a value for this ID. This value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The first and last characters must be a letter or number.", "type": "string" } }, "parameterOrder": [ "parent" ], "description": "Creates a new Session.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}", "id": "aiplatform.projects.locations.reasoningEngines.sessions.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1beta1Session" }, "parameters": { "name": { "description": "Identifier. The resource name of the session. Format: 'projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}'.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "required": true }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Optional. Field mask is used to control which fields get updated. If the mask is not present, all fields will be updated." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates the specific Session.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Session" } }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions", "id": "aiplatform.projects.locations.reasoningEngines.sessions.list", "path": "v1beta1/{+parent}/sessions", "httpMethod": "GET", "parameters": { "orderBy": { "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `create_time` * `update_time` Example: `create_time desc`.", "type": "string" }, "pageToken": { "description": "Optional. The next_page_token value returned from a previous list SessionService.ListSessions call.", "location": "query", "type": "string" }, "parent": { "description": "Required. The resource name of the location to list sessions from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" }, "filter": { "location": "query", "description": "Optional. The standard list filter. Supported fields: * `display_name` * `user_id` * `labels` Example: `display_name=\"abc\"`, `user_id=\"123\"`, `labels.key=\"value\"`.", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The maximum number of sessions to return. The service may return fewer than this value. If unspecified, at most 100 sessions will be returned." } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists Sessions in a given reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListSessionsResponse" } }, "appendEvent": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Appends an event to a given session.", "response": { "$ref": "GoogleCloudAiplatformV1beta1AppendEventResponse" }, "parameters": { "name": { "description": "Required. The resource name of the session to append event to. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.sessions.appendEvent", "path": "v1beta1/{+name}:appendEvent", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1SessionEvent" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}:appendEvent" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes details of the specific Session.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the session. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.sessions.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "required": true, "description": "Required. The resource name of the session. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Session" }, "description": "Gets details of the specific Session.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.sessions.get" } }, "resources": { "operations": { "methods": { "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.reasoningEngines.sessions.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.sessions.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}:cancel" }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.sessions.operations.delete", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.sessions.operations.list", "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.reasoningEngines.sessions.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" } } }, "events": { "methods": { "list": { "path": "v1beta1/{+parent}/events", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.sessions.events.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/events", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListEventsResponse" }, "description": "Lists Events in a given session.", "parameters": { "orderBy": { "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `timestamp` Example: `timestamp desc`.", "type": "string" }, "pageToken": { "location": "query", "description": "Optional. The next_page_token value returned from a previous list SessionService.ListEvents call.", "type": "string" }, "parent": { "location": "path", "description": "Required. The resource name of the session to list events from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "required": true }, "filter": { "type": "string", "location": "query", "description": "Optional. The standard list filter. Supported fields: * `timestamp` range (i.e. `timestamp\u003e=\"2025-01-31T11:30:00-04:00\"` where the timestamp is in RFC 3339 format) More detail in [AIP-160](https://google.aip.dev/160)." }, "pageSize": { "location": "query", "format": "int32", "description": "Optional. The maximum number of events to return. The service may return fewer than this value. If unspecified, at most 100 events will be returned. These events are ordered by timestamp in ascending order.", "type": "integer" } }, "parameterOrder": [ "parent" ] } } } } }, "feedbackEntries": { "resources": { "operations": { "methods": { "get": { "id": "aiplatform.projects.locations.reasoningEngines.feedbackEntries.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/feedbackEntries/{feedbackEntriesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/feedbackEntries/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.feedbackEntries.operations.cancel", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/feedbackEntries/{feedbackEntriesId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/feedbackEntries/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "delete": { "id": "aiplatform.projects.locations.reasoningEngines.feedbackEntries.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/feedbackEntries/{feedbackEntriesId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/feedbackEntries/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "list": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/feedbackEntries/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/feedbackEntries/{feedbackEntriesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.feedbackEntries.operations.list" }, "wait": { "id": "aiplatform.projects.locations.reasoningEngines.feedbackEntries.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/feedbackEntries/{feedbackEntriesId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/feedbackEntries/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "sandboxEnvironmentSnapshots": { "methods": { "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the sandbox environment snapshot. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentSnapshots/{sandbox_environment_snapshot}`" } }, "parameterOrder": [ "name" ], "description": "Gets details of the specific SandboxEnvironmentSnapshot.", "response": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSnapshot" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.list", "path": "v1beta1/{+parent}/sandboxEnvironmentSnapshots", "httpMethod": "GET", "parameters": { "pageToken": { "type": "string", "description": "Optional. The standard list page token, received from a previous `ListSandboxEnvironmentSnapshots` call. Provide this to retrieve the subsequent page.", "location": "query" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The maximum number of SandboxEnvironmentSnapshots to return. The service may return fewer than this value. If unspecified, at most 100 SandboxEnvironmentSnapshots will be returned. Values above 100 will be coerced to 100." }, "filter": { "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" }, "parent": { "location": "path", "description": "Required. The resource name of the reasoning engine to list sandbox environments from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "description": "Lists SandboxEnvironmentSnapshots in a given reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentSnapshotsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes the specific SandboxEnvironmentSnapshot.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The resource name of the SandboxEnvironmentSnapshot to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentSnapshots/{sandbox_environment_snapshot}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}" } }, "resources": { "operations": { "methods": { "list": { "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ] }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" } }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.operations.get", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "sandboxEnvironmentTemplates": { "methods": { "delete": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the SandboxEnvironmentTemplate to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentTemplates/{sandbox_environment_template}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes the specific SandboxEnvironmentTemplate.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "create": { "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the reasoning engine to create the SandboxEnvironmentTemplate in. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`." } }, "parameterOrder": [ "parent" ], "description": "Creates a SandboxEnvironmentTemplate in a given reasoning engine.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates", "request": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplate" }, "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.create", "path": "v1beta1/{+parent}/sandboxEnvironmentTemplates", "httpMethod": "POST" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the sandbox environment template. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentTemplates/{sandbox_environment_template}`" } }, "parameterOrder": [ "name" ], "description": "Gets details of the specific SandboxEnvironmentTemplate.", "response": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplate" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "path": "v1beta1/{+parent}/sandboxEnvironmentTemplates", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentTemplatesResponse" }, "description": "Lists SandboxEnvironmentTemplates in a given reasoning engine.", "parameters": { "parent": { "description": "Required. The resource name of the reasoning engine to list sandbox environment templates from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" }, "filter": { "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The maximum number of SandboxEnvironmentTemplates to return. The service may return fewer than this value. If unspecified, at most 100 SandboxEnvironmentTemplates will be returned." }, "pageToken": { "type": "string", "description": "Optional. The standard list page token, received from a previous `ListSandboxEnvironmentTemplates` call. Provide this to retrieve the subsequent page.", "location": "query" } }, "parameterOrder": [ "parent" ] } }, "resources": { "operations": { "methods": { "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.operations.wait", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.operations.get", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.operations.delete", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.operations.cancel", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." } } } } }, "sandboxEnvironments": { "methods": { "create": { "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the reasoning engine to create the SandboxEnvironment in. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`.", "location": "path" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a SandboxEnvironment in a given reasoning engine.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.create", "path": "v1beta1/{+parent}/sandboxEnvironments", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironment" } }, "execute": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Executes using a sandbox environment.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:execute", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.execute", "path": "v1beta1/{+name}:execute", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest" } }, "list": { "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the reasoning engine to list sandbox environments from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "filter": { "type": "string", "location": "query", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160)." }, "pageSize": { "description": "Optional. The maximum number of SandboxEnvironments to return. The service may return fewer than this value. If unspecified, at most 100 SandboxEnvironments will be returned.", "location": "query", "format": "int32", "type": "integer" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token, received from a previous `ListSandboxEnvironments` call. Provide this to retrieve the subsequent page." } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentsResponse" }, "description": "Lists SandboxEnvironments in a given reasoning engine.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments", "path": "v1beta1/{+parent}/sandboxEnvironments", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.list" }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.delete", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the SandboxEnvironment to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes the specific SandboxEnvironment." }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironment" }, "description": "Gets details of the specific SandboxEnvironment.", "parameters": { "name": { "location": "path", "description": "Required. The resource name of the sandbox environment. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "snapshot": { "parameters": { "name": { "description": "Required. The resource name of the sandbox environment to snapshot. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Snapshots the specific SandboxEnvironment resource and creates a SandboxEnvironmentSnapshot resource.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:snapshot", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.snapshot", "path": "v1beta1/{+name}:snapshot", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSnapshot" } } }, "resources": { "operations": { "methods": { "list": { "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.operations.list" }, "wait": { "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}" }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.operations.delete", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.operations.cancel", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "memories": { "methods": { "patch": { "id": "aiplatform.projects.locations.reasoningEngines.memories.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1beta1Memory" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Update a Memory.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "Identifier. Represents the resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$", "required": true }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Optional. Mask specifying which fields to update. Supported fields: * `display_name` * `description` * `fact`", "type": "string" } }, "parameterOrder": [ "name" ] }, "rollback": { "request": { "$ref": "GoogleCloudAiplatformV1beta1RollbackMemoryRequest" }, "id": "aiplatform.projects.locations.reasoningEngines.memories.rollback", "path": "v1beta1/{+name}:rollback", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}:rollback", "description": "Rollback Memory to a specific revision.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Memory to rollback. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "location": "path" } }, "parameterOrder": [ "name" ] }, "generate": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories:generate", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequest" }, "id": "aiplatform.projects.locations.reasoningEngines.memories.generate", "path": "v1beta1/{+parent}/memories:generate", "httpMethod": "POST", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the ReasoningEngine to generate memories for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "parent" ], "description": "Generate memories.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "retrieveProfiles": { "description": "Retrieves profiles.", "response": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveProfilesResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the ReasoningEngine to retrieve profiles from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveProfilesRequest" }, "id": "aiplatform.projects.locations.reasoningEngines.memories.retrieveProfiles", "path": "v1beta1/{+parent}/memories:retrieveProfiles", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories:retrieveProfiles" }, "get": { "parameters": { "name": { "description": "Required. The resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Memory" }, "description": "Get a Memory.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.memories.get" }, "ingestEvents": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories:ingestEvents", "request": { "$ref": "GoogleCloudAiplatformV1beta1IngestEventsRequest" }, "path": "v1beta1/{+parent}/memories:ingestEvents", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.memories.ingestEvents", "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the ReasoningEngine to ingest events to. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Ingests events for a Memory Bank.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories", "path": "v1beta1/{+parent}/memories", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.memories.list", "parameters": { "orderBy": { "location": "query", "description": "Optional. The standard list order by string. If not specified, the default order is `create_time desc`. If specified, the default sorting order of provided fields is ascending. More detail in [AIP-132](https://google.aip.dev/132). Supported fields: * `create_time` * `update_time`", "type": "string" }, "pageToken": { "location": "query", "description": "Optional. The standard list page token.", "type": "string" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the ReasoningEngine to list the Memories under. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "filter": { "type": "string", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). Supported fields: * `scope` (as a JSON string with equality match only) * `topics` (i.e. `topics.custom_memory_topic_label: \"example topic\" OR topics.managed_memory_topic: USER_PREFERENCES`)", "location": "query" }, "pageSize": { "type": "integer", "description": "Optional. The standard list page size.", "location": "query", "format": "int32" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListMemoriesResponse" }, "description": "List Memories." }, "purge": { "path": "v1beta1/{+parent}/memories:purge", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.memories.purge", "request": { "$ref": "GoogleCloudAiplatformV1beta1PurgeMemoriesRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories:purge", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Purge memories.", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the ReasoningEngine to purge memories from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "parent" ] }, "retrieve": { "response": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveMemoriesResponse" }, "description": "Retrieve memories.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the ReasoningEngine to retrieve memories from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveMemoriesRequest" }, "path": "v1beta1/{+parent}/memories:retrieve", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.memories.retrieve", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories:retrieve" }, "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories", "request": { "$ref": "GoogleCloudAiplatformV1beta1Memory" }, "path": "v1beta1/{+parent}/memories", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.memories.create", "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the ReasoningEngine to create the Memory under. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true }, "memoryId": { "location": "query", "description": "Optional. The user defined ID to use for memory, which will become the final component of the memory resource name. If not provided, Vertex AI will generate a value for this ID. This value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The first character must be a letter, and the last character must be a letter or number.", "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Create a Memory.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}", "id": "aiplatform.projects.locations.reasoningEngines.memories.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "description": "Required. The resource name of the Memory to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Delete a Memory.", "response": { "$ref": "GoogleLongrunningOperation" } } }, "resources": { "operations": { "methods": { "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.memories.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations" }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.memories.operations.wait", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}", "id": "aiplatform.projects.locations.reasoningEngines.memories.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" } }, "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.reasoningEngines.memories.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "id": "aiplatform.projects.locations.reasoningEngines.memories.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] } } }, "revisions": { "methods": { "get": { "response": { "$ref": "GoogleCloudAiplatformV1beta1MemoryRevision" }, "description": "Get a Memory Revision.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+/revisions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Memory Revision to retrieve. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}/revisions/{revision}`" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.memories.revisions.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/revisions/{revisionsId}" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/revisions", "path": "v1beta1/{+parent}/revisions", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.memories.revisions.list", "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "Optional. The standard list page size.", "type": "integer" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token." }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the Memory to list revisions for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`" }, "filter": { "type": "string", "location": "query", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). Supported fields (equality match only): * `labels`" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListMemoryRevisionsResponse" }, "description": "List Memory Revisions for a Memory.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "runtimeRevisions": { "methods": { "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.delete", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the ReasoningEngineRuntimeRevision resource to be deleted. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/runtimeRevisions/{runtime_revision}`", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a reasoning engine revision." }, "get": { "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a reasoning engine runtime revision.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngineRuntimeRevision" }, "parameters": { "name": { "description": "Required. The name of the ReasoningEngineRuntimeRevision resource. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/runtimeRevisions/{runtimeRevision}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "streamQuery": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Streams queries using a reasoning engine.", "response": { "$ref": "GoogleApiHttpBody" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.streamQuery", "path": "v1beta1/{+name}:streamQuery", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}:streamQuery" }, "query": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Queries using a reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1beta1QueryReasoningEngineResponse" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.query", "path": "v1beta1/{+name}:query", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}:query" }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists runtime revisions in a reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListReasoningEngineRuntimeRevisionsResponse" }, "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the ReasoningEngine to list the ReasoningEngineRuntimeRevisions from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true }, "filter": { "type": "string", "location": "query", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160)." }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The maximum number of ReasoningEngineRuntimeRevisions to return. The service may return fewer than this value. If unspecified, at most 50 revisions will be returned. The maximum value is 100; values above 100 will be coerced to 100." }, "pageToken": { "type": "string", "description": "Optional. The standard list page token.", "location": "query" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.list", "path": "v1beta1/{+parent}/runtimeRevisions", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions" } }, "resources": { "a2a": { "methods": { "card": { "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.card", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/card", "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "pattern": "^card$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "tasks": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.tasks", "parameters": { "a2aEndpoint": { "pattern": "^tasks$", "required": true, "type": "string", "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`" }, "historyLength": { "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "type": "string" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis." }, "extendedAgentCard": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/extendedAgentCard", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.extendedAgentCard", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." }, "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "type": "string", "pattern": "^extendedAgentCard$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis." } }, "resources": { "v1": { "methods": { "tasks": { "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "pattern": "^v1/tasks$", "required": true, "type": "string" }, "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true }, "historyLength": { "type": "string", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.v1.tasks", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks" }, "extendedAgentCard": { "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.v1.extendedAgentCard", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/extendedAgentCard", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "pattern": "^v1/extendedAgentCard$", "required": true, "type": "string" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "card": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/card", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.v1.card", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "parameters": { "a2aEndpoint": { "pattern": "^v1/card$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "message": { "methods": { "stream": { "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:stream", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.v1.message.stream", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/message:stream", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Streams queries using a reasoning engine instance via the A2A streaming protocol apis.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." }, "a2aEndpoint": { "type": "string", "pattern": "^v1/message$", "required": true, "description": "Required. The http endpoint extracted from the URL path. e.g., v1/message:stream.", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "send": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "parameters": { "a2aEndpoint": { "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "location": "path", "pattern": "^v1/message$", "required": true, "type": "string" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.v1.message.send", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:send", "httpMethod": "POST", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/message:send" } } }, "tasks": { "methods": { "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "parameters": { "a2aEndpoint": { "type": "string", "pattern": "^v1/tasks/[^/]+$", "required": true, "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "location": "path" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.v1.tasks.cancel", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks/{tasksId}:cancel" }, "a2aGetReasoningEngine": { "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.v1.tasks.a2aGetReasoningEngine", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks/{tasksId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "parameters": { "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "type": "string", "pattern": "^v1/tasks/[^/]+$", "required": true }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "subscribe": { "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:subscribe", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.v1.tasks.subscribe", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks/{tasksId}:subscribe", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Stream get request for reasoning engine instance via the A2A stream get protocol apis.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path" }, "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123:subscribe`.", "pattern": "^v1/tasks/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "pushNotificationConfigs": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks/{tasksId}/pushNotificationConfigs", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.v1.tasks.pushNotificationConfigs", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "parameters": { "a2aEndpoint": { "pattern": "^v1/tasks/[^/]+/pushNotificationConfigs$", "required": true, "type": "string", "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`" }, "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true }, "historyLength": { "type": "string", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "resources": { "pushNotificationConfigs": { "methods": { "a2aGetReasoningEngine": { "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string" }, "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "type": "string", "pattern": "^v1/tasks/[^/]+/pushNotificationConfigs/[^/]+$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.v1.tasks.pushNotificationConfigs.a2aGetReasoningEngine", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks/{tasksId}/pushNotificationConfigs/{pushNotificationConfigsId}" } } } } } } }, "tasks": { "methods": { "pushNotificationConfigs": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks/{tasksId}/pushNotificationConfigs", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.tasks.pushNotificationConfigs", "parameters": { "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" }, "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string" }, "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "type": "string", "pattern": "^tasks/[^/]+/pushNotificationConfigs$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "subscribe": { "description": "Stream get request for reasoning engine instance via the A2A stream get protocol apis.", "response": { "$ref": "GoogleApiHttpBody" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123:subscribe`.", "location": "path", "pattern": "^tasks/[^/]+$", "required": true, "type": "string" }, "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.tasks.subscribe", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:subscribe", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks/{tasksId}:subscribe" }, "cancel": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." }, "a2aEndpoint": { "pattern": "^tasks/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks/{tasksId}:cancel", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.tasks.cancel", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "a2aGetReasoningEngine": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks/{tasksId}", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.tasks.a2aGetReasoningEngine", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "parameters": { "a2aEndpoint": { "pattern": "^tasks/[^/]+$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" }, "historyLength": { "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "type": "string" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "pushNotificationConfigs": { "methods": { "a2aGetReasoningEngine": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "parameters": { "a2aEndpoint": { "type": "string", "pattern": "^tasks/[^/]+/pushNotificationConfigs/[^/]+$", "required": true, "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." } }, "parameterOrder": [ "name", "a2aEndpoint" ], "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.tasks.pushNotificationConfigs.a2aGetReasoningEngine", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks/{tasksId}/pushNotificationConfigs/{pushNotificationConfigsId}" } } } } }, "message": { "methods": { "stream": { "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.message.stream", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:stream", "httpMethod": "POST", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/message:stream", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Streams queries using a reasoning engine instance via the A2A streaming protocol apis.", "response": { "$ref": "GoogleApiHttpBody" }, "parameters": { "a2aEndpoint": { "type": "string", "pattern": "^message$", "required": true, "description": "Required. The http endpoint extracted from the URL path. e.g., v1/message:stream.", "location": "path" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "send": { "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:send", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.a2a.message.send", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/message:send", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "type": "string", "pattern": "^message$", "required": true, "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "location": "path" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." } }, "parameterOrder": [ "name", "a2aEndpoint" ] } } } } }, "operations": { "methods": { "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.operations.wait", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.operations.list" }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.operations.cancel", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "examples": { "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/examples/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/examples/{examplesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.examples.operations.delete" }, "cancel": { "id": "aiplatform.projects.locations.reasoningEngines.examples.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/examples/{examplesId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/examples/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ] }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/examples/{examplesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.examples.operations.wait", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/examples/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.examples.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/examples/{examplesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/examples/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "a2aTasks": { "methods": { "create": { "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the ReasoningEngine to create the A2aTask under. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string" }, "a2aTaskId": { "location": "query", "description": "Required. User-defined ID of the A2aTask. This ID must be unique within the ReasoningEngine. It must be 1-63 characters, start with a lowercase letter or number, end with a lowercase letter or number, and only contain lowercase letters, numbers, and hyphens [AIP-122](https://google.aip.dev/122). Starting with a number is allowed for compatibility with the auto-generated UUID from A2A SDK.", "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates an A2aTask.", "response": { "$ref": "GoogleCloudAiplatformV1beta1A2aTask" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2aTasks", "id": "aiplatform.projects.locations.reasoningEngines.a2aTasks.create", "path": "v1beta1/{+parent}/a2aTasks", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1A2aTask" } }, "appendEvents": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2aTasks/{a2aTasksId}:appendEvents", "request": { "$ref": "GoogleCloudAiplatformV1beta1AppendA2aTaskEventsRequest" }, "path": "v1beta1/{+name}:appendEvents", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.a2aTasks.appendEvents", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/a2aTasks/[^/]+$", "required": true, "description": "Required. The resource name of the A2aTask to append events to. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/a2aTasks/{a2a_task}`", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1AppendA2aTaskEventsResponse" }, "description": "Appends TaskEvents to an A2aTask.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The maximum number of tasks to return. The service may return fewer than this value. If unspecified, at most 10 tasks will be returned. The maximum value is 100; values above 100 will hit exception." }, "parent": { "location": "path", "description": "Required. The resource name of the ReasoningEngine to list the A2aTasks under. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true }, "filter": { "location": "query", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). Supported fields: * `context_id` * `state` Example: `context_id=\"abc\"`, `state=\"WORKING\"`.", "type": "string" }, "orderBy": { "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. If this field is omitted, the default ordering is `create_time` descending. More detail in [AIP-132](https://google.aip.dev/132). Supported fields: * `create_time` * `update_time` Example: `create_time desc`.", "type": "string" }, "pageToken": { "description": "Optional. The next_page_token value returned from a previous list AgentEngineTaskStoreService.ListA2aTasks call.", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListA2aTasksResponse" }, "description": "Lists A2aTasks for a ReasoningEngine.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2aTasks", "path": "v1beta1/{+parent}/a2aTasks", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.a2aTasks.list" }, "delete": { "parameters": { "name": { "location": "path", "description": "Required. The resource name of the A2aTask to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/a2aTasks/{a2a_task}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/a2aTasks/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes an A2aTask.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2aTasks/{a2aTasksId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.a2aTasks.delete" }, "get": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/a2aTasks/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the A2aTask. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/a2aTasks/{a2a_task}`", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Gets an A2aTask.", "response": { "$ref": "GoogleCloudAiplatformV1beta1A2aTask" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2aTasks/{a2aTasksId}", "id": "aiplatform.projects.locations.reasoningEngines.a2aTasks.get", "path": "v1beta1/{+name}", "httpMethod": "GET" } }, "resources": { "events": { "methods": { "list": { "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "Optional. The maximum number of events to return. The service may return fewer than this value. If unspecified, at most 100 events will be returned. The maximum value is 100; values above 100 will hit exception.", "type": "integer" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/a2aTasks/[^/]+$", "required": true, "description": "Required. The resource name of the A2aTask to list the TaskEvents under. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/a2aTasks/{a2a_task}`", "location": "path" }, "filter": { "type": "string", "location": "query", "description": "Optional. The standard list filter. Supported fields: * `create_time` range (i.e. `create_time\u003e=\"2025-01-31T11:30:00-04:00\"` where the timestamp is in RFC 3339 format) More detail in [AIP-160](https://google.aip.dev/160)." }, "orderBy": { "type": "string", "description": "Optional. A comma-separated list of fields to order the results by. If this field is omitted, the results will be ordered by `event_sequence_number` in descending order. For each field, the default sort order is ascending. To specify descending order for a field, append a ` desc` suffix. For example: `create_time desc`. Supported fields: * `create_time` * `event_sequence_number`", "location": "query" }, "pageToken": { "description": "Optional. The next_page_token value returned from a previous list AgentEngineTaskStoreService.ListA2aTaskEvents call.", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists TaskEvents for an A2aTask.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListA2aTaskEventsResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/a2aTasks/{a2aTasksId}/events", "id": "aiplatform.projects.locations.reasoningEngines.a2aTasks.events.list", "path": "v1beta1/{+parent}/events", "httpMethod": "GET" } } } } }, "operations": { "methods": { "delete": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.operations.delete" }, "cancel": { "id": "aiplatform.projects.locations.reasoningEngines.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}:wait" }, "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations" } } } } }, "deploymentResourcePools": { "methods": { "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Delete a DeploymentResourcePool.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "Required. The name of the DeploymentResourcePool to delete. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.deploymentResourcePools.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}" }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the DeploymentResourcePool to retrieve. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1DeploymentResourcePool" }, "description": "Get a DeploymentResourcePool.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.deploymentResourcePools.get" }, "create": { "request": { "$ref": "GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolRequest" }, "path": "v1beta1/{+parent}/deploymentResourcePools", "httpMethod": "POST", "id": "aiplatform.projects.locations.deploymentResourcePools.create", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Create a DeploymentResourcePool.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "location": "path", "description": "Required. The parent location resource where this DeploymentResourcePool will be created. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools", "id": "aiplatform.projects.locations.deploymentResourcePools.list", "path": "v1beta1/{+parent}/deploymentResourcePools", "httpMethod": "GET", "parameters": { "parent": { "description": "Required. The parent Location which owns this collection of DeploymentResourcePools. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The maximum number of DeploymentResourcePools to return. The service may return fewer than this value." }, "pageToken": { "type": "string", "location": "query", "description": "A page token, received from a previous `ListDeploymentResourcePools` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `ListDeploymentResourcePools` must match the call that provided the page token." } }, "parameterOrder": [ "parent" ], "description": "List DeploymentResourcePools in a location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListDeploymentResourcePoolsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Update a DeploymentResourcePool.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", "required": true, "type": "string", "description": "Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", "location": "path" }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Required. The list of fields to update." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.deploymentResourcePools.patch", "request": { "$ref": "GoogleCloudAiplatformV1beta1DeploymentResourcePool" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}" }, "queryDeployedModels": { "parameters": { "deploymentResourcePool": { "location": "path", "description": "Required. The name of the target DeploymentResourcePool to query. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", "required": true }, "pageToken": { "location": "query", "description": "A page token, received from a previous `QueryDeployedModels` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `QueryDeployedModels` must match the call that provided the page token.", "type": "string" }, "pageSize": { "description": "The maximum number of DeployedModels to return. The service may return fewer than this value.", "location": "query", "format": "int32", "type": "integer" } }, "parameterOrder": [ "deploymentResourcePool" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "List DeployedModels that have been deployed on this DeploymentResourcePool.", "response": { "$ref": "GoogleCloudAiplatformV1beta1QueryDeployedModelsResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}:queryDeployedModels", "id": "aiplatform.projects.locations.deploymentResourcePools.queryDeployedModels", "path": "v1beta1/{+deploymentResourcePool}:queryDeployedModels", "httpMethod": "GET" } }, "resources": { "operations": { "methods": { "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.deploymentResourcePools.operations.wait", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "list": { "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.deploymentResourcePools.operations.list" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.deploymentResourcePools.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}" }, "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.deploymentResourcePools.operations.cancel", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.deploymentResourcePools.operations.get", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "notebookExecutionJobs": { "methods": { "reportEvent": { "response": { "$ref": "GoogleCloudAiplatformV1beta1ReportExecutionEventResponse" }, "description": "", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the NotebookExecutionJob resource. Format: `projects/{project}/locations/{location}/notebookExecutionJobs/{notebook_execution_jobs}`", "location": "path" } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1ReportExecutionEventRequest" }, "path": "v1beta1/{+name}:reportEvent", "httpMethod": "POST", "id": "aiplatform.projects.locations.notebookExecutionJobs.reportEvent", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}:reportEvent" }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs", "path": "v1beta1/{+parent}/notebookExecutionJobs", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookExecutionJobs.list", "parameters": { "pageSize": { "type": "integer", "description": "Optional. The standard list page size.", "location": "query", "format": "int32" }, "view": { "type": "string", "enumDescriptions": [ "When unspecified, the API defaults to the BASIC view.", "Includes all fields except for direct notebook inputs.", "Includes all fields." ], "description": "Optional. The NotebookExecutionJob view. Defaults to BASIC.", "location": "query", "enum": [ "NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED", "NOTEBOOK_EXECUTION_JOB_VIEW_BASIC", "NOTEBOOK_EXECUTION_JOB_VIEW_FULL" ] }, "orderBy": { "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", "type": "string" }, "pageToken": { "description": "Optional. The standard list page token. Typically obtained via ListNotebookExecutionJobsResponse.next_page_token of the previous NotebookService.ListNotebookExecutionJobs call.", "location": "query", "type": "string" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location from which to list the NotebookExecutionJobs. Format: `projects/{project}/locations/{location}`" }, "filter": { "type": "string", "location": "query", "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookExecutionJob` supports = and !=. `notebookExecutionJob` represents the NotebookExecutionJob ID. * `displayName` supports = and != and regex. * `schedule` supports = and != and regex. Some examples: * `notebookExecutionJob=\"123\"` * `notebookExecutionJob=\"my-execution-job\"` * `displayName=\"myDisplayName\"` and `displayName=~\"myDisplayNameRegex\"`" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListNotebookExecutionJobsResponse" }, "description": "Lists NotebookExecutionJobs in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a NotebookExecutionJob.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`" }, "notebookExecutionJobId": { "type": "string", "description": "Optional. User specified ID for the NotebookExecutionJob.", "location": "query" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.notebookExecutionJobs.create", "path": "v1beta1/{+parent}/notebookExecutionJobs", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJob" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookExecutionJobs.get", "parameters": { "view": { "location": "query", "enum": [ "NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED", "NOTEBOOK_EXECUTION_JOB_VIEW_BASIC", "NOTEBOOK_EXECUTION_JOB_VIEW_FULL" ], "description": "Optional. The NotebookExecutionJob view. Defaults to BASIC.", "type": "string", "enumDescriptions": [ "When unspecified, the API defaults to the BASIC view.", "Includes all fields except for direct notebook inputs.", "Includes all fields." ] }, "name": { "description": "Required. The name of the NotebookExecutionJob resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1NotebookExecutionJob" }, "description": "Gets a NotebookExecutionJob.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "generateAccessToken": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}:generateAccessToken", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest" }, "path": "v1beta1/{+name}:generateAccessToken", "httpMethod": "POST", "id": "aiplatform.projects.locations.notebookExecutionJobs.generateAccessToken", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the resource requesting the OAuth2 token. Format: `projects/{project}/locations/{location}/notebookRuntimes/{notebook_runtime}` `projects/{project}/locations/{location}/notebookExecutionJobs/{notebook_execution_job}`", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateAccessTokenResponse" }, "description": "Internal only: Called from Compute Engine instance to obtain EUC for owner Anonymous access: authenticates caller using VM identity JWT. Design doc: go/colab-on-vertex-euc-dd", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.notebookExecutionJobs.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a NotebookExecutionJob.", "parameters": { "name": { "location": "path", "description": "Required. The name of the NotebookExecutionJob resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] } }, "resources": { "operations": { "methods": { "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.list", "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", "required": true, "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.wait", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.get" }, "cancel": { "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "extensionControllers": { "resources": { "operations": { "methods": { "wait": { "id": "aiplatform.projects.locations.extensionControllers.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensionControllers/{extensionControllersId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/extensionControllers/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ] }, "list": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensionControllers/{extensionControllersId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.extensionControllers.operations.list", "parameters": { "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/extensionControllers/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.extensionControllers.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensionControllers/{extensionControllersId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/extensionControllers/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/extensionControllers/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.extensionControllers.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensionControllers/{extensionControllersId}/operations/{operationsId}:cancel" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/extensionControllers/{extensionControllersId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.extensionControllers.operations.get", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/extensionControllers/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." } } } } }, "semanticGovernancePolicies": { "resources": { "operations": { "methods": { "cancel": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.semanticGovernancePolicies.operations.cancel" }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.semanticGovernancePolicies.operations.delete" }, "get": { "id": "aiplatform.projects.locations.semanticGovernancePolicies.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "wait": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.semanticGovernancePolicies.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.semanticGovernancePolicies.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations" } } } } }, "dataLabelingJobs": { "methods": { "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.dataLabelingJobs.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}", "response": { "$ref": "GoogleCloudAiplatformV1beta1DataLabelingJob" }, "description": "Gets a DataLabelingJob.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The name of the DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}:cancel", "request": { "$ref": "GoogleCloudAiplatformV1beta1CancelDataLabelingJobRequest" }, "id": "aiplatform.projects.locations.dataLabelingJobs.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "location": "path", "description": "Required. The name of the DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Cancels a DataLabelingJob. Success of cancellation is not guaranteed.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.dataLabelingJobs.delete", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the DataLabelingJob to be deleted. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a DataLabelingJob." }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists DataLabelingJobs in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListDataLabelingJobsResponse" }, "parameters": { "readMask": { "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read. FieldMask represents a set of symbolic field paths. For example, the mask can be `paths: \"name\"`. The \"name\" here is a field in DataLabelingJob. If this field is not set, all fields of the DataLabelingJob are returned.", "type": "string" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The parent of the DataLabelingJob. Format: `projects/{project}/locations/{location}`", "location": "path" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "orderBy": { "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending.", "type": "string" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.dataLabelingJobs.list", "path": "v1beta1/{+parent}/dataLabelingJobs", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs" }, "create": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs", "path": "v1beta1/{+parent}/dataLabelingJobs", "httpMethod": "POST", "id": "aiplatform.projects.locations.dataLabelingJobs.create", "request": { "$ref": "GoogleCloudAiplatformV1beta1DataLabelingJob" }, "parameters": { "parent": { "description": "Required. The parent of the DataLabelingJob. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1DataLabelingJob" }, "description": "Creates a DataLabelingJob." } }, "resources": { "operations": { "methods": { "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.dataLabelingJobs.operations.cancel", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:cancel" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.dataLabelingJobs.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.dataLabelingJobs.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.dataLabelingJobs.operations.wait" }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.dataLabelingJobs.operations.list", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "parameterOrder": [ "name" ] } } } } }, "modelMonitors": { "methods": { "list": { "id": "aiplatform.projects.locations.modelMonitors.list", "path": "v1beta1/{+parent}/modelMonitors", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors", "description": "Lists ModelMonitors in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListModelMonitorsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" }, "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the Location to list the ModelMonitors from. Format: `projects/{project}/locations/{location}`" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "readMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read." } }, "parameterOrder": [ "parent" ] }, "patch": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Immutable. Resource name of the ModelMonitor. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`." }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Required. Mask specifying which fields to update." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Updates a ModelMonitor.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitor" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.modelMonitors.patch" }, "create": { "request": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitor" }, "id": "aiplatform.projects.locations.modelMonitors.create", "path": "v1beta1/{+parent}/modelMonitors", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors", "description": "Creates a ModelMonitor.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location to create the ModelMonitor in. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "modelMonitorId": { "location": "query", "description": "Optional. The ID to use for the Model Monitor, which will become the final component of the model monitor resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.", "type": "string" } }, "parameterOrder": [ "parent" ] }, "searchModelMonitoringStats": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsResponse" }, "description": "Searches Model Monitoring Stats generated within a given time window.", "parameters": { "modelMonitor": { "location": "path", "description": "Required. ModelMonitor resource name. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", "required": true } }, "parameterOrder": [ "modelMonitor" ], "path": "v1beta1/{+modelMonitor}:searchModelMonitoringStats", "httpMethod": "POST", "id": "aiplatform.projects.locations.modelMonitors.searchModelMonitoringStats", "request": { "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsRequest" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}:searchModelMonitoringStats" }, "get": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.modelMonitors.get", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", "required": true, "description": "Required. The name of the ModelMonitor resource. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitor" }, "description": "Gets a ModelMonitor.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "searchModelMonitoringAlerts": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}:searchModelMonitoringAlerts", "path": "v1beta1/{+modelMonitor}:searchModelMonitoringAlerts", "httpMethod": "POST", "id": "aiplatform.projects.locations.modelMonitors.searchModelMonitoringAlerts", "request": { "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsRequest" }, "parameters": { "modelMonitor": { "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. ModelMonitor resource name. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`" } }, "parameterOrder": [ "modelMonitor" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsResponse" }, "description": "Returns the Model Monitoring alerts." }, "delete": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the ModelMonitor resource to be deleted. Format: `projects/{project}/locations/{location}/modelMonitords/{model_monitor}`", "location": "path" }, "force": { "type": "boolean", "description": "Optional. Force delete the model monitor with schedules.", "location": "query" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a ModelMonitor.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.modelMonitors.delete" } }, "resources": { "modelMonitoringJobs": { "methods": { "create": { "request": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJob" }, "id": "aiplatform.projects.locations.modelMonitors.modelMonitoringJobs.create", "path": "v1beta1/{+parent}/modelMonitoringJobs", "httpMethod": "POST", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/modelMonitoringJobs", "description": "Creates a ModelMonitoringJob.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJob" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "description": "Required. The parent of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMoniitors/{model_monitor}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", "required": true, "type": "string" }, "modelMonitoringJobId": { "description": "Optional. The ID to use for the Model Monitoring Job, which will become the final component of the model monitoring job resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ] }, "delete": { "description": "Deletes a ModelMonitoringJob.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/modelMonitoringJobs/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the model monitoring job to delete. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}/modelMonitoringJobs/{model_monitoring_job}`", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.modelMonitors.modelMonitoringJobs.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/modelMonitoringJobs/{modelMonitoringJobsId}" }, "list": { "parameters": { "readMask": { "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read", "type": "string" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "parent": { "location": "path", "description": "Required. The parent of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`", "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", "required": true, "type": "string" }, "filter": { "location": "query", "description": "The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists ModelMonitoringJobs. Callers may choose to read across multiple Monitors as per [AIP-159](https://google.aip.dev/159) by using '-' (the hyphen or dash character) as a wildcard character instead of modelMonitor id in the parent. Format `projects/{project_id}/locations/{location}/moodelMonitors/-/modelMonitoringJobs`", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListModelMonitoringJobsResponse" }, "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/modelMonitoringJobs", "id": "aiplatform.projects.locations.modelMonitors.modelMonitoringJobs.list", "path": "v1beta1/{+parent}/modelMonitoringJobs", "httpMethod": "GET" }, "get": { "parameters": { "name": { "description": "Required. The resource name of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}/modelMonitoringJobs/{model_monitoring_job}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/modelMonitoringJobs/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ModelMonitoringJob" }, "description": "Gets a ModelMonitoringJob.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/modelMonitoringJobs/{modelMonitoringJobsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.modelMonitors.modelMonitoringJobs.get" } } }, "operations": { "methods": { "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.modelMonitors.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/operations" }, "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.modelMonitors.operations.wait", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.modelMonitors.operations.get", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/operations/{operationsId}" }, "delete": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.modelMonitors.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.modelMonitors.operations.cancel", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/modelMonitors/{modelMonitorsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/modelMonitors/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "edgeDevices": { "resources": { "operations": { "methods": { "wait": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/edgeDevices/{edgeDevicesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.edgeDevices.operations.wait", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/edgeDevices/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/edgeDevices/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/edgeDevices/{edgeDevicesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.edgeDevices.operations.list" }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.edgeDevices.operations.delete", "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/edgeDevices/{edgeDevicesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/edgeDevices/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/edgeDevices/{edgeDevicesId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.edgeDevices.operations.cancel", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/edgeDevices/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/edgeDevices/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/edgeDevices/{edgeDevicesId}/operations/{operationsId}", "id": "aiplatform.projects.locations.edgeDevices.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" } } } } } } }, "modelGardenEula": { "methods": { "check": { "flatPath": "v1beta1/projects/{projectsId}/modelGardenEula:check", "id": "aiplatform.projects.modelGardenEula.check", "path": "v1beta1/{+parent}/modelGardenEula:check", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1CheckPublisherModelEulaAcceptanceRequest" }, "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+$", "required": true, "location": "path", "description": "Required. The project requesting access for named model. The format is `projects/{project}`." } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Checks the EULA acceptance status of a publisher model.", "response": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelEulaAcceptance" } }, "accept": { "parameters": { "parent": { "location": "path", "description": "Required. The project requesting access for named model. The format is `projects/{project}`.", "type": "string", "pattern": "^projects/[^/]+$", "required": true } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Accepts the EULA acceptance status of a publisher model.", "response": { "$ref": "GoogleCloudAiplatformV1beta1PublisherModelEulaAcceptance" }, "flatPath": "v1beta1/projects/{projectsId}/modelGardenEula:accept", "id": "aiplatform.projects.modelGardenEula.accept", "path": "v1beta1/{+parent}/modelGardenEula:accept", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1AcceptPublisherModelEulaRequest" } } } }, "publishers": { "resources": { "models": { "methods": { "enableModel": { "parameters": { "parent": { "description": "Required. The project requesting access for named model. Format: `projects/{project}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+$", "required": true }, "name": { "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}`", "location": "path" } }, "parameterOrder": [ "parent", "name" ], "description": "Enables model for the project if prerequisites are met (e.g. completed questionnaire and consents, or an active Private Offer).", "response": { "$ref": "GoogleCloudAiplatformV1beta1EnableModelResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/projects/{projectsId}/publishers/{publishersId}/models/{modelsId}:enableModel", "request": { "$ref": "GoogleCloudAiplatformV1beta1EnableModelRequest" }, "id": "aiplatform.projects.publishers.models.enableModel", "path": "v1beta1/{+parent}/{+name}:enableModel", "httpMethod": "POST" } } } } } } }, "evaluationMetrics": { "resources": { "operations": { "methods": { "list": { "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "type": "string", "pattern": "^evaluationMetrics/[^/]+$", "required": true, "location": "path", "description": "The name of the operation's parent resource." } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/evaluationMetrics/{evaluationMetricsId}/operations", "id": "aiplatform.evaluationMetrics.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "get": { "parameters": { "name": { "pattern": "^evaluationMetrics/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "flatPath": "v1beta1/evaluationMetrics/{evaluationMetricsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.evaluationMetrics.operations.get" }, "delete": { "flatPath": "v1beta1/evaluationMetrics/{evaluationMetricsId}/operations/{operationsId}", "id": "aiplatform.evaluationMetrics.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^evaluationMetrics/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "ragEngineConfig": { "resources": { "operations": { "methods": { "get": { "id": "aiplatform.ragEngineConfig.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/ragEngineConfig/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^ragEngineConfig/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ] }, "delete": { "id": "aiplatform.ragEngineConfig.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/ragEngineConfig/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^ragEngineConfig/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "id": "aiplatform.ragEngineConfig.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/ragEngineConfig/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "pattern": "^ragEngineConfig/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ] }, "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "pattern": "^ragEngineConfig$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ], "id": "aiplatform.ragEngineConfig.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/ragEngineConfig/operations" }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^ragEngineConfig/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.ragEngineConfig.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/ragEngineConfig/operations/{operationsId}:wait" } } } } }, "deploymentResourcePools": { "resources": { "operations": { "methods": { "wait": { "flatPath": "v1beta1/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.deploymentResourcePools.operations.wait", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^deploymentResourcePools/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "name": { "type": "string", "pattern": "^deploymentResourcePools/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "parameterOrder": [ "name" ], "id": "aiplatform.deploymentResourcePools.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/deploymentResourcePools/{deploymentResourcePoolsId}/operations" }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.deploymentResourcePools.operations.delete", "flatPath": "v1beta1/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "type": "string", "pattern": "^deploymentResourcePools/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.deploymentResourcePools.operations.cancel", "parameters": { "name": { "type": "string", "pattern": "^deploymentResourcePools/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "flatPath": "v1beta1/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}", "id": "aiplatform.deploymentResourcePools.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "pattern": "^deploymentResourcePools/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "notebookExecutionJobs": { "resources": { "operations": { "methods": { "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "type": "string", "pattern": "^notebookExecutionJobs/[^/]+$", "required": true, "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ], "id": "aiplatform.notebookExecutionJobs.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/notebookExecutionJobs/{notebookExecutionJobsId}/operations" }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.notebookExecutionJobs.operations.wait", "flatPath": "v1beta1/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ] }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.notebookExecutionJobs.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}" }, "cancel": { "parameters": { "name": { "type": "string", "pattern": "^notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.notebookExecutionJobs.operations.cancel" }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.notebookExecutionJobs.operations.delete", "flatPath": "v1beta1/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "reasoningEngines": { "methods": { "query": { "id": "aiplatform.reasoningEngines.query", "path": "v1beta1/{+name}:query", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}:query", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Queries using a reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1beta1QueryReasoningEngineResponse" }, "parameters": { "name": { "location": "path", "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "create": { "flatPath": "v1beta1/reasoningEngines", "id": "aiplatform.reasoningEngines.create", "path": "v1beta1/reasoningEngines", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngine" }, "parameters": { "parent": { "location": "query", "description": "Required. The resource name of the Location to create the ReasoningEngine in. Format: `projects/{project}/locations/{location}`", "type": "string" } }, "parameterOrder": [], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a reasoning engine.", "response": { "$ref": "GoogleLongrunningOperation" } }, "list": { "id": "aiplatform.reasoningEngines.list", "path": "v1beta1/reasoningEngines", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists reasoning engines in a location.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListReasoningEnginesResponse" }, "parameters": { "parent": { "type": "string", "location": "query", "description": "Required. The resource name of the Location to list the ReasoningEngines from. Format: `projects/{project}/locations/{location}`" }, "filter": { "type": "string", "location": "query", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160)." }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The standard list page size." }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token." } }, "parameterOrder": [] }, "patch": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}", "id": "aiplatform.reasoningEngines.patch", "path": "v1beta1/{+name}", "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngine" }, "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Identifier. The resource name of the ReasoningEngine. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "updateMask": { "description": "Optional. Mask specifying which fields to update.", "location": "query", "format": "google-fieldmask", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates a reasoning engine.", "response": { "$ref": "GoogleLongrunningOperation" } }, "delete": { "parameters": { "name": { "location": "path", "description": "Required. The name of the ReasoningEngine resource to be deleted. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true }, "force": { "description": "Optional. If set to true, child resources of this reasoning engine will also be deleted. Otherwise, the request will fail with FAILED_PRECONDITION error when the reasoning engine has undeleted child resources.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a reasoning engine.", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.reasoningEngines.delete" }, "executeCode": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}:executeCode", "path": "v1beta1/{+name}:executeCode", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.executeCode", "request": { "$ref": "GoogleCloudAiplatformV1beta1ExecuteCodeRequest" }, "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ExecuteCodeResponse" }, "description": "Executes code statelessly." }, "streamQuery": { "parameters": { "name": { "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Streams queries using a reasoning engine.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}:streamQuery", "request": { "$ref": "GoogleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest" }, "path": "v1beta1/{+name}:streamQuery", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.streamQuery" }, "get": { "id": "aiplatform.reasoningEngines.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ReasoningEngine" }, "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the ReasoningEngine resource. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "name" ] } }, "resources": { "memories": { "methods": { "delete": { "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/memories/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Memory to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Delete a Memory.", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.reasoningEngines.memories.delete" }, "create": { "id": "aiplatform.reasoningEngines.memories.create", "path": "v1beta1/{+parent}/memories", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1Memory" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Create a Memory.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "memoryId": { "type": "string", "description": "Optional. The user defined ID to use for memory, which will become the final component of the memory resource name. If not provided, Vertex AI will generate a value for this ID. This value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The first character must be a letter, and the last character must be a letter or number.", "location": "query" }, "parent": { "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the ReasoningEngine to create the Memory under. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "parent" ] }, "list": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories", "id": "aiplatform.reasoningEngines.memories.list", "path": "v1beta1/{+parent}/memories", "httpMethod": "GET", "parameters": { "pageSize": { "description": "Optional. The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "orderBy": { "type": "string", "location": "query", "description": "Optional. The standard list order by string. If not specified, the default order is `create_time desc`. If specified, the default sorting order of provided fields is ascending. More detail in [AIP-132](https://google.aip.dev/132). Supported fields: * `create_time` * `update_time`" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token." }, "parent": { "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the ReasoningEngine to list the Memories under. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "filter": { "type": "string", "location": "query", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). Supported fields: * `scope` (as a JSON string with equality match only) * `topics` (i.e. `topics.custom_memory_topic_label: \"example topic\" OR topics.managed_memory_topic: USER_PREFERENCES`)" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "List Memories.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListMemoriesResponse" } }, "purge": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Purge memories.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The resource name of the ReasoningEngine to purge memories from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1PurgeMemoriesRequest" }, "path": "v1beta1/{+parent}/memories:purge", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.memories.purge", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories:purge" }, "retrieve": { "path": "v1beta1/{+parent}/memories:retrieve", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.memories.retrieve", "request": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveMemoriesRequest" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories:retrieve", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveMemoriesResponse" }, "description": "Retrieve memories.", "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the ReasoningEngine to retrieve memories from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ] }, "ingestEvents": { "parameters": { "parent": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the ReasoningEngine to ingest events to. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Ingests events for a Memory Bank.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories:ingestEvents", "id": "aiplatform.reasoningEngines.memories.ingestEvents", "path": "v1beta1/{+parent}/memories:ingestEvents", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1IngestEventsRequest" } }, "retrieveProfiles": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories:retrieveProfiles", "request": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveProfilesRequest" }, "id": "aiplatform.reasoningEngines.memories.retrieveProfiles", "path": "v1beta1/{+parent}/memories:retrieveProfiles", "httpMethod": "POST", "parameters": { "parent": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the ReasoningEngine to retrieve profiles from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "parent" ], "description": "Retrieves profiles.", "response": { "$ref": "GoogleCloudAiplatformV1beta1RetrieveProfilesResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.memories.get", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Memory" }, "description": "Get a Memory.", "parameters": { "name": { "location": "path", "description": "Required. The resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "type": "string", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "generate": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Generate memories.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the ReasoningEngine to generate memories for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateMemoriesRequest" }, "path": "v1beta1/{+parent}/memories:generate", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.memories.generate", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories:generate" }, "patch": { "parameters": { "name": { "location": "path", "description": "Identifier. Represents the resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+$", "required": true, "type": "string" }, "updateMask": { "type": "string", "description": "Optional. Mask specifying which fields to update. Supported fields: * `display_name` * `description` * `fact`", "location": "query", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Update a Memory.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1Memory" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.reasoningEngines.memories.patch" }, "rollback": { "parameters": { "name": { "description": "Required. The resource name of the Memory to rollback. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "location": "path", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Rollback Memory to a specific revision.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}:rollback", "request": { "$ref": "GoogleCloudAiplatformV1beta1RollbackMemoryRequest" }, "path": "v1beta1/{+name}:rollback", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.memories.rollback" } }, "resources": { "revisions": { "methods": { "list": { "id": "aiplatform.reasoningEngines.memories.revisions.list", "path": "v1beta1/{+parent}/revisions", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/revisions", "description": "List Memory Revisions for a Memory.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListMemoryRevisionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "Optional. The standard list page size.", "type": "integer" }, "pageToken": { "location": "query", "description": "Optional. The standard list page token.", "type": "string" }, "parent": { "pattern": "^reasoningEngines/[^/]+/memories/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Memory to list revisions for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`" }, "filter": { "location": "query", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). Supported fields (equality match only): * `labels`", "type": "string" } }, "parameterOrder": [ "parent" ] }, "get": { "description": "Get a Memory Revision.", "response": { "$ref": "GoogleCloudAiplatformV1beta1MemoryRevision" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/memories/[^/]+/revisions/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Memory Revision to retrieve. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}/revisions/{revision}`", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.memories.revisions.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/revisions/{revisionsId}" } } }, "operations": { "methods": { "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.memories.operations.list", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "wait": { "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.memories.operations.wait", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ] }, "get": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.memories.operations.get" }, "cancel": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.memories.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}", "id": "aiplatform.reasoningEngines.memories.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" } } } } }, "operations": { "methods": { "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.reasoningEngines.operations.delete", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}" }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^reasoningEngines/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.operations.cancel", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}:cancel" }, "get": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}", "id": "aiplatform.reasoningEngines.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" } }, "wait": { "id": "aiplatform.reasoningEngines.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ] }, "list": { "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/operations", "id": "aiplatform.reasoningEngines.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" } } }, "examples": { "resources": { "operations": { "methods": { "get": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/examples/{examplesId}/operations/{operationsId}", "id": "aiplatform.reasoningEngines.examples.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^reasoningEngines/[^/]+/examples/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.reasoningEngines.examples.operations.delete", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/examples/{examplesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/examples/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/examples/{examplesId}/operations/{operationsId}:cancel", "id": "aiplatform.reasoningEngines.examples.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/examples/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/examples/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.examples.operations.wait", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/examples/{examplesId}/operations/{operationsId}:wait" } } } } }, "runtimeRevisions": { "methods": { "query": { "parameters": { "name": { "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Queries using a reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1beta1QueryReasoningEngineResponse" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}:query", "id": "aiplatform.reasoningEngines.runtimeRevisions.query", "path": "v1beta1/{+name}:query", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest" } }, "streamQuery": { "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Streams queries using a reasoning engine.", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}:streamQuery", "path": "v1beta1/{+name}:streamQuery", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.runtimeRevisions.streamQuery", "request": { "$ref": "GoogleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest" } } }, "resources": { "operations": { "methods": { "cancel": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.runtimeRevisions.operations.cancel" }, "delete": { "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/operations/{operationsId}", "id": "aiplatform.reasoningEngines.runtimeRevisions.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" }, "get": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/operations/{operationsId}", "id": "aiplatform.reasoningEngines.runtimeRevisions.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" } }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.runtimeRevisions.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/operations/{operationsId}:wait" }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.runtimeRevisions.operations.list", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "parameterOrder": [ "name" ] } } }, "a2a": { "methods": { "tasks": { "parameters": { "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" }, "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string" }, "a2aEndpoint": { "type": "string", "pattern": "^tasks$", "required": true, "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.tasks" }, "extendedAgentCard": { "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.extendedAgentCard", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/extendedAgentCard", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "type": "string", "pattern": "^extendedAgentCard$", "required": true, "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`" }, "name": { "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "card": { "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.card", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/card", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." }, "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "type": "string", "pattern": "^card$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ] } }, "resources": { "tasks": { "methods": { "subscribe": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks/{tasksId}:subscribe", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:subscribe", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.tasks.subscribe", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." }, "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123:subscribe`.", "location": "path", "pattern": "^tasks/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Stream get request for reasoning engine instance via the A2A stream get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "pushNotificationConfigs": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks/{tasksId}/pushNotificationConfigs", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.tasks.pushNotificationConfigs", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "historyLength": { "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "type": "string" }, "a2aEndpoint": { "pattern": "^tasks/[^/]+/pushNotificationConfigs$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:cancel", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.tasks.cancel", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks/{tasksId}:cancel", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "pattern": "^tasks/[^/]+$", "required": true, "type": "string", "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "location": "path" }, "name": { "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "a2aGetReasoningEngine": { "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.tasks.a2aGetReasoningEngine", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks/{tasksId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "parameters": { "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "pattern": "^tasks/[^/]+$", "required": true, "type": "string" }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." }, "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ] } }, "resources": { "pushNotificationConfigs": { "methods": { "a2aGetReasoningEngine": { "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "pattern": "^tasks/[^/]+/pushNotificationConfigs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`" }, "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true }, "historyLength": { "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.tasks.pushNotificationConfigs.a2aGetReasoningEngine", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/tasks/{tasksId}/pushNotificationConfigs/{pushNotificationConfigsId}" } } } } }, "v1": { "methods": { "card": { "parameters": { "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "type": "string", "pattern": "^v1/card$", "required": true }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/card", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.v1.card", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET" }, "tasks": { "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.v1.tasks", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks", "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "pattern": "^v1/tasks$", "required": true, "type": "string", "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`" }, "name": { "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "extendedAgentCard": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "parameters": { "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "pattern": "^v1/extendedAgentCard$", "required": true, "type": "string" }, "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "historyLength": { "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.v1.extendedAgentCard", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/extendedAgentCard" } }, "resources": { "message": { "methods": { "stream": { "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:stream", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.v1.message.stream", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/message:stream", "response": { "$ref": "GoogleApiHttpBody" }, "description": "Streams queries using a reasoning engine instance via the A2A streaming protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true }, "a2aEndpoint": { "pattern": "^v1/message$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. e.g., v1/message:stream.", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "send": { "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." }, "a2aEndpoint": { "type": "string", "pattern": "^v1/message$", "required": true, "location": "path", "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/message:send", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:send", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.v1.message.send", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } } }, "tasks": { "methods": { "cancel": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks/{tasksId}:cancel", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.v1.tasks.cancel", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:cancel", "httpMethod": "POST", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "parameters": { "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string" }, "a2aEndpoint": { "pattern": "^v1/tasks/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "a2aGetReasoningEngine": { "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "pattern": "^v1/tasks/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`" }, "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "historyLength": { "type": "string", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.v1.tasks.a2aGetReasoningEngine", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks/{tasksId}" }, "pushNotificationConfigs": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "parameters": { "a2aEndpoint": { "pattern": "^v1/tasks/[^/]+/pushNotificationConfigs$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" }, "historyLength": { "type": "string", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query" }, "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.v1.tasks.pushNotificationConfigs", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks/{tasksId}/pushNotificationConfigs" }, "subscribe": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Stream get request for reasoning engine instance via the A2A stream get protocol apis.", "response": { "$ref": "GoogleApiHttpBody" }, "parameters": { "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123:subscribe`.", "location": "path", "pattern": "^v1/tasks/[^/]+$", "required": true, "type": "string" }, "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." } }, "parameterOrder": [ "name", "a2aEndpoint" ], "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.v1.tasks.subscribe", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:subscribe", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks/{tasksId}:subscribe" } }, "resources": { "pushNotificationConfigs": { "methods": { "a2aGetReasoningEngine": { "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "type": "string", "pattern": "^v1/tasks/[^/]+/pushNotificationConfigs/[^/]+$", "required": true, "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" }, "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.v1.tasks.pushNotificationConfigs.a2aGetReasoningEngine", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/v1/tasks/{tasksId}/pushNotificationConfigs/{pushNotificationConfigsId}" } } } } } } }, "message": { "methods": { "stream": { "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." }, "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. e.g., v1/message:stream.", "location": "path", "pattern": "^message$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Streams queries using a reasoning engine instance via the A2A streaming protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/message:stream", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:stream", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.message.stream" }, "send": { "parameters": { "a2aEndpoint": { "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "location": "path", "type": "string", "pattern": "^message$", "required": true }, "name": { "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "required": true, "type": "string", "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}/a2a/message:send", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:send", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.runtimeRevisions.a2a.message.send" } } } } } } }, "feedbackEntries": { "resources": { "operations": { "methods": { "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^reasoningEngines/[^/]+/feedbackEntries/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.feedbackEntries.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/feedbackEntries/{feedbackEntriesId}/operations/{operationsId}:cancel" }, "delete": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/feedbackEntries/{feedbackEntriesId}/operations/{operationsId}", "id": "aiplatform.reasoningEngines.feedbackEntries.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/feedbackEntries/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/feedbackEntries/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.feedbackEntries.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/feedbackEntries/{feedbackEntriesId}/operations/{operationsId}" }, "wait": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/feedbackEntries/{feedbackEntriesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.feedbackEntries.operations.wait", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/feedbackEntries/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "pattern": "^reasoningEngines/[^/]+/feedbackEntries/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.feedbackEntries.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/feedbackEntries/{feedbackEntriesId}/operations" } } } } }, "sandboxEnvironmentSnapshots": { "methods": { "get": { "parameters": { "name": { "description": "Required. The resource name of the sandbox environment snapshot. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentSnapshots/{sandbox_environment_snapshot}`", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSnapshot" }, "description": "Gets details of the specific SandboxEnvironmentSnapshot.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.get" }, "list": { "path": "v1beta1/{+parent}/sandboxEnvironmentSnapshots", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.list", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentSnapshotsResponse" }, "description": "Lists SandboxEnvironmentSnapshots in a given reasoning engine.", "parameters": { "pageSize": { "type": "integer", "description": "Optional. The maximum number of SandboxEnvironmentSnapshots to return. The service may return fewer than this value. If unspecified, at most 100 SandboxEnvironmentSnapshots will be returned. Values above 100 will be coerced to 100.", "location": "query", "format": "int32" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token, received from a previous `ListSandboxEnvironmentSnapshots` call. Provide this to retrieve the subsequent page." }, "parent": { "description": "Required. The resource name of the reasoning engine to list sandbox environments from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" }, "filter": { "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ] }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.delete", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes the specific SandboxEnvironmentSnapshot.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The resource name of the SandboxEnvironmentSnapshot to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentSnapshots/{sandbox_environment_snapshot}`", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] } }, "resources": { "operations": { "methods": { "get": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.operations.get", "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.operations.delete", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}" }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.operations.cancel", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}:cancel" }, "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+$", "required": true, "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" } }, "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations" }, "wait": { "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ] } } } } }, "a2a": { "methods": { "tasks": { "parameters": { "historyLength": { "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "type": "string" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" }, "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "type": "string", "pattern": "^tasks$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/tasks", "id": "aiplatform.reasoningEngines.a2a.tasks", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET" }, "extendedAgentCard": { "id": "aiplatform.reasoningEngines.a2a.extendedAgentCard", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/extendedAgentCard", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "parameters": { "a2aEndpoint": { "pattern": "^extendedAgentCard$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." }, "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "card": { "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "pattern": "^card$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" }, "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "historyLength": { "type": "string", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.a2a.card", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/card" } }, "resources": { "message": { "methods": { "stream": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/message:stream", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:stream", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.a2a.message.stream", "parameters": { "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true }, "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. e.g., v1/message:stream.", "type": "string", "pattern": "^message$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Streams queries using a reasoning engine instance via the A2A streaming protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "send": { "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:send", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.a2a.message.send", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/message:send", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "parameters": { "a2aEndpoint": { "location": "path", "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "pattern": "^message$", "required": true, "type": "string" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ] } } }, "v1": { "methods": { "card": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/v1/card", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.a2a.v1.card", "parameters": { "a2aEndpoint": { "pattern": "^v1/card$", "required": true, "type": "string", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" }, "historyLength": { "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query", "type": "string" }, "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis." }, "tasks": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.a2a.v1.tasks", "parameters": { "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "pattern": "^v1/tasks$", "required": true, "type": "string" }, "historyLength": { "type": "string", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis." }, "extendedAgentCard": { "parameters": { "historyLength": { "type": "string", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "location": "query" }, "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true, "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "a2aEndpoint": { "type": "string", "pattern": "^v1/extendedAgentCard$", "required": true, "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/v1/extendedAgentCard", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.a2a.v1.extendedAgentCard" } }, "resources": { "message": { "methods": { "stream": { "parameters": { "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" }, "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. e.g., v1/message:stream.", "location": "path", "type": "string", "pattern": "^v1/message$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "response": { "$ref": "GoogleApiHttpBody" }, "description": "Streams queries using a reasoning engine instance via the A2A streaming protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/v1/message:stream", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:stream", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.a2a.v1.message.stream" }, "send": { "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:send", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.a2a.v1.message.send", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/v1/message:send", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." }, "a2aEndpoint": { "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "location": "path", "pattern": "^v1/message$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ] } } }, "tasks": { "methods": { "subscribe": { "id": "aiplatform.reasoningEngines.a2a.v1.tasks.subscribe", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:subscribe", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks/{tasksId}:subscribe", "description": "Stream get request for reasoning engine instance via the A2A stream get protocol apis.", "response": { "$ref": "GoogleApiHttpBody" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path" }, "a2aEndpoint": { "type": "string", "pattern": "^v1/tasks/[^/]+$", "required": true, "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123:subscribe`." } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "pushNotificationConfigs": { "id": "aiplatform.reasoningEngines.a2a.v1.tasks.pushNotificationConfigs", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks/{tasksId}/pushNotificationConfigs", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "parameters": { "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "pattern": "^v1/tasks/[^/]+/pushNotificationConfigs$", "required": true, "type": "string" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" }, "historyLength": { "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ] }, "cancel": { "parameters": { "a2aEndpoint": { "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "location": "path", "type": "string", "pattern": "^v1/tasks/[^/]+$", "required": true }, "name": { "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks/{tasksId}:cancel", "id": "aiplatform.reasoningEngines.a2a.v1.tasks.cancel", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:cancel", "httpMethod": "POST", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "a2aGetReasoningEngine": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks/{tasksId}", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.a2a.v1.tasks.a2aGetReasoningEngine", "parameters": { "a2aEndpoint": { "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path", "pattern": "^v1/tasks/[^/]+$", "required": true, "type": "string" }, "historyLength": { "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "type": "string" }, "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis." } }, "resources": { "pushNotificationConfigs": { "methods": { "a2aGetReasoningEngine": { "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "pattern": "^v1/tasks/[^/]+/pushNotificationConfigs/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`" }, "name": { "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." } }, "parameterOrder": [ "name", "a2aEndpoint" ], "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.a2a.v1.tasks.pushNotificationConfigs.a2aGetReasoningEngine", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/v1/tasks/{tasksId}/pushNotificationConfigs/{pushNotificationConfigsId}" } } } } } } }, "tasks": { "methods": { "subscribe": { "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true, "description": "Required. The full resource path of the reasoning engine, captured from the URL.", "location": "path" }, "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123:subscribe`.", "type": "string", "pattern": "^tasks/[^/]+$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "description": "Stream get request for reasoning engine instance via the A2A stream get protocol apis.", "response": { "$ref": "GoogleApiHttpBody" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/tasks/{tasksId}:subscribe", "id": "aiplatform.reasoningEngines.a2a.tasks.subscribe", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:subscribe", "httpMethod": "GET" }, "pushNotificationConfigs": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "parameters": { "a2aEndpoint": { "type": "string", "pattern": "^tasks/[^/]+/pushNotificationConfigs$", "required": true, "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "location": "path" }, "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "historyLength": { "type": "string", "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned." } }, "parameterOrder": [ "name", "a2aEndpoint" ], "id": "aiplatform.reasoningEngines.a2a.tasks.pushNotificationConfigs", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/tasks/{tasksId}/pushNotificationConfigs" }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Send post request for reasoning engine instance via the A2A post protocol apis.", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The full resource path of the reasoning engine, captured from the URL." }, "a2aEndpoint": { "location": "path", "description": "Required. The a2a endpoint path, captured from the URL. e.g., v1/message:send", "type": "string", "pattern": "^tasks/[^/]+$", "required": true } }, "parameterOrder": [ "name", "a2aEndpoint" ], "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}:cancel", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.a2a.tasks.cancel", "request": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/tasks/{tasksId}:cancel" }, "a2aGetReasoningEngine": { "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.a2a.tasks.a2aGetReasoningEngine", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/tasks/{tasksId}", "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "a2aEndpoint": { "pattern": "^tasks/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`" }, "historyLength": { "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "type": "string" }, "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "parameterOrder": [ "name", "a2aEndpoint" ] } }, "resources": { "pushNotificationConfigs": { "methods": { "a2aGetReasoningEngine": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/a2a/tasks/{tasksId}/pushNotificationConfigs/{pushNotificationConfigsId}", "path": "v1beta1/{+name}/a2a/{+a2aEndpoint}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.a2a.tasks.pushNotificationConfigs.a2aGetReasoningEngine", "parameters": { "historyLength": { "location": "query", "description": "Optional. The optional query parameter for the getTask endpoint. Mapped from \"?history_length=\". This indicates how many turns of history to return. If not set, the default value is 0, which means all the history will be returned.", "type": "string" }, "name": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The full resource path of the reasoning engine, captured from the URL. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "a2aEndpoint": { "location": "path", "description": "Required. The http endpoint extracted from the URL path. i.e. `v1/tasks/123`", "pattern": "^tasks/[^/]+/pushNotificationConfigs/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name", "a2aEndpoint" ], "response": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "description": "Get request for reasoning engine instance via the A2A get protocol apis.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } } } }, "sessions": { "methods": { "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes details of the specific Session.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "Required. The resource name of the session. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "location": "path", "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.sessions.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}" }, "get": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}", "id": "aiplatform.reasoningEngines.sessions.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "description": "Required. The resource name of the session. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Gets details of the specific Session.", "response": { "$ref": "GoogleCloudAiplatformV1beta1Session" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a new Session.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "sessionId": { "type": "string", "description": "Optional. The user defined ID to use for session, which will become the final component of the session resource name. If not provided, Vertex AI will generate a value for this ID. This value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The first and last characters must be a letter or number.", "location": "query" }, "parent": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the location to create the session in. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.reasoningEngines.sessions.create", "path": "v1beta1/{+parent}/sessions", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1beta1Session" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions" }, "list": { "parameters": { "orderBy": { "type": "string", "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `create_time` * `update_time` Example: `create_time desc`." }, "pageToken": { "location": "query", "description": "Optional. The next_page_token value returned from a previous list SessionService.ListSessions call.", "type": "string" }, "parent": { "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the location to list sessions from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "filter": { "location": "query", "description": "Optional. The standard list filter. Supported fields: * `display_name` * `user_id` * `labels` Example: `display_name=\"abc\"`, `user_id=\"123\"`, `labels.key=\"value\"`.", "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "Optional. The maximum number of sessions to return. The service may return fewer than this value. If unspecified, at most 100 sessions will be returned.", "type": "integer" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists Sessions in a given reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListSessionsResponse" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions", "id": "aiplatform.reasoningEngines.sessions.list", "path": "v1beta1/{+parent}/sessions", "httpMethod": "GET" }, "appendEvent": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1AppendEventResponse" }, "description": "Appends an event to a given session.", "parameters": { "name": { "description": "Required. The resource name of the session to append event to. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:appendEvent", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.sessions.appendEvent", "request": { "$ref": "GoogleCloudAiplatformV1beta1SessionEvent" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}:appendEvent" }, "patch": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}", "request": { "$ref": "GoogleCloudAiplatformV1beta1Session" }, "path": "v1beta1/{+name}", "httpMethod": "PATCH", "id": "aiplatform.reasoningEngines.sessions.patch", "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+$", "required": true, "description": "Identifier. The resource name of the session. Format: 'projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}'.", "location": "path" }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Optional. Field mask is used to control which fields get updated. If the mask is not present, all fields will be updated.", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1Session" }, "description": "Updates the specific Session.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "operations": { "methods": { "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.reasoningEngines.sessions.operations.delete", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.sessions.operations.cancel", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ] }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.sessions.operations.get", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}" }, "wait": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}:wait", "id": "aiplatform.reasoningEngines.sessions.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.sessions.operations.list", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations" } } }, "events": { "methods": { "list": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/events", "path": "v1beta1/{+parent}/events", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.sessions.events.list", "parameters": { "pageSize": { "type": "integer", "description": "Optional. The maximum number of events to return. The service may return fewer than this value. If unspecified, at most 100 events will be returned. These events are ordered by timestamp in ascending order.", "location": "query", "format": "int32" }, "orderBy": { "type": "string", "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `timestamp` Example: `timestamp desc`." }, "pageToken": { "location": "query", "description": "Optional. The next_page_token value returned from a previous list SessionService.ListEvents call.", "type": "string" }, "parent": { "type": "string", "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+$", "required": true, "description": "Required. The resource name of the session to list events from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "location": "path" }, "filter": { "description": "Optional. The standard list filter. Supported fields: * `timestamp` range (i.e. `timestamp\u003e=\"2025-01-31T11:30:00-04:00\"` where the timestamp is in RFC 3339 format) More detail in [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1beta1ListEventsResponse" }, "description": "Lists Events in a given session.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "sandboxEnvironments": { "methods": { "get": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}", "id": "aiplatform.reasoningEngines.sandboxEnvironments.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "Required. The resource name of the sandbox environment. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Gets details of the specific SandboxEnvironment.", "response": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironment" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "snapshot": { "path": "v1beta1/{+name}:snapshot", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.sandboxEnvironments.snapshot", "request": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentSnapshot" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:snapshot", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Snapshots the specific SandboxEnvironment resource and creates a SandboxEnvironmentSnapshot resource.", "parameters": { "name": { "description": "Required. The resource name of the sandbox environment to snapshot. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`.", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes the specific SandboxEnvironment.", "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true, "description": "Required. The resource name of the SandboxEnvironment to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.reasoningEngines.sandboxEnvironments.delete", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}" }, "execute": { "request": { "$ref": "GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest" }, "id": "aiplatform.reasoningEngines.sandboxEnvironments.execute", "path": "v1beta1/{+name}:execute", "httpMethod": "POST", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:execute", "description": "Executes using a sandbox environment.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "location": "path" } }, "parameterOrder": [ "name" ] }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists SandboxEnvironments in a given reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentsResponse" }, "parameters": { "parent": { "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the reasoning engine to list sandbox environments from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "filter": { "type": "string", "location": "query", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160)." }, "pageSize": { "location": "query", "format": "int32", "description": "Optional. The maximum number of SandboxEnvironments to return. The service may return fewer than this value. If unspecified, at most 100 SandboxEnvironments will be returned.", "type": "integer" }, "pageToken": { "location": "query", "description": "Optional. The standard list page token, received from a previous `ListSandboxEnvironments` call. Provide this to retrieve the subsequent page.", "type": "string" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.reasoningEngines.sandboxEnvironments.list", "path": "v1beta1/{+parent}/sandboxEnvironments", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments" }, "create": { "request": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironment" }, "path": "v1beta1/{+parent}/sandboxEnvironments", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.sandboxEnvironments.create", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates a SandboxEnvironment in a given reasoning engine.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the reasoning engine to create the SandboxEnvironment in. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`.", "location": "path" } }, "parameterOrder": [ "parent" ] } }, "resources": { "operations": { "methods": { "list": { "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.sandboxEnvironments.operations.list" }, "wait": { "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}:wait", "id": "aiplatform.reasoningEngines.sandboxEnvironments.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "get": { "id": "aiplatform.reasoningEngines.sandboxEnvironments.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.sandboxEnvironments.operations.cancel", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}:cancel" }, "delete": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}", "id": "aiplatform.reasoningEngines.sandboxEnvironments.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE" } } } } }, "sandboxEnvironmentTemplates": { "methods": { "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes the specific SandboxEnvironmentTemplate.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "Required. The resource name of the SandboxEnvironmentTemplate to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentTemplates/{sandbox_environment_template}`", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}" }, "create": { "description": "Creates a SandboxEnvironmentTemplate in a given reasoning engine.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the reasoning engine to create the SandboxEnvironmentTemplate in. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`.", "location": "path" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplate" }, "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.create", "path": "v1beta1/{+parent}/sandboxEnvironmentTemplates", "httpMethod": "POST", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.get", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}", "response": { "$ref": "GoogleCloudAiplatformV1beta1SandboxEnvironmentTemplate" }, "description": "Gets details of the specific SandboxEnvironmentTemplate.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The resource name of the sandbox environment template. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentTemplates/{sandbox_environment_template}`", "location": "path", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "list": { "response": { "$ref": "GoogleCloudAiplatformV1beta1ListSandboxEnvironmentTemplatesResponse" }, "description": "Lists SandboxEnvironmentTemplates in a given reasoning engine.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The maximum number of SandboxEnvironmentTemplates to return. The service may return fewer than this value. If unspecified, at most 100 SandboxEnvironmentTemplates will be returned." }, "pageToken": { "description": "Optional. The standard list page token, received from a previous `ListSandboxEnvironmentTemplates` call. Provide this to retrieve the subsequent page.", "location": "query", "type": "string" }, "parent": { "location": "path", "description": "Required. The resource name of the reasoning engine to list sandbox environment templates from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" }, "filter": { "location": "query", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "type": "string" } }, "parameterOrder": [ "parent" ], "path": "v1beta1/{+parent}/sandboxEnvironmentTemplates", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.list", "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates" } }, "resources": { "operations": { "methods": { "list": { "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.operations.list" }, "wait": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.operations.wait", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "get": { "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}", "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "delete": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}", "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "cancel": { "flatPath": "v1beta1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}:cancel", "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } } } }, "extensionControllers": { "resources": { "operations": { "methods": { "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.extensionControllers.operations.list", "flatPath": "v1beta1/extensionControllers/{extensionControllersId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^extensionControllers/[^/]+$", "required": true }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ] }, "wait": { "parameters": { "name": { "pattern": "^extensionControllers/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/extensionControllers/{extensionControllersId}/operations/{operationsId}:wait", "id": "aiplatform.extensionControllers.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "get": { "flatPath": "v1beta1/extensionControllers/{extensionControllersId}/operations/{operationsId}", "id": "aiplatform.extensionControllers.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^extensionControllers/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" } }, "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.extensionControllers.operations.cancel", "flatPath": "v1beta1/extensionControllers/{extensionControllersId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^extensionControllers/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^extensionControllers/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.extensionControllers.operations.delete", "flatPath": "v1beta1/extensionControllers/{extensionControllersId}/operations/{operationsId}" } } } } }, "dataLabelingJobs": { "resources": { "operations": { "methods": { "list": { "id": "aiplatform.dataLabelingJobs.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/dataLabelingJobs/{dataLabelingJobsId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "name": { "pattern": "^dataLabelingJobs/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ] }, "wait": { "flatPath": "v1beta1/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.dataLabelingJobs.operations.wait", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^dataLabelingJobs/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "get": { "id": "aiplatform.dataLabelingJobs.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^dataLabelingJobs/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^dataLabelingJobs/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.dataLabelingJobs.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}" }, "cancel": { "flatPath": "v1beta1/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.dataLabelingJobs.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^dataLabelingJobs/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." } } } } }, "modelMonitors": { "resources": { "operations": { "methods": { "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^modelMonitors/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.modelMonitors.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/modelMonitors/{modelMonitorsId}/operations/{operationsId}:cancel" }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^modelMonitors/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "id": "aiplatform.modelMonitors.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/modelMonitors/{modelMonitorsId}/operations/{operationsId}" }, "get": { "flatPath": "v1beta1/modelMonitors/{modelMonitorsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.modelMonitors.operations.get", "parameters": { "name": { "pattern": "^modelMonitors/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "parameters": { "name": { "pattern": "^modelMonitors/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/modelMonitors/{modelMonitorsId}/operations/{operationsId}:wait", "id": "aiplatform.modelMonitors.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "name": { "pattern": "^modelMonitors/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.modelMonitors.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/modelMonitors/{modelMonitorsId}/operations" } } } } }, "semanticGovernancePolicies": { "resources": { "operations": { "methods": { "wait": { "flatPath": "v1beta1/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}:wait", "id": "aiplatform.semanticGovernancePolicies.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "type": "string", "pattern": "^semanticGovernancePolicies/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" } }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.semanticGovernancePolicies.operations.list", "flatPath": "v1beta1/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "pattern": "^semanticGovernancePolicies/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^semanticGovernancePolicies/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.semanticGovernancePolicies.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}:cancel" }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^semanticGovernancePolicies/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.semanticGovernancePolicies.operations.delete", "flatPath": "v1beta1/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}" }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^semanticGovernancePolicies/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.semanticGovernancePolicies.operations.get", "flatPath": "v1beta1/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}" } } } } }, "edgeDevices": { "resources": { "operations": { "methods": { "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.edgeDevices.operations.get", "flatPath": "v1beta1/edgeDevices/{edgeDevicesId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^edgeDevices/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1beta1/edgeDevices/{edgeDevicesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.edgeDevices.operations.delete", "parameters": { "name": { "type": "string", "pattern": "^edgeDevices/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." }, "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.edgeDevices.operations.cancel", "flatPath": "v1beta1/edgeDevices/{edgeDevicesId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "pattern": "^edgeDevices/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ] }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^edgeDevices/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.edgeDevices.operations.list", "flatPath": "v1beta1/edgeDevices/{edgeDevicesId}/operations" }, "wait": { "parameters": { "name": { "pattern": "^edgeDevices/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/edgeDevices/{edgeDevicesId}/operations/{operationsId}:wait", "id": "aiplatform.edgeDevices.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" } } } } }, "semanticGovernancePolicyEngine": { "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^semanticGovernancePolicyEngine/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/semanticGovernancePolicyEngine/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.semanticGovernancePolicyEngine.operations.delete" }, "cancel": { "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.semanticGovernancePolicyEngine.operations.cancel", "flatPath": "v1beta1/semanticGovernancePolicyEngine/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^semanticGovernancePolicyEngine/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "get": { "id": "aiplatform.semanticGovernancePolicyEngine.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/semanticGovernancePolicyEngine/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "pattern": "^semanticGovernancePolicyEngine/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "wait": { "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^semanticGovernancePolicyEngine/operations/[^/]+$", "required": true }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1beta1/semanticGovernancePolicyEngine/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.semanticGovernancePolicyEngine.operations.wait" }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.semanticGovernancePolicyEngine.operations.list", "flatPath": "v1beta1/semanticGovernancePolicyEngine/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "name": { "pattern": "^semanticGovernancePolicyEngine$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "indexEndpoints": { "resources": { "operations": { "methods": { "cancel": { "parameters": { "name": { "type": "string", "pattern": "^indexEndpoints/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1beta1/indexEndpoints/{indexEndpointsId}/operations/{operationsId}:cancel", "id": "aiplatform.indexEndpoints.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "flatPath": "v1beta1/indexEndpoints/{indexEndpointsId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.indexEndpoints.operations.delete", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^indexEndpoints/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^indexEndpoints/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/indexEndpoints/{indexEndpointsId}/operations/{operationsId}", "id": "aiplatform.indexEndpoints.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET" }, "wait": { "flatPath": "v1beta1/indexEndpoints/{indexEndpointsId}/operations/{operationsId}:wait", "id": "aiplatform.indexEndpoints.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^indexEndpoints/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" } }, "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^indexEndpoints/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.indexEndpoints.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1beta1/indexEndpoints/{indexEndpointsId}/operations" } } } } }, "solvers": { "resources": { "operations": { "methods": { "delete": { "flatPath": "v1beta1/solvers/{solversId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.solvers.operations.delete", "parameters": { "name": { "type": "string", "pattern": "^solvers/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." }, "get": { "flatPath": "v1beta1/solvers/{solversId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.solvers.operations.get", "parameters": { "name": { "type": "string", "pattern": "^solvers/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.solvers.operations.list", "flatPath": "v1beta1/solvers/{solversId}/operations", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "name": { "pattern": "^solvers/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "exampleStores": { "resources": { "operations": { "methods": { "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^exampleStores/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/exampleStores/{exampleStoresId}/operations/{operationsId}:cancel", "id": "aiplatform.exampleStores.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "flatPath": "v1beta1/exampleStores/{exampleStoresId}/operations/{operationsId}", "id": "aiplatform.exampleStores.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "pattern": "^exampleStores/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" } }, "get": { "flatPath": "v1beta1/exampleStores/{exampleStoresId}/operations/{operationsId}", "id": "aiplatform.exampleStores.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "parameters": { "name": { "type": "string", "pattern": "^exampleStores/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" } }, "wait": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^exampleStores/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "id": "aiplatform.exampleStores.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "flatPath": "v1beta1/exampleStores/{exampleStoresId}/operations/{operationsId}:wait" }, "list": { "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.exampleStores.operations.list", "flatPath": "v1beta1/exampleStores/{exampleStoresId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "pattern": "^exampleStores/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ] } } } } }, "schedules": { "resources": { "operations": { "methods": { "wait": { "parameters": { "name": { "pattern": "^schedules/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1beta1/schedules/{schedulesId}/operations/{operationsId}:wait", "id": "aiplatform.schedules.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST" }, "list": { "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "type": "string", "pattern": "^schedules/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1beta1/schedules/{schedulesId}/operations", "id": "aiplatform.schedules.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET" }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.schedules.operations.delete", "flatPath": "v1beta1/schedules/{schedulesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^schedules/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "pattern": "^schedules/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "id": "aiplatform.schedules.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/schedules/{schedulesId}/operations/{operationsId}:cancel" }, "get": { "path": "v1beta1/{+name}", "httpMethod": "GET", "id": "aiplatform.schedules.operations.get", "flatPath": "v1beta1/schedules/{schedulesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^schedules/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "persistentResources": { "resources": { "operations": { "methods": { "get": { "id": "aiplatform.persistentResources.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/persistentResources/{persistentResourcesId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^persistentResources/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "pattern": "^persistentResources/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "id": "aiplatform.persistentResources.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1beta1/persistentResources/{persistentResourcesId}/operations/{operationsId}:cancel" }, "delete": { "flatPath": "v1beta1/persistentResources/{persistentResourcesId}/operations/{operationsId}", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.persistentResources.operations.delete", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^persistentResources/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^persistentResources/[^/]+$", "required": true }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1beta1/persistentResources/{persistentResourcesId}/operations", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.persistentResources.operations.list" }, "wait": { "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^persistentResources/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1beta1/persistentResources/{persistentResourcesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.persistentResources.operations.wait" } } } } }, "apps": { "resources": { "operations": { "methods": { "get": { "id": "aiplatform.apps.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/apps/{appsId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^apps/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1beta1/apps/{appsId}/operations/{operationsId}:cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.apps.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "pattern": "^apps/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." }, "delete": { "path": "v1beta1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.apps.operations.delete", "flatPath": "v1beta1/apps/{appsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^apps/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "list": { "flatPath": "v1beta1/apps/{appsId}/operations", "id": "aiplatform.apps.operations.list", "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^apps/[^/]+$", "required": true }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "wait": { "flatPath": "v1beta1/apps/{appsId}/operations/{operationsId}:wait", "id": "aiplatform.apps.operations.wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "parameters": { "name": { "type": "string", "pattern": "^apps/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "indexes": { "resources": { "operations": { "methods": { "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^indexes/[^/]+$", "required": true, "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "parameterOrder": [ "name" ], "path": "v1beta1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.indexes.operations.list", "flatPath": "v1beta1/indexes/{indexesId}/operations" }, "wait": { "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^indexes/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1beta1/indexes/{indexesId}/operations/{operationsId}:wait", "path": "v1beta1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.indexes.operations.wait" }, "get": { "id": "aiplatform.indexes.operations.get", "path": "v1beta1/{+name}", "httpMethod": "GET", "flatPath": "v1beta1/indexes/{indexesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^indexes/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ] }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^indexes/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.indexes.operations.delete", "path": "v1beta1/{+name}", "httpMethod": "DELETE", "flatPath": "v1beta1/indexes/{indexesId}/operations/{operationsId}" }, "cancel": { "flatPath": "v1beta1/indexes/{indexesId}/operations/{operationsId}:cancel", "id": "aiplatform.indexes.operations.cancel", "path": "v1beta1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^indexes/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } } }, "ownerDomain": "google.com", "protocol": "rest", "batchPath": "batch", "canonicalName": "Aiplatform", "description": "Train high-quality custom machine learning models with minimal machine learning expertise and effort.", "servicePath": "", "version": "v1beta1", "basePath": "", "version_module": true, "name": "aiplatform", "documentationLink": "https://cloud.google.com/vertex-ai/", "revision": "20260414", "endpoints": [ { "endpointUrl": "https://africa-south1-aiplatform.googleapis.com/", "location": "africa-south1", "description": "Locational Endpoint" }, { "endpointUrl": "https://asia-east1-aiplatform.googleapis.com/", "location": "asia-east1", "description": "Locational Endpoint" }, { "endpointUrl": "https://asia-east2-aiplatform.googleapis.com/", "location": "asia-east2", "description": "Locational Endpoint" }, { "endpointUrl": "https://asia-northeast1-aiplatform.googleapis.com/", "location": "asia-northeast1", "description": "Locational Endpoint" }, { "endpointUrl": "https://asia-northeast2-aiplatform.googleapis.com/", "location": "asia-northeast2", "description": "Locational Endpoint" }, { "endpointUrl": "https://asia-northeast3-aiplatform.googleapis.com/", "location": "asia-northeast3", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://asia-south1-aiplatform.googleapis.com/", "location": "asia-south1" }, { "endpointUrl": "https://asia-south2-aiplatform.googleapis.com/", "location": "asia-south2", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://asia-southeast1-aiplatform.googleapis.com/", "location": "asia-southeast1" }, { "endpointUrl": "https://asia-southeast2-aiplatform.googleapis.com/", "location": "asia-southeast2", "description": "Locational Endpoint" }, { "endpointUrl": "https://australia-southeast1-aiplatform.googleapis.com/", "location": "australia-southeast1", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://australia-southeast2-aiplatform.googleapis.com/", "location": "australia-southeast2" }, { "description": "Locational Endpoint", "endpointUrl": "https://europe-central2-aiplatform.googleapis.com/", "location": "europe-central2" }, { "description": "Locational Endpoint", "endpointUrl": "https://europe-north1-aiplatform.googleapis.com/", "location": "europe-north1" }, { "description": "Locational Endpoint", "endpointUrl": "https://europe-north2-aiplatform.googleapis.com/", "location": "europe-north2" }, { "endpointUrl": "https://europe-southwest1-aiplatform.googleapis.com/", "location": "europe-southwest1", "description": "Locational Endpoint" }, { "endpointUrl": "https://europe-west1-aiplatform.googleapis.com/", "location": "europe-west1", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://europe-west10-aiplatform.googleapis.com/", "location": "europe-west10" }, { "description": "Locational Endpoint", "endpointUrl": "https://europe-west15-aiplatform.googleapis.com/", "location": "europe-west15" }, { "endpointUrl": "https://europe-west2-aiplatform.googleapis.com/", "location": "europe-west2", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://europe-west3-aiplatform.googleapis.com/", "location": "europe-west3" }, { "endpointUrl": "https://europe-west4-aiplatform.googleapis.com/", "location": "europe-west4", "description": "Locational Endpoint" }, { "endpointUrl": "https://europe-west6-aiplatform.googleapis.com/", "location": "europe-west6", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://europe-west8-aiplatform.googleapis.com/", "location": "europe-west8" }, { "description": "Locational Endpoint", "endpointUrl": "https://europe-west9-aiplatform.googleapis.com/", "location": "europe-west9" }, { "description": "Locational Endpoint", "endpointUrl": "https://europe-west12-aiplatform.googleapis.com/", "location": "europe-west12" }, { "description": "Locational Endpoint", "endpointUrl": "https://me-central1-aiplatform.googleapis.com/", "location": "me-central1" }, { "description": "Locational Endpoint", "endpointUrl": "https://me-central2-aiplatform.googleapis.com/", "location": "me-central2" }, { "endpointUrl": "https://me-west1-aiplatform.googleapis.com/", "location": "me-west1", "description": "Locational Endpoint" }, { "endpointUrl": "https://northamerica-northeast1-aiplatform.googleapis.com/", "location": "northamerica-northeast1", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://northamerica-northeast2-aiplatform.googleapis.com/", "location": "northamerica-northeast2" }, { "description": "Locational Endpoint", "endpointUrl": "https://southamerica-east1-aiplatform.googleapis.com/", "location": "southamerica-east1" }, { "endpointUrl": "https://southamerica-west1-aiplatform.googleapis.com/", "location": "southamerica-west1", "description": "Locational Endpoint" }, { "endpointUrl": "https://us-central1-aiplatform.googleapis.com/", "location": "us-central1", "description": "Locational Endpoint" }, { "endpointUrl": "https://us-central2-aiplatform.googleapis.com/", "location": "us-central2", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://us-east1-aiplatform.googleapis.com/", "location": "us-east1" }, { "endpointUrl": "https://us-east4-aiplatform.googleapis.com/", "location": "us-east4", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://us-east7-aiplatform.googleapis.com/", "location": "us-east7" }, { "endpointUrl": "https://us-south1-aiplatform.googleapis.com/", "location": "us-south1", "description": "Locational Endpoint" }, { "endpointUrl": "https://us-west1-aiplatform.googleapis.com/", "location": "us-west1", "description": "Locational Endpoint" }, { "endpointUrl": "https://us-west2-aiplatform.googleapis.com/", "location": "us-west2", "description": "Locational Endpoint" }, { "endpointUrl": "https://us-west3-aiplatform.googleapis.com/", "location": "us-west3", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://us-west4-aiplatform.googleapis.com/", "location": "us-west4" }, { "endpointUrl": "https://us-east5-aiplatform.googleapis.com/", "location": "us-east5", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://us-west8-aiplatform.googleapis.com/", "location": "us-west8" }, { "endpointUrl": "https://aiplatform.us.rep.googleapis.com/", "location": "us", "description": "Regional Endpoint" }, { "description": "Regional Endpoint", "endpointUrl": "https://aiplatform.eu.rep.googleapis.com/", "location": "eu" } ] }