{ "canonicalName": "Aiplatform", "documentationLink": "https://cloud.google.com/vertex-ai/", "mtlsRootUrl": "https://aiplatform.mtls.googleapis.com/", "ownerDomain": "google.com", "revision": "20261012", "icons": { "x32": "http://www.google.com/images/icons/product/search-32.gif", "x16": "http://www.google.com/images/icons/product/search-16.gif" }, "basePath": "", "schemas": { "GenaiVertexV1AudioResponseFormat": { "description": "Configuration for audio output format.", "properties": { "delivery": { "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "Audio data is returned inline in the response.", "Audio data is returned as a URI." ], "enum": [ "DELIVERY_UNSPECIFIED", "INLINE", "URI" ], "description": "The delivery mode for the audio output." }, "sampleRate": { "format": "int32", "description": "Sample rate in Hz.", "type": "integer" }, "mimeType": { "enum": [ "TYPE_UNSPECIFIED", "TYPE_MP3", "TYPE_OGG_OPUS", "TYPE_L16", "TYPE_WAV", "TYPE_ALAW", "TYPE_MULAW" ], "description": "The MIME type of the audio output.", "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "MP3 audio format.", "OGG Opus audio format.", "Raw PCM (L16) audio format.", "WAV audio format.", "A-law audio format.", "Mu-law audio format." ] }, "bitRate": { "format": "int32", "description": "Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).", "type": "integer" } }, "type": "object", "id": "GenaiVertexV1AudioResponseFormat" }, "GoogleCloudAiplatformV1MigrateResourceRequest": { "type": "object", "properties": { "migrateAutomlDatasetConfig": { "description": "Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset.", "$ref": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlDatasetConfig" }, "migrateAutomlModelConfig": { "description": "Config for migrating Model in automl.googleapis.com to Vertex AI's Model.", "$ref": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlModelConfig" }, "migrateDataLabelingDatasetConfig": { "description": "Deprecated: Data labeling service is shut down. Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset.", "$ref": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfig", "deprecated": true }, "migrateMlEngineModelVersionConfig": { "description": "Config for migrating Version in ml.googleapis.com to Vertex AI's Model.", "$ref": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateMlEngineModelVersionConfig" } }, "description": "Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.", "id": "GoogleCloudAiplatformV1MigrateResourceRequest" }, "GoogleCloudAiplatformV1RawPredictRequest": { "type": "object", "id": "GoogleCloudAiplatformV1RawPredictRequest", "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.", "$ref": "GoogleApiHttpBody" } }, "description": "Request message for PredictionService.RawPredict." }, "GoogleCloudAiplatformV1AggregationOutput": { "properties": { "aggregationResults": { "items": { "$ref": "GoogleCloudAiplatformV1AggregationResult" }, "description": "One AggregationResult per metric.", "type": "array" }, "dataset": { "$ref": "GoogleCloudAiplatformV1EvaluationDataset", "description": "The dataset used for evaluation & aggregation." } }, "type": "object", "id": "GoogleCloudAiplatformV1AggregationOutput", "description": "The aggregation result for the entire dataset and all metrics." }, "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInput": { "properties": { "instance": { "description": "Required. Question answering helpfulness instance.", "$ref": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInstance" }, "metricSpec": { "description": "Required. Spec for question answering helpfulness score metric.", "$ref": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessSpec" } }, "id": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInput", "description": "Input for question answering helpfulness metric.", "type": "object" }, "GoogleCloudAiplatformV1SchemaTextPromptDatasetMetadata": { "description": "The metadata of Datasets that contain Text Prompt data.", "id": "GoogleCloudAiplatformV1SchemaTextPromptDatasetMetadata", "type": "object", "properties": { "hasPromptVariable": { "type": "boolean", "description": "Whether the prompt dataset has prompt variable." }, "systemInstruction": { "type": "string", "description": "The content of the prompt dataset system instruction." }, "topP": { "format": "float", "description": "Top P value set when the dataset was saved. Given topK tokens for decoding, top candidates will be selected until the sum of their probabilities is topP.", "type": "number" }, "groundingConfig": { "description": "Grounding checking configuration.", "$ref": "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfig" }, "promptApiSchema": { "description": "The API schema of the prompt to support both UI and SDK usages.", "$ref": "GoogleCloudAiplatformV1SchemaPromptApiSchema" }, "gcsUri": { "type": "string", "description": "The Google Cloud Storage URI that stores the prompt data." }, "text": { "type": "string", "description": "The content of the prompt dataset." }, "stopSequences": { "type": "array", "description": "Customized stop sequences.", "items": { "type": "string" } }, "promptType": { "description": "Type of the prompt dataset.", "type": "string" }, "maxOutputTokens": { "description": "Value of the maximum number of tokens generated set when the dataset was saved.", "type": "string", "format": "int64" }, "seedEnabled": { "type": "boolean", "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." }, "temperature": { "description": "Temperature value used for sampling set when the dataset was saved. This value is used to tune the degree of randomness.", "type": "number", "format": "float" }, "systemInstructionGcsUri": { "type": "string", "description": "The Google Cloud Storage URI that stores the system instruction, starting with gs://." }, "note": { "description": "User-created prompt note. Note size limit is 2KB.", "type": "string" }, "seedValue": { "type": "string", "description": "The actual value of the seed.", "format": "int64" }, "candidateCount": { "description": "Number of candidates.", "format": "int64", "type": "string" }, "topK": { "type": "string", "format": "int64", "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." }, "logprobs": { "description": "Whether or not the user has enabled logit probabilities in the model parameters.", "type": "boolean" } } }, "GoogleCloudAiplatformV1ExactMatchSpec": { "type": "object", "description": "Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0.", "id": "GoogleCloudAiplatformV1ExactMatchSpec", "properties": {} }, "GoogleCloudAiplatformV1UserScenario": { "properties": { "testCaseTitle": { "type": "string", "description": "Represents a short 3-5 word title for eval test case." }, "conversationPlan": { "description": "Conversation plan to drive multi-turn agent run and get simulated agent eval dataset.", "type": "string" }, "startingPrompt": { "description": "Starting prompt for the conversation between simulated user and agent under the test.", "type": "string" } }, "type": "object", "description": "Output of user scenario generation.", "id": "GoogleCloudAiplatformV1UserScenario" }, "GoogleCloudAiplatformV1GoogleMaps": { "type": "object", "description": "Tool to retrieve public maps data for grounding, powered by Google.", "id": "GoogleCloudAiplatformV1GoogleMaps", "properties": { "enableWidget": { "type": "boolean", "description": "Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.", "deprecated": true }, "groundingTypes": { "$ref": "GoogleCloudAiplatformV1GoogleMapsGroundingTypes", "description": "Optional. Specifies the types of Google Maps grounding to enable. Defaults to `places` when unset." } } }, "GoogleCloudAiplatformV1CreateTensorboardOperationMetadata": { "properties": { "genericMetadata": { "description": "Operation metadata for Tensorboard.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1CreateTensorboardOperationMetadata", "type": "object", "description": "Details of operations that perform create Tensorboard." }, "GoogleCloudAiplatformV1ListPersistentResourcesResponse": { "id": "GoogleCloudAiplatformV1ListPersistentResourcesResponse", "type": "object", "properties": { "persistentResources": { "items": { "$ref": "GoogleCloudAiplatformV1PersistentResource" }, "type": "array" }, "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListPersistentResourcesRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for PersistentResourceService.ListPersistentResources" }, "GoogleCloudAiplatformV1RagManagedDbConfig": { "description": "Configuration message for RagManagedDb used by RagEngine.", "properties": { "serverless": { "description": "Sets the backend to be the serverless mode offered by RAG Engine.", "$ref": "GoogleCloudAiplatformV1RagManagedDbConfigServerless" }, "basic": { "description": "Deprecated: Use `mode` instead to set the tier under Spanner. Sets the RagManagedDb to the Basic tier.", "$ref": "GoogleCloudAiplatformV1RagManagedDbConfigBasic", "deprecated": true }, "spanner": { "$ref": "GoogleCloudAiplatformV1RagManagedDbConfigSpanner", "description": "Sets the RAG Engine backend to be RagManagedDb, built on top of Spanner. NOTE: This is the default mode (w/ Basic Tier) if not explicitly chosen." }, "unprovisioned": { "deprecated": true, "description": "Deprecated: Use `mode` instead to set the tier under Spanner. Sets the RagManagedDb to the Unprovisioned tier.", "$ref": "GoogleCloudAiplatformV1RagManagedDbConfigUnprovisioned" }, "scaled": { "description": "Deprecated: Use `mode` instead to set the tier under Spanner. Sets the RagManagedDb to the Scaled tier.", "$ref": "GoogleCloudAiplatformV1RagManagedDbConfigScaled", "deprecated": true } }, "type": "object", "id": "GoogleCloudAiplatformV1RagManagedDbConfig" }, "GoogleCloudAiplatformV1ListNotebookRuntimeTemplatesResponse": { "id": "GoogleCloudAiplatformV1ListNotebookRuntimeTemplatesResponse", "type": "object", "properties": { "notebookRuntimeTemplates": { "type": "array", "description": "List of NotebookRuntimeTemplates in the requested page.", "items": { "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplate" } }, "nextPageToken": { "type": "string", "description": "A token to retrieve next page of results. Pass to ListNotebookRuntimeTemplatesRequest.page_token to obtain that page." } }, "description": "Response message for NotebookService.ListNotebookRuntimeTemplates." }, "GoogleCloudAiplatformV1PredefinedSplit": { "id": "GoogleCloudAiplatformV1PredefinedSplit", "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" } }, "description": "Assigns input data to training, validation, and test sets based on the value of a provided key. Supported only for tabular Datasets.", "type": "object" }, "GoogleCloudAiplatformV1SchemaPromptSpecAppBuilderData": { "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" }, "framework": { "enumDescriptions": [ "Unspecified framework.", "React framework.", "Angular framework." ], "description": "Optional. Framework used to build the application.", "enum": [ "FRAMEWORK_UNSPECIFIED", "REACT", "ANGULAR" ], "type": "string" }, "linkedResources": { "type": "array", "description": "Linked resources attached to the application by the user.", "items": { "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecAppBuilderDataLinkedResource" } }, "deployedRegions": { "type": "array", "items": { "type": "string" }, "description": "Optional. The Cloud Run regions in which the application is currently deployed. Used to rediscover and redeploy the app in the regions it already runs in, which may differ from the prompt's location." } }, "id": "GoogleCloudAiplatformV1SchemaPromptSpecAppBuilderData", "type": "object", "description": "Defines data for an application builder." }, "GoogleCloudAiplatformV1PublisherModelResourceReference": { "properties": { "resourceName": { "type": "string", "description": "The resource name of the Google Cloud resource." }, "uri": { "description": "The URI of the resource.", "type": "string" }, "useCase": { "type": "string", "description": "Use case (CUJ) of the resource.", "deprecated": true }, "description": { "deprecated": true, "description": "Description of the resource.", "type": "string" } }, "type": "object", "description": "Reference to a resource.", "id": "GoogleCloudAiplatformV1PublisherModelResourceReference" }, "GoogleCloudAiplatformV1FulfillmentSpec": { "properties": { "version": { "type": "integer", "format": "int32", "description": "Optional. Which version to use for evaluation." } }, "description": "Spec for fulfillment metric.", "id": "GoogleCloudAiplatformV1FulfillmentSpec", "type": "object" }, "GoogleCloudAiplatformV1ReasoningEngineContextSpec": { "type": "object", "id": "GoogleCloudAiplatformV1ReasoningEngineContextSpec", "description": "Configuration for how Agent Engine sub-resources should manage context.", "properties": { "memoryBankConfig": { "description": "Optional. Specification for a Memory Bank, which manages memories for the Agent Engine.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfig" } } }, "GoogleCloudAiplatformV1ExamplesOverride": { "properties": { "neighborCount": { "type": "integer", "description": "The number of neighbors to return.", "format": "int32" }, "crowdingCount": { "type": "integer", "format": "int32", "description": "The number of neighbors to return that have the same crowding tag." }, "restrictions": { "items": { "$ref": "GoogleCloudAiplatformV1ExamplesRestrictionsNamespace" }, "type": "array", "description": "Restrict the resulting nearest neighbors to respect these constraints." }, "dataFormat": { "type": "string", "enum": [ "DATA_FORMAT_UNSPECIFIED", "INSTANCES", "EMBEDDINGS" ], "enumDescriptions": [ "Unspecified format. Must not be used.", "Provided data is a set of model inputs.", "Provided data is a set of embeddings." ], "description": "The format of the data being provided with each call." }, "returnEmbeddings": { "type": "boolean", "description": "If true, return the embeddings instead of neighbors." } }, "id": "GoogleCloudAiplatformV1ExamplesOverride", "type": "object", "description": "Overrides for example-based explanations." }, "GoogleCloudAiplatformV1OnlineEvaluatorConfigRandomSampling": { "id": "GoogleCloudAiplatformV1OnlineEvaluatorConfigRandomSampling", "type": "object", "properties": { "percentage": { "format": "int32", "type": "integer", "description": "Required. The percentage of traces to sample for evaluation. Must be an integer between `1` and `100`." } }, "description": "Configuration for random sampling." }, "GoogleCloudAiplatformV1EvaluationMetric": { "description": "EvaluationMetric is a resource that represents a reusable metric configuration.", "properties": { "description": { "description": "Optional. A description of the EvaluationMetric.", "type": "string" }, "createTime": { "description": "Output only. The time when the EvaluationMetric was created.", "readOnly": true, "type": "string", "format": "google-datetime" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1EncryptionSpec", "description": "Optional. Customer-managed encryption key spec for this EvaluationMetric. If set, this EvaluationMetric will be secured by this key." }, "displayName": { "description": "Required. The user-friendly display name for the EvaluationMetric.", "type": "string" }, "metric": { "description": "Optional. The metric configuration. Only LLMMetric and CustomCodeExecutionMetric are supported.", "$ref": "GoogleCloudAiplatformV1Metric" }, "name": { "description": "Identifier. The resource name of the EvaluationMetric. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}`", "type": "string" }, "labels": { "additionalProperties": { "type": "string" }, "type": "object", "description": "Optional. Labels for the evaluation metric." }, "gcsUri": { "description": "Optional. The Google Cloud Storage URI that stores the metric specification..", "type": "string" }, "updateTime": { "description": "Output only. The time when the EvaluationMetric was last updated.", "format": "google-datetime", "type": "string", "readOnly": true } }, "type": "object", "id": "GoogleCloudAiplatformV1EvaluationMetric" }, "GoogleCloudAiplatformV1TrajectoryRecallMetricValue": { "description": "TrajectoryRecall metric value for an instance.", "properties": { "score": { "format": "float", "type": "number", "description": "Output only. TrajectoryRecall score.", "readOnly": true } }, "id": "GoogleCloudAiplatformV1TrajectoryRecallMetricValue", "type": "object" }, "GoogleCloudAiplatformV1ToolParameterKeyMatchResults": { "type": "object", "properties": { "toolParameterKeyMatchMetricValues": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ToolParameterKeyMatchMetricValue" }, "description": "Output only. Tool parameter key match metric values." } }, "id": "GoogleCloudAiplatformV1ToolParameterKeyMatchResults", "description": "Results for tool parameter key match metric." }, "GoogleCloudAiplatformV1NasJobSpec": { "description": "Represents the spec of a NasJob.", "properties": { "searchSpaceSpec": { "description": "It defines the search space for Neural Architecture Search (NAS).", "type": "string" }, "multiTrialAlgorithmSpec": { "description": "The spec of multi-trial algorithms.", "$ref": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec" }, "resumeNasJobId": { "description": "The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.", "type": "string" } }, "id": "GoogleCloudAiplatformV1NasJobSpec", "type": "object" }, "GoogleCloudAiplatformV1ListFeatureGroupsResponse": { "properties": { "nextPageToken": { "description": "A token, which can be sent as ListFeatureGroupsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" }, "featureGroups": { "type": "array", "description": "The FeatureGroups matching the request.", "items": { "$ref": "GoogleCloudAiplatformV1FeatureGroup" } } }, "id": "GoogleCloudAiplatformV1ListFeatureGroupsResponse", "type": "object", "description": "Response message for FeatureRegistryService.ListFeatureGroups." }, "GoogleCloudAiplatformV1RagEngineConfig": { "properties": { "name": { "type": "string", "description": "Identifier. The name of the RagEngineConfig. Format: `projects/{project}/locations/{location}/ragEngineConfig`" }, "ragManagedDbConfig": { "description": "The config of the RagManagedDb used by RagEngine.", "$ref": "GoogleCloudAiplatformV1RagManagedDbConfig" } }, "id": "GoogleCloudAiplatformV1RagEngineConfig", "type": "object", "description": "Config for RagEngine." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningTask": { "properties": { "inputs": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec", "description": "The input parameters of this HyperparameterTuningTask." }, "metadata": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata", "description": "The metadata information." } }, "description": "A TrainingJob that tunes Hypererparameters of a custom code Model.", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningTask", "type": "object" }, "GoogleCloudAiplatformV1RagVectorDbConfigRagManagedDb": { "type": "object", "id": "GoogleCloudAiplatformV1RagVectorDbConfigRagManagedDb", "properties": { "knn": { "description": "Performs a KNN search on RagCorpus. Default choice if not specified.", "$ref": "GoogleCloudAiplatformV1RagVectorDbConfigRagManagedDbKNN" }, "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.", "$ref": "GoogleCloudAiplatformV1RagVectorDbConfigRagManagedDbANN" } }, "description": "The config for the default RAG-managed Vector DB." }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetrics": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetrics", "type": "object", "description": "Bounding box matching model metrics for a single intersection-over-union threshold and multiple label match confidence thresholds.", "properties": { "iouThreshold": { "format": "float", "type": "number", "description": "The intersection-over-union threshold value used to compute this metrics entry." }, "confidenceMetrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics" }, "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." }, "meanAveragePrecision": { "type": "number", "format": "float", "description": "The mean average precision, most often close to `auPrc`." } } }, "GoogleCloudAiplatformV1Chunk": { "description": "Container for bytes-encoded data such as video frame, audio sample, or a complete binary/text data.", "type": "object", "properties": { "metadata": { "$ref": "GoogleCloudAiplatformV1Metadata", "description": "Optional. Metadata that is associated with the data in the payload." }, "mimeType": { "description": "Required. Mime type of the chunk data. See https://www.iana.org/assignments/media-types/media-types.xhtml for the full list.", "type": "string" }, "data": { "format": "byte", "description": "Required. The data in the chunk.", "type": "string" } }, "id": "GoogleCloudAiplatformV1Chunk" }, "GoogleCloudAiplatformV1TrajectoryPrecisionResults": { "id": "GoogleCloudAiplatformV1TrajectoryPrecisionResults", "description": "Results for TrajectoryPrecision metric.", "type": "object", "properties": { "trajectoryPrecisionMetricValues": { "type": "array", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1TrajectoryPrecisionMetricValue" }, "description": "Output only. TrajectoryPrecision metric values." } } }, "GoogleCloudAiplatformV1UpsertDatapointsRequest": { "description": "Request message for IndexService.UpsertDatapoints", "properties": { "datapoints": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1IndexDatapoint" }, "description": "A list of datapoints to be created/updated." }, "updateMask": { "description": "Optional. Update mask is used to specify the fields to be overwritten in the datapoints by the update. The fields specified in the update_mask are relative to each IndexDatapoint inside datapoints, not the full request. Updatable fields: * Use `all_restricts` to update both restricts and numeric_restricts.", "format": "google-fieldmask", "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1UpsertDatapointsRequest" }, "GoogleCloudAiplatformV1RaySpec": { "description": "Configuration information for the Ray cluster. For experimental launch, Ray cluster creation and Persistent cluster creation are 1:1 mapping: We will provision all the nodes within the Persistent cluster as Ray nodes.", "id": "GoogleCloudAiplatformV1RaySpec", "properties": { "rayClusterAutoscalingSpec": { "description": "Optional. Optional Ray autoscaling configurations.", "$ref": "GoogleCloudAiplatformV1RayClusterAutoscalingSpec" }, "rayLogsSpec": { "description": "Optional. OSS Ray logging configurations.", "$ref": "GoogleCloudAiplatformV1RayLogsSpec" }, "imageUri": { "type": "string", "description": "Optional. Default image for user to choose a preferred ML framework (for example, TensorFlow or Pytorch) by choosing from [Vertex prebuilt images](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). Either this or the resource_pool_images is required. Use this field if you need all the resource pools to have the same Ray image. Otherwise, use the {@code resource_pool_images} field." }, "headNodeResourcePoolId": { "description": "Optional. This will be used to indicate which resource pool will serve as the Ray head node(the first node within that pool). Will use the machine from the first workerpool as the head node by default if this field isn't set.", "type": "string" }, "resourcePoolImages": { "additionalProperties": { "type": "string" }, "type": "object", "description": "Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { \"ray_head_node_pool\": \"head image\" \"ray_worker_node_pool1\": \"worker image\" \"ray_worker_node_pool2\": \"another worker image\" }" }, "rayMetricSpec": { "$ref": "GoogleCloudAiplatformV1RayMetricSpec", "description": "Optional. Ray metrics configurations." } }, "type": "object" }, "GoogleCloudAiplatformV1WriteTensorboardRunDataResponse": { "description": "Response message for TensorboardService.WriteTensorboardRunData.", "id": "GoogleCloudAiplatformV1WriteTensorboardRunDataResponse", "properties": {}, "type": "object" }, "GoogleCloudAiplatformV1RougeInstance": { "id": "GoogleCloudAiplatformV1RougeInstance", "properties": { "prediction": { "type": "string", "description": "Required. Output of the evaluated model." }, "reference": { "type": "string", "description": "Required. Ground truth used to compare against the prediction." } }, "type": "object", "description": "Spec for rouge instance." }, "GoogleCloudAiplatformV1SummarizationQualityResult": { "properties": { "confidence": { "description": "Output only. Confidence for summarization quality score.", "type": "number", "format": "float", "readOnly": true }, "score": { "type": "number", "description": "Output only. Summarization Quality score.", "readOnly": true, "format": "float" }, "explanation": { "readOnly": true, "description": "Output only. Explanation for summarization quality score.", "type": "string" } }, "description": "Spec for summarization quality result.", "id": "GoogleCloudAiplatformV1SummarizationQualityResult", "type": "object" }, "GoogleCloudAiplatformV1RubricBasedInstructionFollowingInstance": { "description": "Instance for RubricBasedInstructionFollowing metric - one instance corresponds to one row in an evaluation dataset.", "id": "GoogleCloudAiplatformV1RubricBasedInstructionFollowingInstance", "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" } }, "type": "object" }, "GoogleCloudAiplatformV1Value": { "id": "GoogleCloudAiplatformV1Value", "description": "Value is the value of the field.", "type": "object", "properties": { "intValue": { "format": "int64", "description": "An integer value.", "type": "string" }, "doubleValue": { "type": "number", "format": "double", "description": "A double value." }, "stringValue": { "type": "string", "description": "A string value." } } }, "GoogleCloudAiplatformV1MemoryRevision": { "properties": { "createTime": { "description": "Output only. Represents the timestamp when this Memory Revision was created.", "readOnly": true, "format": "google-datetime", "type": "string" }, "expireTime": { "format": "google-datetime", "readOnly": true, "description": "Output only. Represents the timestamp of when this resource is considered expired.", "type": "string" }, "structuredData": { "description": "Output only. Represents the structured value of the memory at the time of revision creation.", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "readOnly": true, "type": "object" }, "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.", "items": { "$ref": "GoogleCloudAiplatformV1IntermediateExtractedMemory" }, "type": "array", "readOnly": true }, "context": { "description": "Output only. Represents the context of the Memory Revision. The context may include context from both the historical revisions and the extracted content.", "readOnly": true, "type": "string" }, "fact": { "description": "Output only. Represents the fact of the Memory Revision. This corresponds to the `fact` field of the parent Memory at the time of revision creation.", "readOnly": true, "type": "string" }, "labels": { "readOnly": true, "type": "object", "description": "Output only. Represents the labels of the Memory Revision. These labels are applied to the MemoryRevision when it is created based on `GenerateMemoriesRequest.revision_labels`.", "additionalProperties": { "type": "string" } }, "name": { "description": "Identifier. Represents the resource name of the Memory Revision. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}/revisions/{memory_revision}`", "type": "string" } }, "type": "object", "description": "A revision of a Memory.", "id": "GoogleCloudAiplatformV1MemoryRevision" }, "GoogleCloudAiplatformV1WriteTensorboardExperimentDataResponse": { "description": "Response message for TensorboardService.WriteTensorboardExperimentData.", "id": "GoogleCloudAiplatformV1WriteTensorboardExperimentDataResponse", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1NotebookRuntimeTemplate": { "type": "object", "description": "A template that specifies runtime configurations such as machine type, runtime version, network configurations, etc. Multiple runtimes can be created from a runtime template.", "id": "GoogleCloudAiplatformV1NotebookRuntimeTemplate", "properties": { "dataPersistentDiskSpec": { "description": "Optional. The specification of persistent disk attached to the runtime as data disk storage.", "$ref": "GoogleCloudAiplatformV1PersistentDiskSpec" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1EncryptionSpec", "description": "Customer-managed encryption key spec for the notebook runtime." }, "isDefault": { "type": "boolean", "description": "Output only. Deprecated: This field has no behavior. Use notebook_runtime_type = 'ONE_CLICK' instead. The default template to use if not specified.", "readOnly": true, "deprecated": true }, "networkTags": { "items": { "type": "string" }, "description": "Optional. The Compute Engine tags to add to runtime (see [Tagging instances](https://cloud.google.com/vpc/docs/add-remove-network-tags)).", "type": "array" }, "softwareConfig": { "description": "Optional. The notebook software configuration of the notebook runtime.", "$ref": "GoogleCloudAiplatformV1NotebookSoftwareConfig" }, "createTime": { "readOnly": true, "description": "Output only. Timestamp when this NotebookRuntimeTemplate was created.", "type": "string", "format": "google-datetime" }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this NotebookRuntimeTemplate was most recently updated.", "readOnly": true, "type": "string" }, "networkSpec": { "description": "Optional. Network spec.", "$ref": "GoogleCloudAiplatformV1NetworkSpec" }, "serviceAccount": { "description": "Deprecated: This field is ignored and the \"Vertex AI Notebook Service Account\" (service-PROJECT_NUMBER@gcp-sa-aiplatform-vm.iam.gserviceaccount.com) is used for the runtime workload identity. See https://cloud.google.com/iam/docs/service-agents#vertex-ai-notebook-service-account for more details. For NotebookExecutionJob, use NotebookExecutionJob.service_account instead. The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used.", "type": "string", "deprecated": true }, "eucConfig": { "$ref": "GoogleCloudAiplatformV1NotebookEucConfig", "description": "EUC configuration of the NotebookRuntimeTemplate." }, "name": { "description": "The resource name of the NotebookRuntimeTemplate.", "type": "string" }, "idleShutdownConfig": { "description": "The idle shutdown configuration of NotebookRuntimeTemplate. This config will only be set when idle shutdown is enabled.", "$ref": "GoogleCloudAiplatformV1NotebookIdleShutdownConfig" }, "etag": { "type": "string", "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." }, "description": { "type": "string", "description": "The description of the NotebookRuntimeTemplate." }, "reservationAffinity": { "description": "Optional. Reservation Affinity of the notebook runtime template.", "$ref": "GoogleCloudAiplatformV1NotebookReservationAffinity" }, "shieldedVmConfig": { "description": "Optional. Immutable. Runtime Shielded VM spec.", "$ref": "GoogleCloudAiplatformV1ShieldedVmConfig" }, "machineSpec": { "description": "Optional. Immutable. The specification of a single machine for the template.", "$ref": "GoogleCloudAiplatformV1MachineSpec" }, "notebookRuntimeType": { "type": "string", "description": "Optional. Immutable. The type of the notebook runtime template.", "enum": [ "NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED", "USER_DEFINED", "ONE_CLICK" ], "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." ] }, "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" }, "labels": { "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.", "type": "object", "additionalProperties": { "type": "string" } } } }, "GoogleCloudAiplatformV1SummarizationVerbosityInput": { "properties": { "metricSpec": { "description": "Required. Spec for summarization verbosity score metric.", "$ref": "GoogleCloudAiplatformV1SummarizationVerbositySpec" }, "instance": { "$ref": "GoogleCloudAiplatformV1SummarizationVerbosityInstance", "description": "Required. Summarization verbosity instance." } }, "type": "object", "id": "GoogleCloudAiplatformV1SummarizationVerbosityInput", "description": "Input for summarization verbosity metric." }, "GoogleCloudAiplatformV1SummarizationVerbositySpec": { "type": "object", "description": "Spec for summarization verbosity score metric.", "properties": { "useReference": { "description": "Optional. Whether to use instance.reference to compute summarization verbosity.", "type": "boolean" }, "version": { "type": "integer", "format": "int32", "description": "Optional. Which version to use for evaluation." } }, "id": "GoogleCloudAiplatformV1SummarizationVerbositySpec" }, "GoogleCloudAiplatformV1Model": { "properties": { "defaultCheckpointId": { "description": "The default checkpoint id of a model version.", "type": "string" }, "metadataSchemaUri": { "type": "string", "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." }, "explanationSpec": { "$ref": "GoogleCloudAiplatformV1ExplanationSpec", "description": "The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob." }, "deployedModels": { "readOnly": true, "type": "array", "description": "Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.", "items": { "$ref": "GoogleCloudAiplatformV1DeployedModelRef" } }, "originalModelInfo": { "description": "Output only. If this Model is a copy of another Model, this contains info about the original.", "$ref": "GoogleCloudAiplatformV1ModelOriginalModelInfo", "readOnly": true }, "metadataArtifact": { "description": "Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.", "readOnly": true, "type": "string" }, "description": { "type": "string", "description": "The description of the Model." }, "encryptionSpec": { "description": "Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "updateTime": { "format": "google-datetime", "readOnly": true, "type": "string", "description": "Output only. Timestamp when this Model was most recently updated." }, "dataStats": { "$ref": "GoogleCloudAiplatformV1ModelDataStats", "description": "Stats of data used for training or evaluating the Model. Only populated when the Model is trained by a TrainingPipeline with data_input_config." }, "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" }, "displayName": { "type": "string", "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." }, "supportedInputStorageFormats": { "readOnly": true, "items": { "type": "string" }, "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.", "type": "array" }, "versionCreateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this version was created.", "readOnly": true, "type": "string" }, "modelSourceInfo": { "$ref": "GoogleCloudAiplatformV1ModelSourceInfo", "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 }, "baseModelSource": { "description": "Optional. User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models.", "$ref": "GoogleCloudAiplatformV1ModelBaseModelSource" }, "checkpoints": { "items": { "$ref": "GoogleCloudAiplatformV1Checkpoint" }, "type": "array", "description": "Optional. Output only. The checkpoints of the model.", "readOnly": true }, "trainingPipeline": { "readOnly": true, "description": "Output only. The resource name of the TrainingPipeline that uploaded this Model, if any.", "type": "string" }, "versionId": { "readOnly": true, "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" }, "predictSchemata": { "$ref": "GoogleCloudAiplatformV1PredictSchemata", "description": "The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain." }, "containerSpec": { "description": "The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.", "$ref": "GoogleCloudAiplatformV1ModelContainerSpec" }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when this Model was uploaded into Vertex AI.", "readOnly": true, "type": "string" }, "supportedExportFormats": { "description": "Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1ModelExportFormat" }, "type": "array" }, "versionDescription": { "description": "The description of this version.", "type": "string" }, "versionUpdateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this version was most recently updated.", "readOnly": true, "type": "string" }, "etag": { "type": "string", "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." }, "pipelineJob": { "description": "Optional. This field is populated if the model is produced by a pipeline job.", "type": "string" }, "name": { "description": "Identifier. The resource name of the Model.", "type": "string" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "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." }, "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" }, "supportedOutputStorageFormats": { "readOnly": true, "type": "array", "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.", "items": { "type": "string" } }, "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.", "items": { "type": "string", "enum": [ "DEPLOYMENT_RESOURCES_TYPE_UNSPECIFIED", "DEDICATED_RESOURCES", "AUTOMATIC_RESOURCES", "SHARED_RESOURCES" ], "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." ] }, "type": "array", "readOnly": true }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "versionAliases": { "type": "array", "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.", "items": { "type": "string" } } }, "description": "A trained machine learning Model.", "type": "object", "id": "GoogleCloudAiplatformV1Model" }, "GenaiVertexV1TextResponseFormat": { "id": "GenaiVertexV1TextResponseFormat", "description": "Configuration for text output format.", "type": "object", "properties": { "schema": { "description": "The JSON schema that the output should conform to. Only applicable when mime_type is application/json.", "$ref": "GenaiVertexV1Struct" }, "mimeType": { "enumDescriptions": [ "Default value. This value is unused.", "JSON output format.", "Plain text output format." ], "description": "The MIME type of the text output.", "type": "string", "enum": [ "TYPE_UNSPECIFIED", "TYPE_APPLICATION_JSON", "TYPE_TEXT_PLAIN" ] } } }, "GoogleCloudAiplatformV1ExactMatchResults": { "type": "object", "description": "Results for exact match metric.", "id": "GoogleCloudAiplatformV1ExactMatchResults", "properties": { "exactMatchMetricValues": { "items": { "$ref": "GoogleCloudAiplatformV1ExactMatchMetricValue" }, "description": "Output only. Exact match metric values.", "type": "array", "readOnly": true } } }, "GoogleCloudAiplatformV1NearestNeighborQueryParameters": { "description": "Parameters that can be overrided in each query to tune query latency and recall.", "id": "GoogleCloudAiplatformV1NearestNeighborQueryParameters", "properties": { "approximateNeighborCandidates": { "description": "Optional. The number of neighbors to find via approximate search before exact reordering is performed; if set, this value must be \u003e neighbor_count.", "type": "integer", "format": "int32" }, "leafNodesSearchFraction": { "type": "number", "format": "double", "description": "Optional. The fraction of the number of leaves to search, set at query time allows user to tune search performance. This value increase result in both search accuracy and latency increase. The value should be between 0.0 and 1.0." } }, "type": "object" }, "GoogleCloudAiplatformV1GroundednessInput": { "id": "GoogleCloudAiplatformV1GroundednessInput", "properties": { "instance": { "description": "Required. Groundedness instance.", "$ref": "GoogleCloudAiplatformV1GroundednessInstance" }, "metricSpec": { "description": "Required. Spec for groundedness metric.", "$ref": "GoogleCloudAiplatformV1GroundednessSpec" } }, "type": "object", "description": "Input for groundedness metric." }, "GoogleCloudAiplatformV1DeployModelOperationMetadata": { "description": "Runtime operation information for EndpointService.DeployModel.", "properties": { "deploymentStage": { "enumDescriptions": [ "Default value. This value is unused.", "The deployment is initializing and setting up the environment.", "The deployment is preparing the model assets.", "The deployment is creating the underlying serving cluster.", "The deployment is adding nodes to the serving cluster.", "The deployment is getting the container image for the model server.", "The deployment is starting the model server.", "The deployment is performing finalization steps.", "The deployment has terminated.", "The deployment has succeeded.", "The deployment has failed." ], "description": "Output only. The deployment stage of the model.", "readOnly": true, "type": "string", "enum": [ "DEPLOYMENT_STAGE_UNSPECIFIED", "STARTING_DEPLOYMENT", "PREPARING_MODEL", "CREATING_SERVING_CLUSTER", "ADDING_NODES_TO_CLUSTER", "GETTING_CONTAINER_IMAGE", "STARTING_MODEL_SERVER", "FINISHING_UP", "DEPLOYMENT_TERMINATED", "SUCCESSFULLY_DEPLOYED", "FAILED_TO_DEPLOY" ] }, "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "type": "object", "id": "GoogleCloudAiplatformV1DeployModelOperationMetadata" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoObjectTracking": { "type": "object", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoObjectTracking", "description": "A TrainingJob that trains and uploads an AutoML Video ObjectTracking Model." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata", "type": "object", "properties": { "bestTrialBackingCustomJob": { "type": "string", "description": "The resource name of the CustomJob that has been created to run the best Trial of this HyperparameterTuning task." }, "backingHyperparameterTuningJob": { "description": "The resource name of the HyperparameterTuningJob that has been created to carry out this HyperparameterTuning task.", "type": "string" } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig": { "properties": { "overrideExistingTable": { "type": "boolean", "description": "If true and an export destination is specified, then the contents of the destination are overwritten. Otherwise, if the export destination already exists, then the export operation fails." }, "destinationBigqueryUri": { "type": "string", "description": "URI of desired destination BigQuery table. Expected format: `bq://{project_id}:{dataset_id}:{table}` If not specified, then results are exported to the following auto-created BigQuery table: `{project_id}:export_evaluated_examples_{model_name}_{yyyy_MM_dd'T'HH_mm_ss_SSS'Z'}.evaluated_examples`" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig", "type": "object", "description": "Configuration for exporting test set predictions to a BigQuery table." }, "GenaiVertexV1ContentList": { "id": "GenaiVertexV1ContentList", "type": "object", "description": "A list of Content.", "properties": { "contents": { "description": "The contents of the list.", "items": { "$ref": "GenaiVertexV1Content" }, "type": "array" } } }, "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExampleGeneratedMemory": { "id": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExampleGeneratedMemory", "description": "A memory generated by the operation.", "properties": { "topics": { "items": { "$ref": "GoogleCloudAiplatformV1MemoryTopicId" }, "type": "array", "description": "Optional. Represents the list of topics that the memory should be associated with. For example, use `custom_memory_topic_label = \"jargon\"` if the extracted memory is an example of memory extraction for the custom topic `jargon`." }, "fact": { "description": "Required. Represents the fact to generate a memory from.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1NasJobOutput": { "description": "Represents a uCAIP NasJob output.", "properties": { "multiTrialJobOutput": { "description": "Output only. The output of this multi-trial Neural Architecture Search (NAS) job.", "$ref": "GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutput", "readOnly": true } }, "type": "object", "id": "GoogleCloudAiplatformV1NasJobOutput" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation": { "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.", "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation", "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" } } }, "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataEvents": { "properties": { "event": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Content" }, "description": "Optional. A list of events." } }, "description": "Represents a list of events for an agent.", "id": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataEvents", "type": "object" }, "GoogleCloudLocationLocation": { "id": "GoogleCloudLocationLocation", "description": "A resource that represents a Google Cloud location.", "type": "object", "properties": { "labels": { "additionalProperties": { "type": "string" }, "description": "Cross-service attributes for the location. For example {\"cloud.googleapis.com/region\": \"us-east1\"}", "type": "object" }, "name": { "type": "string", "description": "Resource name for the location, which may vary between implementations. For example: `\"projects/example-project/locations/us-east1\"`" }, "displayName": { "description": "The friendly name for this location, typically a nearby city name. For example, \"Tokyo\".", "type": "string" }, "metadata": { "additionalProperties": { "description": "Properties of the object. Contains field @type with type URL.", "type": "any" }, "type": "object", "description": "Service-specific metadata. For example the available capacity at the given location." }, "locationId": { "type": "string", "description": "The canonical id for this location. For example: `\"us-east1\"`." } } }, "GoogleCloudAiplatformV1SuspendOnlineEvaluatorRequest": { "description": "Request message for SuspendOnlineEvaluator.", "properties": {}, "id": "GoogleCloudAiplatformV1SuspendOnlineEvaluatorRequest", "type": "object" }, "GoogleCloudAiplatformV1DeploymentResourcePool": { "description": "A description of resources that can be shared by multiple DeployedModels, whose underlying specification consists of a DedicatedResources.", "type": "object", "id": "GoogleCloudAiplatformV1DeploymentResourcePool", "properties": { "encryptionSpec": { "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.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "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" }, "disableContainerLogging": { "type": "boolean", "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." }, "name": { "description": "Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", "type": "string" }, "dedicatedResources": { "description": "Required. The underlying DedicatedResources that the DeploymentResourcePool uses.", "$ref": "GoogleCloudAiplatformV1DedicatedResources" }, "satisfiesPzs": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "createTime": { "readOnly": true, "format": "google-datetime", "description": "Output only. Timestamp when this DeploymentResourcePool was created.", "type": "string" }, "satisfiesPzi": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." } } }, "GoogleCloudAiplatformV1ServingProfileCmekConfig": { "type": "object", "description": "Configuration for Customer-Managed Encryption Keys (CMEK).", "id": "GoogleCloudAiplatformV1ServingProfileCmekConfig", "properties": { "encryptionSpec": { "description": "Required. The customer-managed encryption key spec for the Serving Profile.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" } } }, "GoogleCloudAiplatformV1GenericOperationMetadata": { "properties": { "partialFailures": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleRpcStatus" }, "description": "Output only. Partial failures encountered. E.g. single files that couldn't be read. This field should never exceed 20 entries. Status details field will contain standard Google Cloud error details." }, "createTime": { "format": "google-datetime", "type": "string", "readOnly": true, "description": "Output only. Time when the operation was created." }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the operation was updated for the last time. If the operation has finished (successfully or not), this is the finish time." } }, "description": "Generic Metadata shared by all operations.", "type": "object", "id": "GoogleCloudAiplatformV1GenericOperationMetadata" }, "GoogleCloudAiplatformV1EvaluationItem": { "id": "GoogleCloudAiplatformV1EvaluationItem", "type": "object", "properties": { "metadata": { "description": "Optional. Metadata for the EvaluationItem.", "type": "any" }, "labels": { "additionalProperties": { "type": "string" }, "description": "Optional. Labels for the EvaluationItem.", "type": "object" }, "evaluationRequest": { "$ref": "GoogleCloudAiplatformV1EvaluationRequest", "description": "The request to evaluate." }, "displayName": { "description": "Required. The display name of the EvaluationItem.", "type": "string" }, "name": { "description": "Identifier. The resource name of the EvaluationItem. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}`", "type": "string" }, "error": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. Error for the evaluation item." }, "createTime": { "readOnly": true, "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when this item was created." }, "gcsUri": { "description": "The Cloud Storage object where the request or response is stored.", "type": "string" }, "evaluationItemType": { "type": "string", "description": "Required. The type of the EvaluationItem.", "enum": [ "EVALUATION_ITEM_TYPE_UNSPECIFIED", "REQUEST", "RESULT" ], "enumDescriptions": [ "The default value. This value is unused.", "The EvaluationItem is a request to evaluate.", "The EvaluationItem is the result of evaluation." ] }, "evaluationResponse": { "readOnly": true, "description": "Output only. The response from evaluation.", "$ref": "GoogleCloudAiplatformV1EvaluationResult" } }, "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." }, "GoogleCloudAiplatformV1RubricGenerationSpec": { "description": "Specification for how rubrics should be generated.", "properties": { "rubricTypeOntology": { "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.", "type": "array" }, "modelConfig": { "$ref": "GoogleCloudAiplatformV1AutoraterConfig", "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." }, "promptTemplate": { "type": "string", "description": "Template for the prompt used to generate rubrics. The details should be updated based on the most-recent recipe requirements." }, "rubricContentType": { "type": "string", "enum": [ "RUBRIC_CONTENT_TYPE_UNSPECIFIED", "PROPERTY", "NL_QUESTION_ANSWER", "PYTHON_CODE_ASSERTION" ], "description": "The type of rubric content to be generated.", "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." ] } }, "type": "object", "id": "GoogleCloudAiplatformV1RubricGenerationSpec" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputs": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputs", "type": "object", "properties": { "enableProbabilisticInference": { "type": "boolean", "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." }, "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.", "type": "string", "format": "int64" }, "dataGranularity": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity", "description": "Expected difference in time granularity between rows in the data." }, "weightColumn": { "type": "string", "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." }, "timeSeriesAttributeColumns": { "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.", "type": "array" }, "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" }, "additionalExperiments": { "type": "array", "description": "Additional experiment flags for the time series forcasting training.", "items": { "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": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation" } }, "quantiles": { "items": { "format": "double", "type": "number" }, "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" }, "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" }, "holidayRegions": { "items": { "type": "string" }, "type": "array", "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." }, "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" }, "targetColumn": { "type": "string", "description": "The name of the column that the Model is to predict values for. This column must be unavailable at forecast." }, "hierarchyConfig": { "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHierarchyConfig" }, "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." }, "exportEvaluatedDataItemsConfig": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig", "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed." }, "unavailableAtForecastColumns": { "description": "Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day.", "items": { "type": "string" }, "type": "array" }, "contextWindow": { "format": "int64", "type": "string", "description": "The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field." }, "timeColumn": { "type": "string", "description": "The name of the column that identifies time order in the time series. This column must be available at forecast." }, "windowConfig": { "description": "Config containing strategy for generating sliding windows.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig" } } }, "GoogleCloudAiplatformV1SummarizationQualitySpec": { "properties": { "useReference": { "type": "boolean", "description": "Optional. Whether to use instance.reference to compute summarization quality." }, "version": { "description": "Optional. Which version to use for evaluation.", "format": "int32", "type": "integer" } }, "id": "GoogleCloudAiplatformV1SummarizationQualitySpec", "description": "Spec for summarization quality score metric.", "type": "object" }, "GoogleCloudAiplatformV1ExplanationMetadataOverrideInputMetadataOverride": { "id": "GoogleCloudAiplatformV1ExplanationMetadataOverrideInputMetadataOverride", "type": "object", "properties": { "inputBaselines": { "type": "array", "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.", "items": { "type": "any" } } }, "description": "The input metadata entries to be overridden." }, "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityTraceScopePredicate": { "properties": { "totalTokenUsage": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityNumericPredicate", "description": "Filter on the total token usage within a trace." }, "serviceVersion": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityStringPredicate", "description": "Filter on the version that served a trace (`service.version` OTel resource attribute). At most one is allowed. On Vertex AI Agent Engine, this is the runtime revision id, currently set only for agents created via v1beta1." }, "duration": { "description": "Filter on the duration of a trace (in seconds).", "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityNumericPredicate" } }, "description": "Defines a single filter predicate.", "type": "object", "id": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityTraceScopePredicate" }, "GoogleCloudAiplatformV1ThresholdConfig": { "properties": { "value": { "description": "Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.", "type": "number", "format": "double" } }, "id": "GoogleCloudAiplatformV1ThresholdConfig", "type": "object", "description": "The config for feature monitoring threshold." }, "GoogleCloudAiplatformV1UpdateEndpointLongRunningRequest": { "description": "Request message for EndpointService.UpdateEndpointLongRunning.", "type": "object", "properties": { "endpoint": { "description": "Required. The Endpoint which replaces the resource on the server. Currently we only support updating the `client_connection_config` field, all the other fields' update will be blocked.", "$ref": "GoogleCloudAiplatformV1Endpoint" } }, "id": "GoogleCloudAiplatformV1UpdateEndpointLongRunningRequest" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs": { "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 Classification might stop training before the entire training budget has been used.", "type": "boolean" }, "budgetMilliNodeHours": { "format": "int64", "type": "string", "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." }, "tunableParameter": { "description": "Trainer type for Vision TrainRequest.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter" }, "multiLabel": { "type": "boolean", "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)." }, "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" }, "baseModelId": { "type": "string", "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." }, "modelType": { "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" ], "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." ] } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs" }, "GoogleCloudAiplatformV1CancelAsyncQueryReasoningEngineResponse": { "properties": {}, "description": "Response message for ReasoningEngineExecutionService.CancelAsyncQueryReasoningEngine.", "type": "object", "id": "GoogleCloudAiplatformV1CancelAsyncQueryReasoningEngineResponse" }, "GoogleCloudAiplatformV1ImportEvaluationSetRequest": { "id": "GoogleCloudAiplatformV1ImportEvaluationSetRequest", "type": "object", "properties": { "bigquerySource": { "$ref": "GoogleCloudAiplatformV1BigQueryRequestSet", "description": "BigQuery source with column mappings." }, "gcsSource": { "description": "Google Cloud Storage location.", "$ref": "GoogleCloudAiplatformV1ImportEvaluationSetRequestGcsSource" }, "interactionsSource": { "description": "Optional. Source for importing Interactions API interactions.", "$ref": "GoogleCloudAiplatformV1ImportEvaluationSetRequestInteractionsSource" }, "inlineSource": { "description": "Inline source for small payloads (\u003c 4MB).", "$ref": "GoogleCloudAiplatformV1ImportEvaluationSetRequestInlineSource" }, "gcsDestination": { "$ref": "GoogleCloudAiplatformV1GcsDestination", "description": "Required. The Cloud Storage location where the resulting EvaluationItem payloads will be stored." }, "evaluationSet": { "description": "Required. The EvaluationSet to create. Used to specify 'display_name' and 'metadata'. The 'evaluation_items' field is ignored and populated by the import process.", "$ref": "GoogleCloudAiplatformV1EvaluationSet" }, "cloudTraceSource": { "description": "Source for loading data directly from Cloud Trace.", "$ref": "GoogleCloudAiplatformV1ImportEvaluationSetRequestCloudTraceSource" }, "agentEngineSource": { "$ref": "GoogleCloudAiplatformV1ImportEvaluationSetRequestAgentEngineSource", "description": "Source for loading Agent Engine sessions." } }, "description": "Request message for EvaluationManagementService.ImportEvaluationSet." }, "GoogleCloudAiplatformV1TrajectoryExactMatchMetricValue": { "description": "TrajectoryExactMatch metric value for an instance.", "type": "object", "id": "GoogleCloudAiplatformV1TrajectoryExactMatchMetricValue", "properties": { "score": { "format": "float", "description": "Output only. TrajectoryExactMatch score.", "readOnly": true, "type": "number" } } }, "GoogleCloudAiplatformV1DeleteFeatureValuesResponse": { "type": "object", "description": "Response message for FeaturestoreService.DeleteFeatureValues.", "id": "GoogleCloudAiplatformV1DeleteFeatureValuesResponse", "properties": { "selectTimeRangeAndFeature": { "description": "Response for request specifying time range and feature", "$ref": "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectTimeRangeAndFeature" }, "selectEntity": { "description": "Response for request specifying the entities to delete", "$ref": "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectEntity" } } }, "GoogleCloudAiplatformV1SandboxEnvironmentSpecCodeExecutionEnvironment": { "type": "object", "description": "The code execution environment with customized settings.", "properties": { "codeLanguage": { "enum": [ "LANGUAGE_UNSPECIFIED", "LANGUAGE_PYTHON", "LANGUAGE_JAVASCRIPT" ], "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." }, "machineConfig": { "enumDescriptions": [ "The default value: milligcu 2000, memory 1.5Gib", "The default value: milligcu 4000, memory 4 Gib" ], "enum": [ "MACHINE_CONFIG_UNSPECIFIED", "MACHINE_CONFIG_VCPU4_RAM4GIB" ], "description": "The machine config of the code execution environment.", "type": "string" } }, "id": "GoogleCloudAiplatformV1SandboxEnvironmentSpecCodeExecutionEnvironment" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation": { "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.", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation", "properties": { "columnName": { "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1BigQuerySource": { "id": "GoogleCloudAiplatformV1BigQuerySource", "type": "object", "description": "The BigQuery location for the input content.", "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" } } }, "GoogleCloudAiplatformV1BatchReadFeatureValuesResponse": { "id": "GoogleCloudAiplatformV1BatchReadFeatureValuesResponse", "description": "Response message for FeaturestoreService.BatchReadFeatureValues.", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1ResourcePoolAutoscalingSpec": { "id": "GoogleCloudAiplatformV1ResourcePoolAutoscalingSpec", "properties": { "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" }, "minReplicaCount": { "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", "type": "string" } }, "type": "object", "description": "The min/max number of replicas allowed if enabling autoscaling" }, "GoogleCloudAiplatformV1SchemaPromptSpecReferenceSentencePair": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaPromptSpecReferenceSentencePair", "properties": { "targetSentence": { "type": "string", "description": "Target sentence in the sentence pair." }, "sourceSentence": { "description": "Source sentence in the sentence pair.", "type": "string" } }, "description": "A pair of sentences used as reference in source and target languages." }, "GoogleCloudAiplatformV1ReasoningEngineSpecPackageSpec": { "properties": { "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" }, "pythonVersion": { "description": "Optional. The Python version. Supported values are 3.10, 3.11, 3.12, 3.13, 3.14. If not specified, the default value is 3.10.", "type": "string" }, "requirementsGcsUri": { "type": "string", "description": "Optional. The Cloud Storage URI of the `requirements.txt` file" } }, "description": "User-provided package specification, containing pickled object and package requirements.", "id": "GoogleCloudAiplatformV1ReasoningEngineSpecPackageSpec", "type": "object" }, "GoogleCloudAiplatformV1SchemaPromptSpecTranslationSentenceFileInput": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationSentenceFileInput", "properties": { "fileInputSource": { "description": "Inlined file source.", "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationFileInputSource" }, "gcsInputSource": { "description": "Cloud Storage file source.", "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationGcsInputSource" } } }, "GoogleCloudAiplatformV1EvaluationRunMetricComputationBasedMetricSpec": { "description": "Specification for a computation based metric.", "type": "object", "id": "GoogleCloudAiplatformV1EvaluationRunMetricComputationBasedMetricSpec", "properties": { "parameters": { "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "type": "object", "description": "Optional. A map of parameters for the metric, e.g. {\"rouge_type\": \"rougeL\"}." }, "type": { "enumDescriptions": [ "Unspecified computation based metric type.", "Exact match metric.", "BLEU metric.", "ROUGE metric." ], "type": "string", "description": "Required. The type of the computation based metric.", "enum": [ "COMPUTATION_BASED_METRIC_TYPE_UNSPECIFIED", "EXACT_MATCH", "BLEU", "ROUGE" ] } } }, "GoogleCloudAiplatformV1UndeployModelRequest": { "id": "GoogleCloudAiplatformV1UndeployModelRequest", "type": "object", "properties": { "deployedModelId": { "description": "Required. The ID of the DeployedModel to be undeployed from the Endpoint.", "type": "string" }, "trafficSplit": { "additionalProperties": { "format": "int32", "type": "integer" }, "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" } }, "description": "Request message for EndpointService.UndeployModel." }, "GoogleCloudAiplatformV1SchemaVisualInspectionClassificationLabelSavedQueryMetadata": { "properties": { "multiLabel": { "description": "Whether or not the classification label is multi_label.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1SchemaVisualInspectionClassificationLabelSavedQueryMetadata", "type": "object" }, "GoogleCloudAiplatformV1GoogleDriveSource": { "id": "GoogleCloudAiplatformV1GoogleDriveSource", "properties": { "resourceIds": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1GoogleDriveSourceResourceId" }, "description": "Required. Google Drive resource IDs." } }, "description": "The Google Drive location for the input content.", "type": "object" }, "GenaiVertexV1ServerToolResultDelta": { "type": "object", "properties": { "codeExecutionResult": { "$ref": "GenaiVertexV1CodeExecutionResultDelta" }, "signature": { "description": "A signature hash for backend validation.", "format": "byte", "type": "string" }, "urlContextResult": { "$ref": "GenaiVertexV1UrlContextResultDelta" }, "processingResult": { "$ref": "GenaiVertexV1ProcessingResultDelta" }, "googleSearchResult": { "$ref": "GenaiVertexV1GoogleSearchResultDelta" }, "fileSearchResult": { "$ref": "GenaiVertexV1FileSearchResultDelta" }, "retrievalResult": { "$ref": "GenaiVertexV1RetrievalResultDelta" }, "googleMapsResult": { "$ref": "GenaiVertexV1GoogleMapsResultDelta" } }, "id": "GenaiVertexV1ServerToolResultDelta" }, "GoogleCloudAiplatformV1Memory": { "type": "object", "properties": { "createTime": { "description": "Output only. Represents the timestamp when this Memory was created.", "readOnly": true, "type": "string", "format": "google-datetime" }, "revisionTtl": { "type": "string", "description": "Optional. Input only. Represents the TTL for the revision. The expiration time is computed: now + TTL.", "format": "google-duration" }, "metadata": { "additionalProperties": { "$ref": "GoogleCloudAiplatformV1MemoryMetadataValue" }, "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" }, "revisionExpireTime": { "format": "google-datetime", "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." }, "topics": { "description": "Optional. Represents the Topics of the Memory.", "items": { "$ref": "GoogleCloudAiplatformV1MemoryTopicId" }, "type": "array" }, "context": { "description": "Optional. Represents the context of the memory.", "type": "string" }, "fact": { "type": "string", "description": "Optional. Represents semantic knowledge extracted from the source content." }, "scope": { "type": "object", "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 '*'.", "additionalProperties": { "type": "string" } }, "disableMemoryRevisions": { "type": "boolean", "description": "Optional. Input only. Indicates whether no revision will be created for this request." }, "displayName": { "description": "Optional. Represents the display name of the Memory.", "type": "string" }, "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" }, "revisionLabels": { "type": "object", "description": "Optional. Input only. Represents the labels to apply to the Memory Revision created as a result of this request.", "additionalProperties": { "type": "string" } }, "ttl": { "type": "string", "description": "Optional. Input only. Represents the TTL for this resource. The expiration time is computed: now + TTL.", "format": "google-duration" }, "description": { "description": "Optional. Represents the description of the Memory.", "type": "string" }, "updateTime": { "readOnly": true, "format": "google-datetime", "type": "string", "description": "Output only. Represents the timestamp when this Memory was most recently updated." }, "name": { "description": "Identifier. Represents the resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "type": "string" } }, "description": "A memory.", "id": "GoogleCloudAiplatformV1Memory" }, "GoogleCloudAiplatformV1UpdateOnlineEvaluatorOperationMetadata": { "type": "object", "description": "Metadata for the UpdateOnlineEvaluator operation.", "id": "GoogleCloudAiplatformV1UpdateOnlineEvaluatorOperationMetadata", "properties": { "genericMetadata": { "description": "Generic operation metadata.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1CloudLoggingConfigTracingContext": { "description": "Tracing context for Observability correlation.", "id": "GoogleCloudAiplatformV1CloudLoggingConfigTracingContext", "properties": { "traceId": { "type": "string", "description": "Optional. Trace ID being written to Cloud Trace in association with this log entry. e.g., `12345`, the numeric ID from the resource name. If a trace or span is being evaluated, this field should be populated." }, "conversationId": { "description": "Optional. Unique identifier for a conversation (session thread), used to store and correlate messages within a conversation. The value corresponds to the `gen_ai.conversation.id` field in the the OpenTelemetry GenAI attributes.", "type": "string" }, "spanId": { "type": "string", "description": "Optional. ID of the Cloud Trace span associated with the current operation in which the log is being written. e.g., `7a2190356c3fc94b`. If a span is being evaluated, this field should be populated." } }, "type": "object" }, "GoogleCloudAiplatformV1CitationMetadata": { "type": "object", "description": "A collection of citations that apply to a piece of generated content.", "properties": { "citations": { "description": "Output only. A list of citations for the content.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Citation" }, "readOnly": true } }, "id": "GoogleCloudAiplatformV1CitationMetadata" }, "GoogleCloudAiplatformV1DeprovisionSemanticGovernancePolicyEngineRequest": { "description": "Request message for SemanticGovernancePolicyEngineService.DeprovisionSemanticGovernancePolicyEngine.", "properties": { "force": { "type": "boolean", "description": "Optional. If true, the operation bypass checks on current state and force the deprovisioning operation." } }, "id": "GoogleCloudAiplatformV1DeprovisionSemanticGovernancePolicyEngineRequest", "type": "object" }, "GenaiVertexV1CodeExecutionCallContentCodeExecutionCallArguments": { "type": "object", "properties": { "language": { "type": "string", "enumDescriptions": [ "Unspecified language. This value should not be used.", "Python \u003e= 3.10, with numpy and simpy available." ], "description": "Programming language of the `code`.", "enum": [ "LANGUAGE_UNSPECIFIED", "PYTHON" ] }, "code": { "type": "string", "description": "The code to be executed." } }, "id": "GenaiVertexV1CodeExecutionCallContentCodeExecutionCallArguments", "description": "The arguments to pass to the code execution." }, "GoogleCloudAiplatformV1AuthorizeSandboxEnvironmentAccessRequest": { "id": "GoogleCloudAiplatformV1AuthorizeSandboxEnvironmentAccessRequest", "description": "Request message for SandboxEnvironmentExecutionService.AuthorizeSandboxEnvironmentAccess.", "properties": {}, "type": "object" }, "CloudAiLargeModelsVisionNamedBoundingBox": { "type": "object", "properties": { "x1": { "type": "number", "format": "float" }, "x2": { "format": "float", "type": "number" }, "entities": { "type": "array", "items": { "type": "string" } }, "classes": { "type": "array", "items": { "type": "string" } }, "y1": { "format": "float", "type": "number" }, "y2": { "type": "number", "format": "float" }, "scores": { "type": "array", "items": { "format": "float", "type": "number" } } }, "id": "CloudAiLargeModelsVisionNamedBoundingBox" }, "GoogleCloudAiplatformV1CreateFeatureRequest": { "description": "Request message for FeaturestoreService.CreateFeature. Request message for FeatureRegistryService.CreateFeature.", "id": "GoogleCloudAiplatformV1CreateFeatureRequest", "properties": { "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" }, "feature": { "$ref": "GoogleCloudAiplatformV1Feature", "description": "Required. The Feature to create." }, "parent": { "type": "string", "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": "object" }, "GenaiVertexV1GoogleSearchCallContentGoogleSearchCallArguments": { "type": "object", "id": "GenaiVertexV1GoogleSearchCallContentGoogleSearchCallArguments", "properties": { "queries": { "description": "Web search queries for the following-up web search.", "type": "array", "items": { "type": "string" } } }, "description": "The arguments to pass to Google Search." }, "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataGcsSource": { "properties": { "uri": { "type": "array", "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.", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataGcsSource", "type": "object" }, "GoogleCloudAiplatformV1GroundingChunkImage": { "type": "object", "properties": { "imageUri": { "type": "string", "description": "The URI of the image." }, "title": { "type": "string", "description": "The title of the image search result page." }, "sourceUri": { "description": "The URI of the image search result page.", "type": "string" }, "domain": { "description": "The domain of the image search result page.", "type": "string" } }, "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.", "id": "GoogleCloudAiplatformV1GroundingChunkImage" }, "GoogleCloudAiplatformV1TrajectoryExactMatchInput": { "id": "GoogleCloudAiplatformV1TrajectoryExactMatchInput", "type": "object", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1TrajectoryExactMatchSpec", "description": "Required. Spec for TrajectoryExactMatch metric." }, "instances": { "description": "Required. Repeated TrajectoryExactMatch instance.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1TrajectoryExactMatchInstance" } } }, "description": "Instances and metric spec for TrajectoryExactMatch metric." }, "GoogleCloudAiplatformV1BatchDedicatedResources": { "properties": { "machineSpec": { "description": "Required. Immutable. The specification of a single machine.", "$ref": "GoogleCloudAiplatformV1MachineSpec" }, "maxReplicaCount": { "description": "Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.", "format": "int32", "type": "integer" }, "startingReplicaCount": { "type": "integer", "description": "Immutable. The number of machine replicas used at the start of the batch operation. If not set, Agent Platform decides starting number, not greater than max_replica_count", "format": "int32" } }, "description": "A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.", "id": "GoogleCloudAiplatformV1BatchDedicatedResources", "type": "object" }, "GoogleCloudAiplatformV1ResourcePool": { "type": "object", "description": "Represents the spec of a group of resources of the same type, for example machine type, disk, and accelerators, in a PersistentResource.", "properties": { "replicaCount": { "type": "string", "format": "int64", "description": "Optional. The total number of machines to use for this resource pool." }, "autoscalingSpec": { "description": "Optional. Optional spec to configure GKE or Ray-on-Vertex autoscaling", "$ref": "GoogleCloudAiplatformV1ResourcePoolAutoscalingSpec" }, "machineSpec": { "description": "Required. Immutable. The specification of a single machine.", "$ref": "GoogleCloudAiplatformV1MachineSpec" }, "diskSpec": { "description": "Optional. Disk spec for the machine in this node pool.", "$ref": "GoogleCloudAiplatformV1DiskSpec" }, "id": { "type": "string", "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." }, "usedReplicaCount": { "description": "Output only. The number of machines currently in use by training jobs for this resource pool. Will replace idle_replica_count.", "readOnly": true, "format": "int64", "type": "string" } }, "id": "GoogleCloudAiplatformV1ResourcePool" }, "GoogleCloudAiplatformV1BleuInstance": { "id": "GoogleCloudAiplatformV1BleuInstance", "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." }, "GoogleCloudAiplatformV1RagFileChunkingConfigFixedLengthChunking": { "properties": { "chunkSize": { "description": "The size of the chunks.", "format": "int32", "type": "integer" }, "chunkOverlap": { "type": "integer", "description": "The overlap between chunks.", "format": "int32" } }, "id": "GoogleCloudAiplatformV1RagFileChunkingConfigFixedLengthChunking", "type": "object", "description": "Specifies the fixed length chunking config." }, "GoogleCloudAiplatformV1ListMemoriesResponse": { "type": "object", "description": "Response message for MemoryBankService.ListMemories.", "id": "GoogleCloudAiplatformV1ListMemoriesResponse", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListMemoriesRequest.page_token to obtain that page.", "type": "string" }, "memories": { "items": { "$ref": "GoogleCloudAiplatformV1Memory" }, "description": "List of Memories in the requested page.", "type": "array" } } }, "GoogleCloudAiplatformV1GenerateUserScenariosResponse": { "type": "object", "description": "Response message for DataFoundryService.GenerateUserScenarios.", "id": "GoogleCloudAiplatformV1GenerateUserScenariosResponse", "properties": { "userScenarios": { "description": "The generated user scenarios used to simulate multi-turn agent running results and agent evaluation.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1UserScenario" } } } }, "GoogleCloudAiplatformV1Explanation": { "description": "Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance.", "type": "object", "properties": { "neighbors": { "items": { "$ref": "GoogleCloudAiplatformV1Neighbor" }, "description": "Output only. List of the nearest neighbors for example-based explanations. For models deployed with the examples explanations feature enabled, the attributions field is empty and instead the neighbors field is populated.", "readOnly": true, "type": "array" }, "attributions": { "items": { "$ref": "GoogleCloudAiplatformV1Attribution" }, "type": "array", "readOnly": true, "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." } }, "id": "GoogleCloudAiplatformV1Explanation" }, "GoogleCloudAiplatformV1EmbedContentRequest": { "properties": { "taskType": { "enum": [ "UNSPECIFIED", "RETRIEVAL_QUERY", "RETRIEVAL_DOCUMENT", "SEMANTIC_SIMILARITY", "CLASSIFICATION", "CLUSTERING", "QUESTION_ANSWERING", "FACT_VERIFICATION", "CODE_RETRIEVAL_QUERY" ], "type": "string", "deprecated": true, "description": "Optional. Deprecated: Please use EmbedContentConfig.task_type instead. The task type of the embedding.", "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": { "deprecated": true, "type": "string", "description": "Optional. Deprecated: Please use EmbedContentConfig.title instead. The title for the text." }, "outputDimensionality": { "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", "format": "int32" }, "embedContentConfig": { "description": "Optional. Configuration for the EmbedContent request.", "$ref": "GoogleCloudAiplatformV1EmbedContentRequestEmbedContentConfig" }, "content": { "$ref": "GoogleCloudAiplatformV1Content", "description": "Required. The content to be embedded." }, "autoTruncate": { "deprecated": true, "type": "boolean", "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." } }, "id": "GoogleCloudAiplatformV1EmbedContentRequest", "description": "Request message for PredictionService.EmbedContent.", "type": "object" }, "GoogleCloudAiplatformV1PublisherModel": { "type": "object", "properties": { "name": { "readOnly": true, "description": "Output only. Identifier. The resource name of the PublisherModel.", "type": "string" }, "launchStage": { "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." ], "description": "Optional. Indicates the launch stage of the model.", "enum": [ "LAUNCH_STAGE_UNSPECIFIED", "EXPERIMENTAL", "PRIVATE_PREVIEW", "PUBLIC_PREVIEW", "GA" ], "type": "string" }, "frameworks": { "description": "Optional. Additional information about the model's Frameworks.", "type": "array", "items": { "type": "string" } }, "supportedActions": { "description": "Optional. Supported call-to-action options.", "$ref": "GoogleCloudAiplatformV1PublisherModelCallToAction" }, "versionState": { "type": "string", "enum": [ "VERSION_STATE_UNSPECIFIED", "VERSION_STATE_STABLE", "VERSION_STATE_UNSTABLE" ], "description": "Optional. Indicates the state of the model version.", "enumDescriptions": [ "The version state is unspecified.", "Used to indicate the version is stable.", "Used to indicate the version is unstable." ] }, "predictSchemata": { "description": "Optional. The schemata that describes formats of the PublisherModel's predictions and explanations as given and returned via PredictionService.Predict.", "$ref": "GoogleCloudAiplatformV1PredictSchemata" }, "publisherModelTemplate": { "description": "Optional. Output only. Immutable. Used to indicate this model has a publisher model and provide the template of the publisher model resource name.", "type": "string", "readOnly": true }, "versionId": { "type": "string", "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.", "readOnly": true }, "openSourceCategory": { "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" ], "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." ], "type": "string", "description": "Required. Indicates the open source category of the publisher model." } }, "description": "A Model Garden Publisher Model.", "id": "GoogleCloudAiplatformV1PublisherModel" }, "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateResponse": { "type": "object", "description": "Response message for VizierService.CheckTrialEarlyStoppingState.", "id": "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateResponse", "properties": { "shouldStop": { "description": "True if the Trial should stop.", "type": "boolean" } } }, "GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetail": { "type": "object", "description": "The detailed info for a custom job executor.", "properties": { "job": { "readOnly": true, "type": "string", "description": "Output only. The name of the CustomJob." }, "failedJobs": { "description": "Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.", "type": "array", "readOnly": true, "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetail" }, "GoogleCloudAiplatformV1NotebookExecutionJobDirectNotebookSource": { "description": "The content of the input notebook in ipynb format.", "type": "object", "properties": { "content": { "type": "string", "format": "byte", "description": "The base64-encoded contents of the input notebook file." } }, "id": "GoogleCloudAiplatformV1NotebookExecutionJobDirectNotebookSource" }, "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecSliceConfig": { "properties": { "value": { "description": "A unique specific value for a given feature. Example: `{ \"value\": { \"string_value\": \"12345\" } }`", "$ref": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecValue" }, "range": { "description": "A range of values for a numerical feature. Example: `{\"range\":{\"low\":10000.0,\"high\":50000.0}}` will capture 12345 and 23334 in the slice.", "$ref": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecRange" }, "allValues": { "type": "boolean", "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}}`" } }, "id": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecSliceConfig", "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.", "type": "object" }, "GenaiVertexV1ArgumentsDelta": { "type": "object", "id": "GenaiVertexV1ArgumentsDelta", "properties": { "arguments": { "type": "string" } } }, "GoogleCloudAiplatformV1EvaluatedAnnotationExplanation": { "description": "Explanation result of the prediction produced by the Model.", "properties": { "explanationType": { "description": "Explanation type. For AutoML Image Classification models, possible values are: * `image-integrated-gradients` * `image-xrai`", "type": "string" }, "explanation": { "$ref": "GoogleCloudAiplatformV1Explanation", "description": "Explanation attribution response details." } }, "type": "object", "id": "GoogleCloudAiplatformV1EvaluatedAnnotationExplanation" }, "GoogleCloudAiplatformV1GenerateMemoriesRequestVertexSessionSource": { "description": "Defines an Agent Engine Session from which to generate the memories. If `scope` is not provided, the scope will be extracted from the Session (i.e. {\"user_id\": sesison.user_id}).", "properties": { "session": { "description": "Required. The resource name of the Session to generate memories for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "type": "string" }, "endTime": { "type": "string", "description": "Optional. End time (exclusive) of the time range. If not set, the end time is unbounded.", "format": "google-datetime" }, "startTime": { "format": "google-datetime", "description": "Optional. Time range to define which session events should be used to generate memories. Start time (inclusive) of the time range. If not set, the start time is unbounded.", "type": "string" } }, "id": "GoogleCloudAiplatformV1GenerateMemoriesRequestVertexSessionSource", "type": "object" }, "GoogleCloudAiplatformV1FeatureOnlineStoreBigtableBigtableMetadata": { "description": "Metadata of the Bigtable instance. This is used by direct read access to the Bigtable in tenant project.", "type": "object", "properties": { "tenantProjectId": { "description": "Tenant project ID.", "type": "string" }, "instanceId": { "type": "string", "description": "The Cloud Bigtable instance id." }, "tableId": { "description": "The Cloud Bigtable table id.", "type": "string" } }, "id": "GoogleCloudAiplatformV1FeatureOnlineStoreBigtableBigtableMetadata" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionCustomTask": { "description": "A TrainingJob that trains a custom code Model.", "properties": { "inputs": { "$ref": "GoogleCloudAiplatformV1CustomJobSpec", "description": "The input parameters of this CustomTask." }, "metadata": { "description": "The metadata information.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionCustomJobMetadata" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionCustomTask" }, "GoogleCloudAiplatformV1PairwiseSummarizationQualityInput": { "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1PairwiseSummarizationQualityInstance", "description": "Required. Pairwise summarization quality instance." }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1PairwiseSummarizationQualitySpec", "description": "Required. Spec for pairwise summarization quality score metric." } }, "id": "GoogleCloudAiplatformV1PairwiseSummarizationQualityInput", "description": "Input for pairwise summarization quality metric.", "type": "object" }, "GoogleCloudAiplatformV1BatchMigrateResourcesOperationMetadataPartialResult": { "id": "GoogleCloudAiplatformV1BatchMigrateResourcesOperationMetadataPartialResult", "description": "Represents a partial result in batch migration operation for one MigrateResourceRequest.", "properties": { "error": { "$ref": "GoogleRpcStatus", "description": "The error result of the migration request in case of failure." }, "model": { "description": "Migrated model resource name.", "type": "string" }, "dataset": { "type": "string", "description": "Migrated dataset resource name." }, "request": { "description": "It's the same as the value in BatchMigrateResourcesRequest.migrate_resource_requests.", "$ref": "GoogleCloudAiplatformV1MigrateResourceRequest" } }, "type": "object" }, "GoogleCloudAiplatformV1PublisherModelCallToActionOpenFineTuningPipelines": { "properties": { "fineTuningPipelines": { "description": "Required. Regional resource references to fine tuning pipelines.", "items": { "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" }, "type": "array" } }, "id": "GoogleCloudAiplatformV1PublisherModelCallToActionOpenFineTuningPipelines", "description": "Open fine tuning pipelines.", "type": "object" }, "GoogleCloudAiplatformV1TokensInfo": { "properties": { "tokens": { "type": "array", "items": { "type": "string", "format": "byte" }, "description": "A list of tokens from the input." }, "role": { "type": "string", "description": "Optional. Optional fields for the role from the corresponding Content." }, "tokenIds": { "description": "A list of token ids from the input.", "items": { "type": "string", "format": "int64" }, "type": "array" } }, "description": "Tokens info with a list of tokens and the corresponding list of token ids.", "id": "GoogleCloudAiplatformV1TokensInfo", "type": "object" }, "GoogleCloudAiplatformV1ToolCallValidInstance": { "properties": { "prediction": { "type": "string", "description": "Required. Output of the evaluated model." }, "reference": { "description": "Required. Ground truth used to compare against the prediction.", "type": "string" } }, "id": "GoogleCloudAiplatformV1ToolCallValidInstance", "description": "Spec for tool call valid instance.", "type": "object" }, "GoogleCloudAiplatformV1RagRetrievalConfigRankingLlmRanker": { "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" } }, "description": "Config for LlmRanker.", "id": "GoogleCloudAiplatformV1RagRetrievalConfigRankingLlmRanker", "type": "object" }, "GoogleCloudAiplatformV1ListFeaturestoresResponse": { "properties": { "featurestores": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Featurestore" }, "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" } }, "type": "object", "description": "Response message for FeaturestoreService.ListFeaturestores.", "id": "GoogleCloudAiplatformV1ListFeaturestoresResponse" }, "GoogleCloudAiplatformV1PredictResponse": { "description": "Response message for PredictionService.Predict.", "id": "GoogleCloudAiplatformV1PredictResponse", "type": "object", "properties": { "model": { "description": "Output only. The resource name of the Model which is deployed as the DeployedModel that this prediction hits.", "readOnly": true, "type": "string" }, "deployedModelId": { "description": "ID of the Endpoint's DeployedModel that served this prediction.", "type": "string" }, "metadata": { "description": "Output only. Request-level metadata returned by the model. The metadata type will be dependent upon the model implementation.", "type": "any", "readOnly": true }, "modelDisplayName": { "type": "string", "readOnly": true, "description": "Output only. The display name of the Model which is deployed as the DeployedModel that this prediction hits." }, "predictions": { "type": "array", "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.", "items": { "type": "any" } }, "modelVersionId": { "description": "Output only. The version ID of the Model which is deployed as the DeployedModel that this prediction hits.", "type": "string", "readOnly": true } } }, "GoogleCloudAiplatformV1TrialParameter": { "description": "A message representing a parameter to be tuned.", "properties": { "parameterId": { "readOnly": true, "type": "string", "description": "Output only. The ID of the parameter. The parameter should be defined in StudySpec's Parameters." }, "value": { "readOnly": true, "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'.", "type": "any" } }, "type": "object", "id": "GoogleCloudAiplatformV1TrialParameter" }, "GoogleCloudAiplatformV1FeatureGroupBigQueryTimeSeries": { "properties": { "timestampColumn": { "type": "string", "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." } }, "id": "GoogleCloudAiplatformV1FeatureGroupBigQueryTimeSeries", "type": "object" }, "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationMaskAnnotation": { "id": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationMaskAnnotation", "properties": { "maskGcsUri": { "type": "string", "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." }, "annotationSpecColors": { "type": "array", "description": "The mapping between color and AnnotationSpec for this Annotation.", "items": { "$ref": "GoogleCloudAiplatformV1SchemaAnnotationSpecColor" } } }, "type": "object", "description": "The mask based segmentation annotation." }, "GoogleCloudAiplatformV1UndeployModelOperationMetadata": { "id": "GoogleCloudAiplatformV1UndeployModelOperationMetadata", "description": "Runtime operation information for EndpointService.UndeployModel.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The operation generic information." } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaPredictPredictionClassificationPredictionResult": { "id": "GoogleCloudAiplatformV1SchemaPredictPredictionClassificationPredictionResult", "properties": { "ids": { "type": "array", "items": { "format": "int64", "type": "string" }, "description": "The resource IDs of the AnnotationSpecs that had been identified." }, "confidences": { "description": "The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids.", "type": "array", "items": { "format": "float", "type": "number" } }, "displayNames": { "type": "array", "items": { "type": "string" }, "description": "The display names of the AnnotationSpecs that had been identified, order matches the IDs." } }, "type": "object", "description": "Prediction output format for Image and Text Classification." }, "GoogleCloudAiplatformV1PointwiseMetricInstance": { "properties": { "jsonInstance": { "description": "Instance specified as a json string. String key-value pairs are expected in the json_instance to render PointwiseMetricSpec.instance_prompt_template.", "type": "string" }, "contentMapInstance": { "description": "Key-value contents for the mutlimodality input, including text, image, video, audio, and pdf, etc. The key is placeholder in metric prompt template, and the value is the multimodal content.", "$ref": "GoogleCloudAiplatformV1ContentMap" } }, "description": "Pointwise metric instance. Usually one instance corresponds to one row in an evaluation dataset.", "id": "GoogleCloudAiplatformV1PointwiseMetricInstance", "type": "object" }, "GoogleCloudAiplatformV1ModelEvaluationSliceSlice": { "description": "Definition of a slice.", "properties": { "dimension": { "readOnly": true, "type": "string", "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." }, "value": { "readOnly": true, "description": "Output only. The value of the dimension in this slice.", "type": "string" }, "sliceSpec": { "description": "Output only. Specification for how the data was sliced.", "$ref": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpec", "readOnly": true } }, "id": "GoogleCloudAiplatformV1ModelEvaluationSliceSlice", "type": "object" }, "GoogleCloudAiplatformV1AutoscalingMetricSpec": { "id": "GoogleCloudAiplatformV1AutoscalingMetricSpec", "properties": { "metricName": { "type": "string", "description": "Required. The resource metric name. Supported metrics: * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle` * `aiplatform.googleapis.com/prediction/online/cpu/utilization` * `aiplatform.googleapis.com/prediction/online/request_count` * `pubsub.googleapis.com/subscription/num_undelivered_messages` * `prometheus.googleapis.com/vertex_dcgm_fi_dev_gpu_util` * `prometheus.googleapis.com/vertex_vllm_gpu_cache_usage_perc` * `prometheus.googleapis.com/vertex_vllm_num_requests_waiting`" }, "target": { "type": "integer", "format": "int32", "description": "The target resource utilization in percentage (1% - 100%) for the given metric; once the real usage deviates from the target by a certain percentage, the machine replicas change. The default value is 60 (representing 60%) if not provided." } }, "description": "The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.", "type": "object" }, "GenaiVertexV1ToolResultStep": { "id": "GenaiVertexV1ToolResultStep", "type": "object", "properties": { "googleSearchResult": { "$ref": "GenaiVertexV1GoogleSearchResultStep" }, "retrievalResult": { "$ref": "GenaiVertexV1RetrievalResultStep" }, "urlContextResult": { "$ref": "GenaiVertexV1UrlContextResultStep" }, "processingResult": { "$ref": "GenaiVertexV1ProcessingResultStep" }, "callId": { "type": "string", "description": "Required. ID to match the ID from the function call block." }, "signature": { "description": "A signature hash for backend validation.", "format": "byte", "type": "string" }, "codeExecutionResult": { "$ref": "GenaiVertexV1CodeExecutionResultStep" }, "fileSearchResult": { "$ref": "GenaiVertexV1FileSearchResultStep" }, "functionResult": { "$ref": "GenaiVertexV1FunctionResultStep" }, "googleMapsResult": { "$ref": "GenaiVertexV1GoogleMapsResultStep" } }, "description": "Tool result step." }, "GoogleCloudAiplatformV1Trajectory": { "description": "Spec for trajectory.", "properties": { "toolCalls": { "items": { "$ref": "GoogleCloudAiplatformV1ToolCall" }, "description": "Required. Tool calls in the trajectory.", "type": "array" } }, "id": "GoogleCloudAiplatformV1Trajectory", "type": "object" }, "GoogleCloudAiplatformV1ModelEvaluationSlice": { "type": "object", "id": "GoogleCloudAiplatformV1ModelEvaluationSlice", "description": "A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations.", "properties": { "metricsSchemaUri": { "type": "string", "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 }, "modelExplanation": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1ModelExplanation", "description": "Output only. Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for tabular Models." }, "name": { "description": "Output only. The resource name of the ModelEvaluationSlice.", "readOnly": true, "type": "string" }, "createTime": { "type": "string", "description": "Output only. Timestamp when this ModelEvaluationSlice was created.", "format": "google-datetime", "readOnly": true }, "slice": { "description": "Output only. The slice of the test data that is used to evaluate the Model.", "$ref": "GoogleCloudAiplatformV1ModelEvaluationSliceSlice", "readOnly": true }, "metrics": { "readOnly": true, "type": "any", "description": "Output only. Sliced evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri" } } }, "GoogleCloudAiplatformV1ComputeTokensResponse": { "description": "Response message for ComputeTokens RPC call.", "id": "GoogleCloudAiplatformV1ComputeTokensResponse", "type": "object", "properties": { "tokensInfo": { "items": { "$ref": "GoogleCloudAiplatformV1TokensInfo" }, "type": "array", "description": "Lists of tokens info from the input. A ComputeTokensRequest could have multiple instances with a prompt in each instance. We also need to return lists of tokens info for the request with multiple instances." } } }, "GoogleCloudAiplatformV1FeatureViewBigQuerySource": { "id": "GoogleCloudAiplatformV1FeatureViewBigQuerySource", "type": "object", "properties": { "uri": { "type": "string", "description": "Required. The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig." }, "entityIdColumns": { "description": "Required. Columns to construct entity_id / row keys.", "items": { "type": "string" }, "type": "array" } } }, "GoogleCloudAiplatformV1CreateServingProfileOperationMetadata": { "id": "GoogleCloudAiplatformV1CreateServingProfileOperationMetadata", "description": "Runtime operation metadata for ServingProfileService.CreateServingProfile.", "properties": { "genericMetadata": { "description": "Output only. The standard operation metadata for Vertex AI.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "type": "object" }, "GoogleCloudAiplatformV1ToolParameterKeyMatchSpec": { "description": "Spec for tool parameter key match metric.", "properties": {}, "type": "object", "id": "GoogleCloudAiplatformV1ToolParameterKeyMatchSpec" }, "GoogleCloudAiplatformV1PipelineJobDetail": { "type": "object", "id": "GoogleCloudAiplatformV1PipelineJobDetail", "properties": { "taskDetails": { "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1PipelineTaskDetail" }, "type": "array", "description": "Output only. The runtime details of the tasks under the pipeline." }, "pipelineContext": { "description": "Output only. The context of the pipeline.", "$ref": "GoogleCloudAiplatformV1Context", "readOnly": true }, "pipelineRunContext": { "readOnly": true, "description": "Output only. The context of the current pipeline run.", "$ref": "GoogleCloudAiplatformV1Context" } }, "description": "The runtime detail of PipelineJob." }, "GoogleCloudAiplatformV1FeatureViewSync": { "description": "FeatureViewSync is a representation of sync operation which copies data from data source to Feature View in Online Store.", "id": "GoogleCloudAiplatformV1FeatureViewSync", "properties": { "satisfiesPzs": { "type": "boolean", "description": "Output only. Reserved for future use.", "readOnly": true }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "createTime": { "description": "Output only. Time when this FeatureViewSync is created. Creation of a FeatureViewSync means that the job is pending / waiting for sufficient resources but may not have started the actual data transfer yet.", "type": "string", "format": "google-datetime", "readOnly": true }, "name": { "type": "string", "description": "Identifier. Name of the FeatureViewSync. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`" }, "syncSummary": { "readOnly": true, "description": "Output only. Summary of the sync job.", "$ref": "GoogleCloudAiplatformV1FeatureViewSyncSyncSummary" }, "runTime": { "readOnly": true, "$ref": "GoogleTypeInterval", "description": "Output only. Time when this FeatureViewSync is finished." }, "finalStatus": { "$ref": "GoogleRpcStatus", "readOnly": true, "description": "Output only. Final status of the FeatureViewSync." } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation": { "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.", "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation", "properties": { "columnName": { "type": "string" } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputs": { "type": "object", "properties": { "availableAtForecastColumns": { "items": { "type": "string" }, "type": "array", "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": { "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.", "type": "array" }, "unavailableAtForecastColumns": { "type": "array", "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.", "items": { "type": "string" } }, "quantiles": { "items": { "type": "number", "format": "double" }, "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" }, "hierarchyConfig": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHierarchyConfig", "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies." }, "optimizationObjective": { "type": "string", "description": "Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). * \"minimize-mae\" - Minimize mean-absolute error (MAE). * \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE). * \"minimize-rmspe\" - Minimize root-mean-squared percentage error (RMSPE). * \"minimize-wape-mae\" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * \"minimize-quantile-loss\" - Minimize the quantile loss at the quantiles defined in `quantiles`. * \"minimize-mape\" - Minimize the mean absolute percentage error." }, "weightColumn": { "type": "string", "description": "Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1. This column must be available at forecast." }, "dataGranularity": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsGranularity", "description": "Expected difference in time granularity between rows in the data." }, "additionalExperiments": { "items": { "type": "string" }, "type": "array", "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" }, "forecastHorizon": { "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", "type": "string" }, "transformations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformation" }, "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter." }, "validationOptions": { "type": "string", "description": "Validation options for the data validation component. The available options are: * \"fail-pipeline\" - default, will validate against the validation and fail the pipeline if it fails. * \"ignore-validation\" - ignore the results of the validation and continue" }, "timeSeriesAttributeColumns": { "description": "Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.", "type": "array", "items": { "type": "string" } }, "timeColumn": { "description": "The name of the column that identifies time order in the time series. This column must be available at forecast.", "type": "string" }, "windowConfig": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig", "description": "Config containing strategy for generating sliding windows." }, "trainBudgetMilliNodeHours": { "type": "string", "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" }, "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" }, "timeSeriesIdentifierColumn": { "description": "The name of the column that identifies the time series.", "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.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputs" }, "GoogleCloudAiplatformV1SyncFeatureViewResponse": { "description": "Response message for FeatureOnlineStoreAdminService.SyncFeatureView.", "properties": { "featureViewSync": { "description": "Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`", "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1SyncFeatureViewResponse" }, "GoogleCloudAiplatformV1UpdateDeploymentResourcePoolOperationMetadata": { "description": "Runtime operation information for UpdateDeploymentResourcePool method.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The operation generic information." } }, "type": "object", "id": "GoogleCloudAiplatformV1UpdateDeploymentResourcePoolOperationMetadata" }, "GoogleCloudAiplatformV1DatasetCustomMetric": { "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": { "type": "string", "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} ] }" } }, "description": "Defines a custom dataset-level aggregation.", "id": "GoogleCloudAiplatformV1DatasetCustomMetric" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation": { "type": "object", "properties": { "numeric": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation" }, "categorical": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation" }, "text": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation" }, "timestamp": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation" }, "auto": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation" }, "GoogleCloudAiplatformV1SchemaPromptSpecStructuredPrompt": { "description": "Prompt variation that stores preambles in separate fields.", "id": "GoogleCloudAiplatformV1SchemaPromptSpecStructuredPrompt", "properties": { "predictionInputs": { "description": "Preamble: The input test data for prediction. Each PartList in this field represents one text-only input set for a single model request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecPartList" } }, "promptMessage": { "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecPromptMessage", "description": "The prompt message." }, "inputPrefixes": { "type": "array", "description": "Preamble: The input prefixes before each example input.", "items": { "type": "string" } }, "infillPrefix": { "type": "string", "description": "Preamble: For infill prompt, the prefix before expected model response." }, "interactionData": { "description": "Data for interaction use case.", "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecInteractionData" }, "examples": { "description": "Preamble: A set of examples for expected model response.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecPartList" } }, "contentMetadata": { "items": { "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecContentMetadata" }, "type": "array", "description": "Optional. Metadata the model returned with each of `prompt_message.contents`, such as citations and grounding sources. This maps 1:1 to PromptMessage.contents; an entry is empty when its content has no metadata." }, "outputPrefixes": { "type": "array", "items": { "type": "string" }, "description": "Preamble: The output prefixes before each example output." }, "appBuilderData": { "description": "Data for app builder use case.", "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecAppBuilderData" }, "infillSuffix": { "description": "Preamble: For infill prompt, the suffix after expected model response.", "type": "string" }, "context": { "description": "Preamble: The context of the prompt.", "$ref": "GoogleCloudAiplatformV1Content" } }, "type": "object" }, "GoogleCloudAiplatformV1EntityType": { "type": "object", "properties": { "etag": { "type": "string", "description": "Optional. Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" }, "createTime": { "readOnly": true, "description": "Output only. Timestamp when this EntityType was created.", "format": "google-datetime", "type": "string" }, "monitoringConfig": { "$ref": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfig", "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." }, "name": { "type": "string", "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." }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this EntityType was most recently updated.", "type": "string", "readOnly": true }, "description": { "description": "Optional. Description of the EntityType.", "type": "string" }, "labels": { "additionalProperties": { "type": "string" }, "type": "object", "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." }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" }, "offlineStorageTtlDays": { "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.", "type": "integer", "format": "int32" } }, "id": "GoogleCloudAiplatformV1EntityType", "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." }, "GoogleCloudAiplatformV1RagEmbeddingModelConfig": { "id": "GoogleCloudAiplatformV1RagEmbeddingModelConfig", "type": "object", "properties": { "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": "GoogleCloudAiplatformV1RagEmbeddingModelConfigVertexPredictionEndpoint" } }, "description": "Config for the embedding model to use for RAG." }, "GoogleCloudAiplatformV1PurgeContextsResponse": { "type": "object", "description": "Response message for MetadataService.PurgeContexts.", "properties": { "purgeSample": { "items": { "type": "string" }, "type": "array", "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)." }, "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" } }, "id": "GoogleCloudAiplatformV1PurgeContextsResponse" }, "GoogleCloudAiplatformV1GoogleMapsPlaces": { "type": "object", "id": "GoogleCloudAiplatformV1GoogleMapsPlaces", "properties": {}, "description": "Grounding with Google Maps Places data (e.g. QueryPlaces). This is the default Google Maps grounding type when no other type is specified." }, "GoogleCloudAiplatformV1ListDataItemsResponse": { "type": "object", "properties": { "nextPageToken": { "type": "string", "description": "The standard List next-page token." }, "dataItems": { "items": { "$ref": "GoogleCloudAiplatformV1DataItem" }, "type": "array", "description": "A list of DataItems that matches the specified filter in the request." } }, "id": "GoogleCloudAiplatformV1ListDataItemsResponse", "description": "Response message for DatasetService.ListDataItems." }, "GoogleCloudAiplatformV1StreamRawPredictRequest": { "type": "object", "id": "GoogleCloudAiplatformV1StreamRawPredictRequest", "description": "Request message for PredictionService.StreamRawPredict.", "properties": { "httpBody": { "description": "The prediction input. Supports HTTP headers and arbitrary data payload.", "$ref": "GoogleApiHttpBody" } } }, "GoogleCloudAiplatformV1SchemaPredictPredictionTabularRegressionPredictionResult": { "properties": { "quantilePredictions": { "description": "Quantile predictions, in 1-1 correspondence with quantile_values.", "items": { "format": "float", "type": "number" }, "type": "array" }, "lowerBound": { "format": "float", "type": "number", "description": "The lower bound of the prediction interval." }, "upperBound": { "format": "float", "type": "number", "description": "The upper bound of the prediction interval." }, "quantileValues": { "type": "array", "description": "Quantile values.", "items": { "format": "float", "type": "number" } }, "value": { "format": "float", "type": "number", "description": "The regression value." } }, "description": "Prediction output format for Tabular Regression.", "type": "object", "id": "GoogleCloudAiplatformV1SchemaPredictPredictionTabularRegressionPredictionResult" }, "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecDeveloperConnectConfig": { "properties": { "gitRepositoryLink": { "description": "Required. The Developer Connect Git repository link, formatted as `projects/*/locations/*/connections/*/gitRepositoryLink/*`.", "type": "string" }, "dir": { "description": "Required. Directory, relative to the source root, in which to run the build.", "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" } }, "id": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecDeveloperConnectConfig", "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.", "type": "object" }, "GoogleCloudAiplatformV1SuspendOnlineEvaluatorOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Common part of operation metadata." } }, "id": "GoogleCloudAiplatformV1SuspendOnlineEvaluatorOperationMetadata", "type": "object", "description": "Metadata for the SuspendOnlineEvaluator operation." }, "GoogleCloudAiplatformV1PublisherModelCallToActionDeploy": { "properties": { "largeModelReference": { "description": "Optional. Large model reference. When this is set, model_artifact_spec is not needed.", "$ref": "GoogleCloudAiplatformV1LargeModelReference" }, "deployTaskName": { "type": "string", "description": "Optional. The name of the deploy task (e.g., \"text to image generation\")." }, "automaticResources": { "description": "A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.", "$ref": "GoogleCloudAiplatformV1AutomaticResources" }, "title": { "description": "Required. The title of the regional resource reference.", "type": "string" }, "publicArtifactUri": { "description": "Optional. The signed URI for ephemeral Cloud Storage access to model artifact.", "type": "string" }, "artifactUri": { "description": "Optional. The path to the directory containing the Model artifact and any of its supporting files.", "type": "string" }, "deployMetadata": { "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionDeployDeployMetadata", "description": "Optional. Metadata information about this deployment config." }, "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.", "$ref": "GoogleCloudAiplatformV1ModelContainerSpec" }, "modelDisplayName": { "type": "string", "description": "Optional. Default model display name." }, "sharedResources": { "type": "string", "description": "The resource name of the shared DeploymentResourcePool to deploy on. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`" }, "dedicatedResources": { "description": "A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.", "$ref": "GoogleCloudAiplatformV1DedicatedResources" } }, "type": "object", "id": "GoogleCloudAiplatformV1PublisherModelCallToActionDeploy", "description": "Model metadata that is needed for UploadModel or DeployModel/CreateEndpoint requests." }, "GoogleCloudAiplatformV1ModelExportFormat": { "description": "Represents export format supported by the Model. All formats export to Google Cloud Storage.", "id": "GoogleCloudAiplatformV1ModelExportFormat", "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": { "type": "array", "readOnly": true, "description": "Output only. The content of this Model that may be exported.", "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." ] } } }, "type": "object" }, "GoogleCloudAiplatformV1GenerateContentResponsePromptFeedback": { "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.", "id": "GoogleCloudAiplatformV1GenerateContentResponsePromptFeedback", "properties": { "blockReason": { "readOnly": true, "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." ], "type": "string", "description": "Output only. The reason why the prompt was blocked.", "enum": [ "BLOCKED_REASON_UNSPECIFIED", "SAFETY", "OTHER", "BLOCKLIST", "PROHIBITED_CONTENT", "MODEL_ARMOR", "IMAGE_SAFETY", "JAILBREAK" ] }, "safetyRatings": { "description": "Output only. A list of safety ratings for the prompt. There is one rating per category.", "type": "array", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1SafetyRating" } }, "blockReasonMessage": { "description": "Output only. A readable message that explains the reason why the prompt was blocked.", "type": "string", "readOnly": true } }, "type": "object" }, "GenaiVertexV1VideoConfig": { "id": "GenaiVertexV1VideoConfig", "description": "Configuration options for video generation.", "properties": { "task": { "type": "string", "enum": [ "TASK_UNSPECIFIED", "TEXT_TO_VIDEO", "IMAGE_TO_VIDEO", "REFERENCE_TO_VIDEO", "EDIT", "EXTEND" ], "description": "Optional task mode for video generation. If not specified, the model automatically determines the appropriate mode based on the provided text prompt and input media.", "enumDescriptions": [ "Unspecified task. The task is inferred from the input prompt and media.", "Generates video solely from a text prompt.", "Generates video from one or two source images. The first image defines the starting frame, and the optional second image defines the ending frame.", "Generates video using reference media (such as images, audio, or video).", "Modifies an existing input video.", "Extends an existing input video." ] } }, "type": "object" }, "GenaiVertexV1AllowedTools": { "id": "GenaiVertexV1AllowedTools", "type": "object", "description": "The configuration for allowed tools.", "properties": { "mode": { "enum": [ "TOOL_CHOICE_TYPE_UNSPECIFIED", "AUTO", "ANY", "NONE", "VALIDATED" ], "enumDescriptions": [ "Default value. This value is unused.", "Auto tool choice.", "Any tool choice.", "No tool choice.", "Validated tool choice." ], "type": "string", "description": "The mode of the tool choice." }, "tools": { "items": { "type": "string" }, "description": "The names of the allowed tools.", "type": "array" } } }, "GoogleCloudAiplatformV1TensorboardRun": { "type": "object", "properties": { "createTime": { "type": "string", "readOnly": true, "format": "google-datetime", "description": "Output only. Timestamp when this TensorboardRun was created." }, "etag": { "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "labels": { "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.", "type": "object" }, "updateTime": { "description": "Output only. Timestamp when this TensorboardRun was last updated.", "type": "string", "format": "google-datetime", "readOnly": true }, "displayName": { "type": "string", "description": "Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment." }, "description": { "type": "string", "description": "Description of this TensorboardRun." }, "name": { "type": "string", "readOnly": true, "description": "Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`" } }, "description": "TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc", "id": "GoogleCloudAiplatformV1TensorboardRun" }, "GoogleCloudAiplatformV1KeepAliveProbe": { "id": "GoogleCloudAiplatformV1KeepAliveProbe", "type": "object", "properties": { "maxSeconds": { "type": "integer", "format": "int32", "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)." }, "httpGet": { "description": "Optional. Specifies the HTTP GET configuration for the probe.", "$ref": "GoogleCloudAiplatformV1KeepAliveProbeHttpGet" } }, "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." }, "GoogleCloudAiplatformV1CancelAsyncQueryReasoningEngineRequest": { "description": "Request message for ReasoningEngineExecutionService.CancelAsyncQueryReasoningEngine.", "type": "object", "properties": { "operationName": { "type": "string", "description": "Required. The name of the longrunning operation returned from AsyncQueryReasoningEngine. Format: `projects/{project}/locations/{location}/operations/{operation}`" } }, "id": "GoogleCloudAiplatformV1CancelAsyncQueryReasoningEngineRequest" }, "GoogleCloudAiplatformV1SchemaPredictPredictionTextExtractionPredictionResult": { "description": "Prediction output format for Text Extraction.", "type": "object", "properties": { "textSegmentEndOffsets": { "type": "array", "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.", "items": { "type": "string", "format": "int64" } }, "displayNames": { "description": "The display names of the AnnotationSpecs that had been identified, order matches the IDs.", "items": { "type": "string" }, "type": "array" }, "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": { "format": "int64", "type": "string" } }, "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" } }, "ids": { "type": "array", "description": "The resource IDs of the AnnotationSpecs that had been identified, ordered by the confidence score descendingly.", "items": { "type": "string", "format": "int64" } } }, "id": "GoogleCloudAiplatformV1SchemaPredictPredictionTextExtractionPredictionResult" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHierarchyConfig": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHierarchyConfig", "properties": { "temporalTotalWeight": { "type": "number", "description": "The weight of the loss for predictions aggregated over the horizon for a single time series.", "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" } }, "groupTotalWeight": { "format": "double", "description": "The weight of the loss for predictions aggregated over time series in the same group.", "type": "number" }, "groupTemporalTotalWeight": { "type": "number", "description": "The weight of the loss for predictions aggregated over both the horizon and time series in the same hierarchy group.", "format": "double" } }, "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies." }, "GenaiVertexV1ThoughtSignatureDelta": { "properties": { "signature": { "type": "string", "description": "Signature to match the backend source to be part of the generation.", "format": "byte" } }, "id": "GenaiVertexV1ThoughtSignatureDelta", "type": "object" }, "GoogleCloudAiplatformV1VoiceConfig": { "type": "object", "properties": { "replicatedVoiceConfig": { "description": "Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.", "$ref": "GoogleCloudAiplatformV1ReplicatedVoiceConfig" }, "voice": { "description": "Optional. The speaker identifier for synthesis. Supported formats: * Speaker name for prebuilt voices (for example, `Orus` or `Kore`). * Voice ID for stored voices (for example, `voice_xxx`). * Voice replication key (for example, `voicekey_xxx`).", "type": "string" }, "prebuiltVoiceConfig": { "description": "The configuration for a prebuilt voice.", "$ref": "GoogleCloudAiplatformV1PrebuiltVoiceConfig" } }, "id": "GoogleCloudAiplatformV1VoiceConfig", "description": "Configuration for a voice." }, "GoogleCloudAiplatformV1GatewayConfig": { "description": "Configuration for a single gateway.", "properties": { "dnsZoneName": { "description": "Optional. Name of the private Cloud DNS managed zone in which to create the gateway's A-record. This is the managed zone's own name, not its DNS name: for a zone serving `example.internal.`, this field takes the zone name, such as `my-private-zone`. The zone's DNS name is combined with a generated per-gateway label to form the record's fully qualified name, which must stay within the 255-octet DNS limit. If the full name is too long, gateway provisioning fails when it attempts to create the DNS record.", "type": "string" }, "ipAddress": { "readOnly": true, "type": "string", "description": "Output only. The private IP address of the PSC endpoint." }, "subnetwork": { "type": "string", "description": "Optional. The URI of the subnetwork resource where PSC-E will be provisioned. if not provided `default` subnet will be used from the same {location} Format: projects/{project}/regions/{region}/subnetworks/{subnetwork}" }, "state": { "enum": [ "STATE_UNSPECIFIED", "PROVISIONING", "ACTIVE", "DEPROVISIONING", "INACTIVE", "FAILED" ], "type": "string", "readOnly": true, "description": "Output only. The state of the Gateway configuration.", "enumDescriptions": [ "The default value. This value is used if the state is omitted.", "The Gateway is being provisioned.", "The Gateway is active and ready to use.", "The Gateway is being de-provisioned.", "The Gateway is inactive.", "The Gateway failed to be provisioned." ] }, "dnsRecord": { "readOnly": true, "description": "Output only. The fully qualified record name of the created A-record in Cloud DNS.", "type": "string" }, "network": { "description": "Optional. The URI of the network resource where PSC-E will be provisioned. if not provided `default` network will be used. Format: projects/{project}/global/networks/{network}", "type": "string" }, "pscEndpoint": { "readOnly": true, "type": "string", "description": "Output only. The self-link or name of the Private Service Connect endpoint forwarding rule." }, "allowedProjects": { "items": { "type": "string" }, "description": "Optional. Additional consumer projects permitted to attach their own PSC endpoint to this gateway's ServiceAttachment. This is the \"decoupled\" mode, where the customer creates the PSC endpoint in a project other than this gateway's `network` project. Each listed project is VPC-SC enforced: it must be within the caller's service perimeter. The owning SemanticGovernancePolicyEngine's own project is always permitted implicitly and need not be listed. Format: `projects/{project}` (ID or number).", "type": "array" } }, "type": "object", "id": "GoogleCloudAiplatformV1GatewayConfig" }, "GoogleCloudAiplatformV1MemoryBankCustomizationConfigMemoryTopicCustomMemoryTopic": { "id": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigMemoryTopicCustomMemoryTopic", "properties": { "description": { "description": "Required. Represents the description of the memory topic. This should explain what information should be extracted for this topic.", "type": "string" }, "label": { "description": "Required. Represents the label of the topic.", "type": "string" } }, "description": "A custom memory topic defined by the developer.", "type": "object" }, "GoogleCloudAiplatformV1PublisherModelCallToActionViewRestApi": { "type": "object", "properties": { "title": { "type": "string", "description": "Required. The title of the view rest API." }, "documentations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1PublisherModelDocumentation" }, "description": "Required." } }, "id": "GoogleCloudAiplatformV1PublisherModelCallToActionViewRestApi", "description": "Rest API docs." }, "GoogleCloudAiplatformV1NotebookReservationAffinity": { "type": "object", "description": "Notebook Reservation Affinity for consuming Zonal reservation.", "properties": { "values": { "type": "array", "items": { "type": "string" }, "description": "Optional. Corresponds to the label values of a reservation resource. This must be the full path name of Reservation." }, "consumeReservationType": { "type": "string", "enum": [ "RESERVATION_AFFINITY_TYPE_UNSPECIFIED", "RESERVATION_NONE", "RESERVATION_ANY", "RESERVATION_SPECIFIC" ], "description": "Required. Specifies the type of reservation from which this instance can consume resources: RESERVATION_ANY (default), RESERVATION_SPECIFIC, or RESERVATION_NONE. See Consuming reserved instances for examples.", "enumDescriptions": [ "Default type.", "Do not consume from any allocated capacity.", "Consume any reservation available.", "Must consume from a specific reservation. Must specify key value fields for specifying the reservations." ] }, "key": { "type": "string", "description": "Optional. Corresponds to the label key of a reservation resource. To target a RESERVATION_SPECIFIC by name, use compute.googleapis.com/reservation-name as the key and specify the name of your reservation as its value." } }, "id": "GoogleCloudAiplatformV1NotebookReservationAffinity" }, "GoogleCloudAiplatformV1ExecuteSandboxEnvironmentRequest": { "description": "Request message for SandboxEnvironmentExecutionService.Execute.", "type": "object", "properties": { "inputs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Chunk" }, "description": "Required. The inputs to the sandbox environment." } }, "id": "GoogleCloudAiplatformV1ExecuteSandboxEnvironmentRequest" }, "GoogleCloudAiplatformV1RagVectorDbConfigRagManagedDbKNN": { "description": "Config for KNN search.", "properties": {}, "type": "object", "id": "GoogleCloudAiplatformV1RagVectorDbConfigRagManagedDbKNN" }, "GoogleCloudAiplatformV1DirectUploadSource": { "type": "object", "description": "The input content is encapsulated and uploaded in the request.", "properties": {}, "id": "GoogleCloudAiplatformV1DirectUploadSource" }, "GoogleCloudAiplatformV1ModelMonitoringAlertConfig": { "description": "The alert config for model monitoring.", "type": "object", "id": "GoogleCloudAiplatformV1ModelMonitoringAlertConfig", "properties": { "enableLogging": { "type": "boolean", "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." }, "emailAlertConfig": { "description": "Email alert config.", "$ref": "GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfig" }, "notificationChannels": { "items": { "type": "string" }, "description": "Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`", "type": "array" } } }, "GoogleCloudAiplatformV1GroundingMetadata": { "type": "object", "properties": { "groundingSupports": { "items": { "$ref": "GoogleCloudAiplatformV1GroundingSupport" }, "type": "array", "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." }, "searchEntryPoint": { "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.", "$ref": "GoogleCloudAiplatformV1SearchEntryPoint" }, "imageSearchQueries": { "description": "Optional. The image search queries that were used to generate the content. This field is populated only when the grounding source is Google Search with the Image Search search_type enabled.", "type": "array", "items": { "type": "string" } }, "retrievalQueries": { "description": "Optional. The queries that were executed by the retrieval tools. This field is populated only when the grounding source is a retrieval tool, such as Vertex AI Search.", "items": { "type": "string" }, "type": "array" }, "sourceFlaggingUris": { "readOnly": true, "type": "array", "description": "Optional. Output only. A list of URIs that can be used to flag a place or review for inappropriate content. This field is populated only when the grounding source is Google Maps.", "items": { "$ref": "GoogleCloudAiplatformV1GroundingMetadataSourceFlaggingUri" } }, "groundingChunks": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1GroundingChunk" }, "description": "A list of supporting references retrieved from the grounding source. This field is populated when the grounding source is Google Search, Vertex AI Search, or Google Maps." }, "retrievalMetadata": { "$ref": "GoogleCloudAiplatformV1RetrievalMetadata", "description": "Optional. Output only. Metadata related to the retrieval grounding source.", "readOnly": true }, "googleMapsWidgetContextToken": { "readOnly": true, "description": "Optional. Output only. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and will no longer be populated once removed. 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.", "type": "string", "deprecated": true }, "webSearchQueries": { "type": "array", "items": { "type": "string" }, "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." } }, "id": "GoogleCloudAiplatformV1GroundingMetadata", "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." }, "GoogleCloudAiplatformV1DeployIndexResponse": { "description": "Response message for IndexEndpointService.DeployIndex.", "id": "GoogleCloudAiplatformV1DeployIndexResponse", "properties": { "deployedIndex": { "description": "The DeployedIndex that had been deployed in the IndexEndpoint.", "$ref": "GoogleCloudAiplatformV1DeployedIndex" } }, "type": "object" }, "GoogleCloudAiplatformV1FunctionResponsePart": { "id": "GoogleCloudAiplatformV1FunctionResponsePart", "properties": { "inlineData": { "description": "Inline media bytes.", "$ref": "GoogleCloudAiplatformV1FunctionResponseBlob" }, "fileData": { "description": "URI based data.", "$ref": "GoogleCloudAiplatformV1FunctionResponseFileData" } }, "description": "A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.", "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata", "properties": { "successfulStopReason": { "description": "For successful job completions, this is the reason why the job has finished.", "enumDescriptions": [ "Should not be set.", "The inputs.budgetMilliNodeHours had been reached.", "Further training of the Model ceased to increase its quality, since it already has converged." ], "enum": [ "SUCCESSFUL_STOP_REASON_UNSPECIFIED", "BUDGET_REACHED", "MODEL_CONVERGED" ], "type": "string" }, "costMilliNodeHours": { "description": "The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours.", "type": "string", "format": "int64" } }, "type": "object" }, "GoogleCloudAiplatformV1ReadFeatureValuesResponse": { "id": "GoogleCloudAiplatformV1ReadFeatureValuesResponse", "properties": { "header": { "description": "Response header.", "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponseHeader" }, "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.", "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityView" } }, "description": "Response message for FeaturestoreOnlineServingService.ReadFeatureValues.", "type": "object" }, "GoogleCloudAiplatformV1SchemaPromptSpecTranslationPrompt": { "id": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationPrompt", "properties": { "example": { "description": "The translation example.", "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationExample" }, "promptMessage": { "description": "The prompt message.", "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecPromptMessage" }, "option": { "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationOption", "description": "The translation option." }, "sourceLanguageCode": { "type": "string", "description": "The source language code." }, "targetLanguageCode": { "description": "The target language code.", "type": "string" } }, "type": "object", "description": "Prompt variation for Translation use case." }, "GoogleCloudAiplatformV1CreateOnlineEvaluatorOperationMetadata": { "id": "GoogleCloudAiplatformV1CreateOnlineEvaluatorOperationMetadata", "properties": { "genericMetadata": { "description": "Common part of operation metadata.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "description": "Metadata for the CreateOnlineEvaluator operation.", "type": "object" }, "GenaiVertexV1Value": { "description": "`Value` represents a dynamically typed value which can be either null, a number, a string, a boolean, a recursive struct value, or a list of values. A producer of value is expected to set one of these variants. Absence of any variant indicates an error.", "type": "object", "properties": { "structValue": { "description": "Represents a structured value.", "$ref": "GenaiVertexV1Struct" }, "listValue": { "description": "Represents a repeated `Value`.", "$ref": "GenaiVertexV1ListValue" }, "contentValue": { "$ref": "GenaiVertexV1Content", "description": "Represents rich content (text, image, etc.)." }, "boolValue": { "description": "Represents a boolean value.", "type": "boolean" }, "nullValue": { "enumDescriptions": [ "Null value." ], "description": "Represents a null value.", "enum": [ "NULL_VALUE" ], "type": "string" }, "numberValue": { "description": "Represents a double value.", "format": "double", "type": "number" }, "stringValue": { "type": "string", "description": "Represents a string value." } }, "id": "GenaiVertexV1Value" }, "GenaiVertexV1Error": { "type": "object", "properties": { "code": { "description": "A URI that identifies the error type.", "type": "string" }, "message": { "type": "string", "description": "A human-readable error message." } }, "id": "GenaiVertexV1Error", "description": "Error message from an interaction." }, "GoogleCloudAiplatformV1ReasoningEngineSpec": { "properties": { "packageSpec": { "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecPackageSpec", "description": "Optional. User provided package spec of the ReasoningEngine. Ignored when users directly specify a deployment image through `deployment_spec.first_party_image_override`, but keeping the field_behavior to avoid introducing breaking changes. The `deployment_source` field should not be set if `package_spec` is specified." }, "containerSpec": { "description": "Deploy from a container image with a defined entrypoint and commands.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecContainerSpec" }, "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.", "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." ], "type": "string", "enum": [ "IDENTITY_TYPE_UNSPECIFIED", "SERVICE_ACCOUNT", "AGENT_IDENTITY" ] }, "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": { "type": "string", "readOnly": true, "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" }, "sourceCodeSpec": { "description": "Deploy from source code files with a defined entrypoint.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpec" }, "deploymentSpec": { "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpec", "description": "Optional. The specification of a Reasoning Engine deployment." }, "buildSpec": { "description": "Optional. Configuration for building container image.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecBuildSpec" }, "classMethods": { "type": "array", "items": { "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "type": "object" }, "description": "Optional. Declarations for object class methods in OpenAPI specification format." } }, "id": "GoogleCloudAiplatformV1ReasoningEngineSpec", "description": "ReasoningEngine configurations", "type": "object" }, "GoogleCloudAiplatformV1ExportModelOperationMetadata": { "description": "Details of ModelService.ExportModel operation.", "type": "object", "properties": { "outputInfo": { "$ref": "GoogleCloudAiplatformV1ExportModelOperationMetadataOutputInfo", "description": "Output only. Information further describing the output of this Model export.", "readOnly": true }, "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The common part of the operation metadata." } }, "id": "GoogleCloudAiplatformV1ExportModelOperationMetadata" }, "GenaiVertexV1UrlContextCallDelta": { "id": "GenaiVertexV1UrlContextCallDelta", "properties": { "arguments": { "$ref": "GenaiVertexV1UrlContextCallContentUrlContextCallArguments" } }, "type": "object" }, "GoogleCloudAiplatformV1PurgeExecutionsRequest": { "description": "Request message for MetadataService.PurgeExecutions.", "type": "object", "id": "GoogleCloudAiplatformV1PurgeExecutionsRequest", "properties": { "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" }, "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" } } }, "GoogleCloudAiplatformV1Rubric": { "id": "GoogleCloudAiplatformV1Rubric", "type": "object", "properties": { "rubricId": { "description": "Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.", "type": "string" }, "type": { "type": "string", "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\"." }, "content": { "description": "Required. The actual testable criteria for the rubric.", "$ref": "GoogleCloudAiplatformV1RubricContent" }, "importance": { "enumDescriptions": [ "Importance is not specified.", "High importance.", "Medium importance.", "Low importance." ], "type": "string", "description": "Optional. The relative importance of this rubric.", "enum": [ "IMPORTANCE_UNSPECIFIED", "HIGH", "MEDIUM", "LOW" ] } }, "description": "Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics." }, "GenaiVertexV1StepDeltaData": { "id": "GenaiVertexV1StepDeltaData", "type": "object", "properties": { "audio": { "$ref": "GenaiVertexV1AudioDelta" }, "textAnnotationDelta": { "$ref": "GenaiVertexV1TextAnnotationDelta" }, "document": { "$ref": "GenaiVertexV1DocumentDelta" }, "serverToolCall": { "$ref": "GenaiVertexV1ServerToolCallDelta" }, "thoughtSignature": { "$ref": "GenaiVertexV1ThoughtSignatureDelta" }, "image": { "$ref": "GenaiVertexV1ImageDelta" }, "argumentsDelta": { "$ref": "GenaiVertexV1ArgumentsDelta" }, "functionResult": { "$ref": "GenaiVertexV1FunctionResultDelta" }, "text": { "$ref": "GenaiVertexV1TextDelta" }, "video": { "$ref": "GenaiVertexV1VideoDelta" }, "thoughtSummary": { "$ref": "GenaiVertexV1ThoughtSummaryDelta" }, "serverToolResult": { "$ref": "GenaiVertexV1ServerToolResultDelta" } } }, "GoogleCloudAiplatformV1SafetySetting": { "type": "object", "properties": { "method": { "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.", "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." ], "type": "string" }, "threshold": { "description": "Required. The threshold for blocking content. If the harm probability exceeds this threshold, the content will be blocked.", "enum": [ "HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF" ], "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." ] }, "category": { "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." ], "description": "Required. The harm category to be blocked.", "type": "string", "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" ], "enumDeprecated": [ false, false, false, false, false, true, false, false, false, false, false ] } }, "id": "GoogleCloudAiplatformV1SafetySetting", "description": "A safety setting that affects the safety-blocking behavior. A SafetySetting consists of a harm category and a threshold for that category." }, "GoogleCloudAiplatformV1StreamingReadFeatureValuesRequest": { "type": "object", "properties": { "featureSelector": { "$ref": "GoogleCloudAiplatformV1FeatureSelector", "description": "Required. Selector choosing Features of the target EntityType. Feature IDs will be deduplicated." }, "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" } } }, "description": "Request message for FeaturestoreOnlineServingService.StreamingReadFeatureValues.", "id": "GoogleCloudAiplatformV1StreamingReadFeatureValuesRequest" }, "GoogleCloudAiplatformV1HyperparameterTuningJob": { "type": "object", "id": "GoogleCloudAiplatformV1HyperparameterTuningJob", "properties": { "state": { "description": "Output only. The detailed state of the job.", "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." ], "type": "string", "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" ], "readOnly": true }, "trials": { "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1Trial" }, "type": "array", "description": "Output only. Trials of the HyperparameterTuningJob." }, "satisfiesPzi": { "readOnly": true, "description": "Output only. Reserved for future use.", "type": "boolean" }, "displayName": { "description": "Required. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "satisfiesPzs": { "readOnly": true, "description": "Output only. Reserved for future use.", "type": "boolean" }, "startTime": { "readOnly": true, "format": "google-datetime", "description": "Output only. Time when the HyperparameterTuningJob for the first time entered the `JOB_STATE_RUNNING` state.", "type": "string" }, "maxTrialCount": { "type": "integer", "description": "Required. The desired total number of Trials.", "format": "int32" }, "parallelTrialCount": { "type": "integer", "description": "Required. The desired number of Trials to run in parallel.", "format": "int32" }, "updateTime": { "description": "Output only. Time when the HyperparameterTuningJob was most recently updated.", "type": "string", "readOnly": true, "format": "google-datetime" }, "name": { "description": "Output only. Resource name of the HyperparameterTuningJob.", "readOnly": true, "type": "string" }, "studySpec": { "$ref": "GoogleCloudAiplatformV1StudySpec", "description": "Required. Study configuration of the HyperparameterTuningJob." }, "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" }, "error": { "$ref": "GoogleRpcStatus", "description": "Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.", "readOnly": true }, "createTime": { "type": "string", "format": "google-datetime", "description": "Output only. Time when the HyperparameterTuningJob was created.", "readOnly": true }, "trialJobSpec": { "description": "Required. The spec of a trial job. The same spec applies to the CustomJobs created in all the trials.", "$ref": "GoogleCloudAiplatformV1CustomJobSpec" }, "labels": { "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.", "additionalProperties": { "type": "string" }, "type": "object" }, "endTime": { "description": "Output only. Time when the HyperparameterTuningJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", "readOnly": true, "type": "string", "format": "google-datetime" }, "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": "GoogleCloudAiplatformV1EncryptionSpec" } }, "description": "Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification." }, "GoogleCloudAiplatformV1ModalityTokenCount": { "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": "GoogleCloudAiplatformV1ModalityTokenCount", "type": "object", "properties": { "tokenCount": { "format": "int32", "type": "integer", "description": "The number of tokens counted for this modality." }, "modality": { "description": "The modality that this token count applies to.", "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." ], "type": "string", "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "VIDEO", "AUDIO", "DOCUMENT" ] } } }, "GenaiVertexV1ImageResponseFormat": { "description": "Configuration for image output format.", "id": "GenaiVertexV1ImageResponseFormat", "type": "object", "properties": { "delivery": { "enumDescriptions": [ "Default value. This value is unused.", "Image data is returned inline in the response.", "Image data is returned as a URI." ], "type": "string", "description": "The delivery mode for the image output.", "enum": [ "DELIVERY_UNSPECIFIED", "INLINE", "URI" ] }, "aspectRatio": { "enumDescriptions": [ "Default value. This value is unused.", "1:1 aspect ratio.", "2:3 aspect ratio.", "3:2 aspect ratio.", "3:4 aspect ratio.", "4:3 aspect ratio.", "4:5 aspect ratio.", "5:4 aspect ratio.", "9:16 aspect ratio.", "16:9 aspect ratio.", "21:9 aspect ratio.", "1:8 aspect ratio.", "8:1 aspect ratio.", "1:4 aspect ratio.", "4:1 aspect ratio." ], "type": "string", "enum": [ "ASPECT_RATIO_UNSPECIFIED", "ASPECT_RATIO_ONE_BY_ONE", "ASPECT_RATIO_TWO_BY_THREE", "ASPECT_RATIO_THREE_BY_TWO", "ASPECT_RATIO_THREE_BY_FOUR", "ASPECT_RATIO_FOUR_BY_THREE", "ASPECT_RATIO_FOUR_BY_FIVE", "ASPECT_RATIO_FIVE_BY_FOUR", "ASPECT_RATIO_NINE_BY_SIXTEEN", "ASPECT_RATIO_SIXTEEN_BY_NINE", "ASPECT_RATIO_TWENTY_ONE_BY_NINE", "ASPECT_RATIO_ONE_BY_EIGHT", "ASPECT_RATIO_EIGHT_BY_ONE", "ASPECT_RATIO_ONE_BY_FOUR", "ASPECT_RATIO_FOUR_BY_ONE" ], "description": "The aspect ratio for the image output." }, "mimeType": { "enum": [ "TYPE_UNSPECIFIED", "TYPE_JPEG" ], "enumDescriptions": [ "Default value. This value is unused.", "JPEG image format." ], "type": "string", "description": "The MIME type of the image output." }, "imageSize": { "enum": [ "IMAGE_SIZE_UNSPECIFIED", "IMAGE_SIZE_FIVE_TWELVE", "IMAGE_SIZE_ONE_K", "IMAGE_SIZE_TWO_K", "IMAGE_SIZE_FOUR_K" ], "type": "string", "description": "The size of the image output.", "enumDescriptions": [ "Default value. This value is unused.", "512px image size.", "1K image size.", "2K image size.", "4K image size." ] } } }, "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig": { "description": "The config for Prediction data drift detection.", "properties": { "attributionScoreDriftThresholds": { "description": "Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1ThresholdConfig" } }, "driftThresholds": { "type": "object", "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.", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1ThresholdConfig" } }, "defaultDriftThreshold": { "$ref": "GoogleCloudAiplatformV1ThresholdConfig", "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." } }, "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig", "type": "object" }, "GenaiVertexV1ProcessingCallStep": { "description": "A server-initiated processing step for media analysis (e.g. video understanding).", "type": "object", "properties": {}, "id": "GenaiVertexV1ProcessingCallStep" }, "GoogleCloudAiplatformV1GenerateFetchAccessTokenResponse": { "id": "GoogleCloudAiplatformV1GenerateFetchAccessTokenResponse", "description": "Response message for FeatureOnlineStoreService.GenerateFetchAccessToken.", "type": "object", "properties": { "expireTime": { "type": "string", "description": "Token expiration time. This is always set", "format": "google-datetime" }, "accessToken": { "type": "string", "description": "The OAuth 2.0 access token." } } }, "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecInlineSource": { "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": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecInlineSource", "type": "object", "description": "Specifies source code provided as a byte stream." }, "GoogleCloudAiplatformV1UpdateFeatureViewOperationMetadata": { "type": "object", "properties": { "genericMetadata": { "description": "Operation metadata for FeatureView Update.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1UpdateFeatureViewOperationMetadata", "description": "Details of operations that perform update FeatureView." }, "GoogleCloudAiplatformV1NearestNeighbors": { "type": "object", "properties": { "neighbors": { "description": "All its neighbors.", "items": { "$ref": "GoogleCloudAiplatformV1NearestNeighborsNeighbor" }, "type": "array" } }, "description": "Nearest neighbors for one query.", "id": "GoogleCloudAiplatformV1NearestNeighbors" }, "GoogleCloudAiplatformV1EnterpriseWebSearch": { "properties": { "excludeDomains": { "description": "Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.", "items": { "type": "string" }, "type": "array" }, "blockingConfidence": { "type": "string", "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.", "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." ] } }, "type": "object", "description": "Tool to search public web data, powered by Vertex AI Search and Sec4 compliance.", "id": "GoogleCloudAiplatformV1EnterpriseWebSearch" }, "GoogleCloudAiplatformV1IntegratedGradientsAttribution": { "properties": { "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", "$ref": "GoogleCloudAiplatformV1BlurBaselineConfig" }, "stepCount": { "format": "int32", "type": "integer", "description": "Required. The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is within the desired error range. Valid range of its value is [1, 100], inclusively." }, "smoothGradConfig": { "description": "Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf", "$ref": "GoogleCloudAiplatformV1SmoothGradConfig" } }, "id": "GoogleCloudAiplatformV1IntegratedGradientsAttribution", "type": "object", "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" }, "GoogleCloudAiplatformV1DataLabelingJob": { "type": "object", "id": "GoogleCloudAiplatformV1DataLabelingJob", "description": "DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:", "properties": { "error": { "description": "Output only. DataLabelingJob errors. It is only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "$ref": "GoogleRpcStatus", "readOnly": true }, "labelerCount": { "type": "integer", "format": "int32", "description": "Required. Number of labelers to work on each DataItem." }, "labelingProgress": { "description": "Output only. Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.", "format": "int32", "type": "integer", "readOnly": true }, "createTime": { "description": "Output only. Timestamp when this DataLabelingJob was created.", "type": "string", "format": "google-datetime", "readOnly": true }, "inputs": { "description": "Required. Input config parameters for the DataLabelingJob.", "type": "any" }, "name": { "type": "string", "readOnly": true, "description": "Output only. Resource name of the DataLabelingJob." }, "datasets": { "items": { "type": "string" }, "description": "Required. Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "type": "array" }, "encryptionSpec": { "description": "Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "specialistPools": { "type": "array", "description": "The SpecialistPools' resource names associated with this job.", "items": { "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" ], "type": "string", "description": "Output only. The detailed state of the job.", "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 }, "currentSpend": { "description": "Output only. Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.", "$ref": "GoogleTypeMoney", "readOnly": true }, "instructionUri": { "description": "Required. The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.", "type": "string" }, "updateTime": { "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when this DataLabelingJob was updated most recently.", "readOnly": true }, "displayName": { "description": "Required. The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.", "type": "string" }, "activeLearningConfig": { "$ref": "GoogleCloudAiplatformV1ActiveLearningConfig", "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." }, "annotationLabels": { "additionalProperties": { "type": "string" }, "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" }, "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" }, "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." } } }, "GoogleCloudAiplatformV1ProbeTcpSocketAction": { "id": "GoogleCloudAiplatformV1ProbeTcpSocketAction", "type": "object", "description": "TcpSocketAction probes the health of a container by opening a TCP socket connection.", "properties": { "port": { "type": "integer", "format": "int32", "description": "Number of the port to access on the container. Number must be in the range 1 to 65535." }, "host": { "type": "string", "description": "Optional: Host name to connect to, defaults to the model serving container's IP." } } }, "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityTraceScope": { "type": "object", "description": "If chosen, the online evaluator will evaluate single traces matching specified `filter`.", "properties": { "filter": { "items": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityTraceScopePredicate" }, "description": "Optional. A list of predicates to filter traces. Multiple predicates are combined using AND. The maximum number of predicates is 10.", "type": "array" } }, "id": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityTraceScope" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs", "properties": { "modelType": { "type": "string", "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" ], "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." ] } }, "type": "object" }, "GoogleCloudAiplatformV1ListMemoryRevisionsResponse": { "description": "Response message for MemoryBankService.ListMemoryRevisions.", "id": "GoogleCloudAiplatformV1ListMemoryRevisionsResponse", "type": "object", "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" }, "memoryRevisions": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1MemoryRevision" }, "description": "The list of Memory Revisions in the request page." } } }, "GoogleCloudAiplatformV1FeatureNoiseSigma": { "properties": { "noiseSigma": { "description": "Noise sigma per feature. No noise is added to features that are not set.", "items": { "$ref": "GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature" }, "type": "array" } }, "id": "GoogleCloudAiplatformV1FeatureNoiseSigma", "description": "Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.", "type": "object" }, "GoogleCloudAiplatformV1DeployIndexOperationMetadata": { "description": "Runtime operation information for IndexEndpointService.DeployIndex.", "id": "GoogleCloudAiplatformV1DeployIndexOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" }, "deployedIndexId": { "description": "The unique index id specified by user", "type": "string" } } }, "GoogleCloudAiplatformV1PredictLongRunningRequest": { "id": "GoogleCloudAiplatformV1PredictLongRunningRequest", "type": "object", "properties": { "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" }, "instances": { "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.", "type": "array" }, "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." }, "GoogleCloudAiplatformV1ApiAuth": { "description": "The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead.", "type": "object", "properties": { "apiKeyConfig": { "description": "The API secret.", "$ref": "GoogleCloudAiplatformV1ApiAuthApiKeyConfig" } }, "id": "GoogleCloudAiplatformV1ApiAuth" }, "GoogleCloudAiplatformV1DeleteFeatureValuesOperationMetadata": { "type": "object", "id": "GoogleCloudAiplatformV1DeleteFeatureValuesOperationMetadata", "description": "Details of operations that delete Feature values.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Operation metadata for Featurestore delete Features values." } } }, "GoogleCloudAiplatformV1RetrievalMetadata": { "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" } }, "description": "Metadata related to the retrieval grounding source. This is part of the `GroundingMetadata` returned when grounding is enabled.", "type": "object", "id": "GoogleCloudAiplatformV1RetrievalMetadata" }, "GoogleCloudAiplatformV1OutputConfig": { "description": "Config for evaluation output.", "id": "GoogleCloudAiplatformV1OutputConfig", "type": "object", "properties": { "gcsDestination": { "description": "Cloud storage destination for evaluation output.", "$ref": "GoogleCloudAiplatformV1GcsDestination" } } }, "GoogleCloudAiplatformV1TrajectorySingleToolUseResults": { "type": "object", "id": "GoogleCloudAiplatformV1TrajectorySingleToolUseResults", "description": "Results for TrajectorySingleToolUse metric.", "properties": { "trajectorySingleToolUseMetricValues": { "items": { "$ref": "GoogleCloudAiplatformV1TrajectorySingleToolUseMetricValue" }, "readOnly": true, "description": "Output only. TrajectorySingleToolUse metric values.", "type": "array" } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation": { "properties": { "columnName": { "type": "string" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation", "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.", "type": "object" }, "GoogleCloudAiplatformV1ListEvaluationItemsResponse": { "id": "GoogleCloudAiplatformV1ListEvaluationItemsResponse", "properties": { "evaluationItems": { "items": { "$ref": "GoogleCloudAiplatformV1EvaluationItem" }, "type": "array", "description": "List of EvaluationItems in the requested page." }, "nextPageToken": { "type": "string", "description": "A token to retrieve the next page of results." } }, "description": "Response message for EvaluationManagementService.ListEvaluationItems.", "type": "object" }, "GenaiVertexV1CodeExecutionResultDelta": { "type": "object", "properties": { "result": { "type": "string" }, "isError": { "type": "boolean" } }, "id": "GenaiVertexV1CodeExecutionResultDelta" }, "GoogleCloudAiplatformV1CustomJobSpec": { "id": "GoogleCloudAiplatformV1CustomJobSpec", "type": "object", "properties": { "experiment": { "description": "Optional. The Experiment associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}`", "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" }, "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" }, "network": { "type": "string", "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." }, "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": "GoogleCloudAiplatformV1GcsDestination" }, "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" }, "protectedArtifactLocationId": { "type": "string", "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" }, "tensorboard": { "type": "string", "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}`" }, "workerPoolSpecs": { "items": { "$ref": "GoogleCloudAiplatformV1WorkerPoolSpec" }, "description": "Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.", "type": "array" }, "pscInterfaceConfig": { "$ref": "GoogleCloudAiplatformV1PscInterfaceConfig", "description": "Optional. Configuration for PSC-I for CustomJob." }, "models": { "type": "array", "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.", "items": { "type": "string" } }, "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" }, "scheduling": { "$ref": "GoogleCloudAiplatformV1Scheduling", "description": "Scheduling options for a CustomJob." }, "experimentRun": { "type": "string", "description": "Optional. The Experiment Run associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}`" }, "reservedIpRanges": { "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'].", "type": "array", "items": { "type": "string" } } }, "description": "Represents the spec of a CustomJob." }, "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective": { "id": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective", "type": "object", "description": "Stats requested for specific objective.", "properties": { "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" }, "type": { "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" ], "type": "string" } } }, "GoogleCloudAiplatformV1TrajectoryRecallResults": { "properties": { "trajectoryRecallMetricValues": { "items": { "$ref": "GoogleCloudAiplatformV1TrajectoryRecallMetricValue" }, "description": "Output only. TrajectoryRecall metric values.", "type": "array", "readOnly": true } }, "type": "object", "description": "Results for TrajectoryRecall metric.", "id": "GoogleCloudAiplatformV1TrajectoryRecallResults" }, "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateMetatdata": { "description": "This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.", "type": "object", "id": "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateMetatdata", "properties": { "genericMetadata": { "description": "Operation metadata for suggesting Trials.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" }, "trial": { "description": "The Trial name.", "type": "string" }, "study": { "description": "The name of the Study that the Trial belongs to.", "type": "string" } } }, "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDataset": { "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDataset", "properties": { "gcsSource": { "$ref": "GoogleCloudAiplatformV1GcsSource", "description": "The Google Cloud Storage uri of the unmanaged Dataset used to train this Model." }, "dataset": { "description": "The resource name of the Dataset used to train this Model.", "type": "string" }, "bigquerySource": { "description": "The BigQuery table of the unmanaged Dataset used to train this Model.", "$ref": "GoogleCloudAiplatformV1BigQuerySource" }, "dataFormat": { "type": "string", "description": "Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: \"tf-record\" The source file is a TFRecord file. \"csv\" The source file is a CSV file. \"jsonl\" The source file is a JSONL file." }, "targetField": { "description": "The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.", "type": "string" }, "loggingSamplingStrategy": { "$ref": "GoogleCloudAiplatformV1SamplingStrategy", "description": "Strategy to sample data from Training Dataset. If not set, we process the whole dataset." } }, "type": "object", "description": "Training Dataset information." }, "GoogleCloudAiplatformV1ExplanationMetadataOverride": { "id": "GoogleCloudAiplatformV1ExplanationMetadataOverride", "type": "object", "properties": { "inputs": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1ExplanationMetadataOverrideInputMetadataOverride" }, "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." } }, "description": "The ExplanationMetadata entries that can be overridden at online explanation time." }, "GoogleCloudAiplatformV1PreferenceOptimizationHyperParameters": { "properties": { "adapterSize": { "type": "string", "description": "Optional. Adapter size for preference optimization.", "enum": [ "ADAPTER_SIZE_UNSPECIFIED", "ADAPTER_SIZE_ONE", "ADAPTER_SIZE_TWO", "ADAPTER_SIZE_FOUR", "ADAPTER_SIZE_EIGHT", "ADAPTER_SIZE_SIXTEEN", "ADAPTER_SIZE_THIRTY_TWO" ], "enumDescriptions": [ "Adapter size is unspecified.", "Adapter size 1.", "Adapter size 2.", "Adapter size 4.", "Adapter size 8.", "Adapter size 16.", "Adapter size 32." ] }, "epochCount": { "type": "string", "description": "Optional. Number of complete passes the model makes over the entire training dataset during training.", "format": "int64" }, "beta": { "format": "double", "description": "Optional. Weight for KL Divergence regularization.", "type": "number" }, "learningRateMultiplier": { "type": "number", "format": "double", "description": "Optional. Multiplier for adjusting the default learning rate." } }, "id": "GoogleCloudAiplatformV1PreferenceOptimizationHyperParameters", "type": "object", "description": "Hyperparameters for Preference Optimization." }, "GoogleCloudAiplatformV1GroundingChunkWeb": { "id": "GoogleCloudAiplatformV1GroundingChunkWeb", "properties": { "domain": { "description": "The domain of the web page that contains the evidence. This can be used to filter out low-quality sources.", "type": "string" }, "title": { "description": "The title of the web page that contains the evidence.", "type": "string" }, "uri": { "type": "string", "description": "The URI of the web page that contains the evidence." } }, "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.", "type": "object" }, "GoogleCloudAiplatformV1BleuInput": { "id": "GoogleCloudAiplatformV1BleuInput", "description": "Input for bleu metric.", "properties": { "instances": { "items": { "$ref": "GoogleCloudAiplatformV1BleuInstance" }, "description": "Required. Repeated bleu instances.", "type": "array" }, "metricSpec": { "description": "Required. Spec for bleu score metric.", "$ref": "GoogleCloudAiplatformV1BleuSpec" } }, "type": "object" }, "GoogleCloudAiplatformV1CreateSpecialistPoolOperationMetadata": { "id": "GoogleCloudAiplatformV1CreateSpecialistPoolOperationMetadata", "type": "object", "description": "Runtime operation information for SpecialistPoolService.CreateSpecialistPool.", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageSegmentationEvaluationMetrics": { "description": "Metrics for image segmentation evaluation results.", "properties": { "confidenceMetricsEntries": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry" }, "description": "Metrics for each confidenceThreshold in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 Precision-recall curve can be derived from it." } }, "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageSegmentationEvaluationMetrics", "type": "object" }, "GoogleCloudAiplatformV1RagEmbeddingModelConfigVertexPredictionEndpoint": { "id": "GoogleCloudAiplatformV1RagEmbeddingModelConfigVertexPredictionEndpoint", "description": "Config representing a model hosted on Vertex Prediction Endpoint.", "type": "object", "properties": { "modelVersionId": { "readOnly": true, "description": "Output only. Version ID of the model that is deployed on the endpoint. Present only when the endpoint is not a publisher model.", "type": "string" }, "model": { "type": "string", "description": "Output only. The resource name of the model that is deployed on the endpoint. Present only when the endpoint is not a publisher model. Pattern: `projects/{project}/locations/{location}/models/{model}`", "readOnly": true }, "endpoint": { "type": "string", "description": "Required. The endpoint resource name. Format: `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/endpoints/{endpoint}`" } } }, "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataAgentEvent": { "type": "object", "properties": { "content": { "description": "Required. The content of the event (e.g., text response, tool call, tool response).", "$ref": "GoogleCloudAiplatformV1Content" }, "stateDelta": { "type": "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.", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "author": { "description": "Required. The ID of the agent or entity that generated this event.", "type": "string" }, "activeTools": { "items": { "$ref": "GoogleCloudAiplatformV1Tool" }, "description": "Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.", "type": "array" }, "eventTime": { "format": "google-datetime", "description": "Optional. The timestamp when the event occurred.", "type": "string" } }, "id": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataAgentEvent", "description": "A single event in the execution trace." }, "GoogleCloudAiplatformV1DeployedIndex": { "description": "A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes.", "properties": { "dedicatedResources": { "description": "Optional. A description of resources that are dedicated to the DeployedIndex, and that need a higher degree of manual configuration. The field min_replica_count must be set to a value strictly greater than 0, or else validation will fail. We don't provide SLA when min_replica_count=1. If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000. Available machine types for SMALL shard: e2-standard-2 and all machine types available for MEDIUM and LARGE shard. Available machine types for MEDIUM shard: e2-standard-16 and all machine types available for LARGE shard. Available machine types for LARGE shard: e2-highmem-16, n2d-standard-32. n1-standard-16 and n1-standard-32 are still available, but we recommend e2-standard-16 and e2-highmem-16 for cost efficiency.", "$ref": "GoogleCloudAiplatformV1DedicatedResources" }, "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" }, "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": "GoogleCloudAiplatformV1IndexPrivateEndpoints" }, "reservedIpRanges": { "type": "array", "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.", "items": { "type": "string" } }, "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" }, "displayName": { "type": "string", "description": "The display name of the DeployedIndex. If not provided upon creation, the Index's display_name is used." }, "indexSyncTime": { "format": "google-datetime", "readOnly": true, "type": "string", "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." }, "deployedIndexAuthConfig": { "description": "Optional. If set, the authentication is enabled for the private endpoint.", "$ref": "GoogleCloudAiplatformV1DeployedIndexAuthConfig" }, "deploymentTier": { "enumDescriptions": [ "Default deployment tier.", "Optimized for costs." ], "enum": [ "DEPLOYMENT_TIER_UNSPECIFIED", "STORAGE" ], "type": "string", "description": "Optional. The deployment tier that the index is deployed to. DEPLOYMENT_TIER_UNSPECIFIED will use a system-chosen default tier." }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when the DeployedIndex was created.", "readOnly": true, "type": "string" }, "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" }, "automaticResources": { "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.", "$ref": "GoogleCloudAiplatformV1AutomaticResources" }, "pscAutomationConfigs": { "description": "Optional. If set for PSC deployed index, PSC connection will be automatically created after deployment is done and the endpoint information is populated in private_endpoints.psc_automated_endpoints.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1PSCAutomationConfig" } }, "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" }, "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" } }, "type": "object", "id": "GoogleCloudAiplatformV1DeployedIndex" }, "GoogleCloudAiplatformV1ListTensorboardTimeSeriesResponse": { "description": "Response message for TensorboardService.ListTensorboardTimeSeries.", "id": "GoogleCloudAiplatformV1ListTensorboardTimeSeriesResponse", "properties": { "tensorboardTimeSeries": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" }, "description": "The TensorboardTimeSeries mathching the request." }, "nextPageToken": { "description": "A token, which can be sent as ListTensorboardTimeSeriesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1CacheConfig": { "description": "Config of GenAI caching features. This is a singleton resource.", "properties": { "disableCache": { "type": "boolean", "description": "If set to true, disables GenAI caching. Otherwise caching is enabled." }, "retentionConfig": { "$ref": "GoogleCloudAiplatformV1CacheConfigRetentionConfig", "description": "Optional. Project-level retention type for implicit caching. On `GetCacheConfig` this is populated with the retention the project gets: a project that has stated no preference reports `DURABLE`. On `UpdateCacheConfig`, leaving it unset means the project states no preference. Whether that clears an existing preference depends on `update_mask`; see that field." }, "name": { "type": "string", "description": "Identifier. Name of the cache config. Format: - `projects/{project}/cacheConfig`." } }, "type": "object", "id": "GoogleCloudAiplatformV1CacheConfig" }, "GoogleCloudAiplatformV1RougeResults": { "properties": { "rougeMetricValues": { "type": "array", "description": "Output only. Rouge metric values.", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1RougeMetricValue" } } }, "id": "GoogleCloudAiplatformV1RougeResults", "description": "Results for rouge metric.", "type": "object" }, "GoogleCloudAiplatformV1BoolArray": { "properties": { "values": { "type": "array", "items": { "type": "boolean" }, "description": "A list of bool values." } }, "description": "A list of boolean values.", "id": "GoogleCloudAiplatformV1BoolArray", "type": "object" }, "GoogleCloudAiplatformV1AuthorizeSandboxEnvironmentAccessResponse": { "description": "Response message for SandboxEnvironmentExecutionService.AuthorizeSandboxEnvironmentAccess. Intentionally empty: a successful response is the authorization result.", "id": "GoogleCloudAiplatformV1AuthorizeSandboxEnvironmentAccessResponse", "properties": {}, "type": "object" }, "GoogleCloudAiplatformV1SandboxEnvironmentTemplateEgressControlConfigDnsPeeringConfig": { "type": "object", "description": "Configuration for peering a customer's private DNS zone so that sandbox egress can resolve customer-internal domains via the customer VPC.", "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" }, "targetNetwork": { "type": "string", "description": "Required. The VPC network name in the target_project where the DNS zone specified by `domain` is visible." }, "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" } }, "id": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateEgressControlConfigDnsPeeringConfig" }, "GoogleCloudAiplatformV1SchemaVideoDatasetMetadata": { "description": "The metadata of Datasets that contain Video DataItems.", "id": "GoogleCloudAiplatformV1SchemaVideoDatasetMetadata", "properties": { "gcsBucket": { "type": "string", "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset." }, "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" } }, "type": "object" }, "GoogleCloudAiplatformV1ReadTensorboardSizeResponse": { "description": "Response message for TensorboardService.ReadTensorboardSize.", "type": "object", "properties": { "storageSizeByte": { "type": "string", "format": "int64", "description": "Payload storage size for the TensorBoard" } }, "id": "GoogleCloudAiplatformV1ReadTensorboardSizeResponse" }, "GoogleCloudAiplatformV1ImportEvaluationSetRequestInteractionsSource": { "properties": { "geminiAgentConfig": { "description": "Optional. Gemini Agent (Vertex AI Agent resource).", "$ref": "GoogleCloudAiplatformV1GeminiAgentConfig" }, "interactions": { "items": { "type": "string" }, "type": "array", "description": "Required. The interactions to import. Format: `projects/{project}/locations/{location}/interactions/{interaction}`." } }, "type": "object", "id": "GoogleCloudAiplatformV1ImportEvaluationSetRequestInteractionsSource", "description": "Source for importing interactions from the Interactions API into an EvaluationSet. The agent identity is specified once, with a list of interaction IDs to import." }, "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectContentsSourceEvent": { "properties": { "content": { "$ref": "GoogleCloudAiplatformV1Content", "description": "Required. A single piece of content from which to generate memories." } }, "description": "A single piece of conversation from which to generate memories.", "type": "object", "id": "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectContentsSourceEvent" }, "GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpec": { "type": "object", "description": "Value specification for a parameter in `CATEGORICAL` type.", "properties": { "defaultValue": { "type": "string", "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." }, "values": { "items": { "type": "string" }, "description": "Required. The list of possible categories.", "type": "array" } }, "id": "GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpec" }, "GoogleCloudAiplatformV1FeatureViewVertexRagSource": { "type": "object", "properties": { "ragCorpusId": { "type": "string", "description": "Optional. The RAG corpus id corresponding to this FeatureView.", "format": "int64" }, "uri": { "type": "string", "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)" } }, "description": "A Vertex Rag source for features that need to be synced to Online Store.", "id": "GoogleCloudAiplatformV1FeatureViewVertexRagSource" }, "CloudAiLargeModelsVisionGenerateVideoExperimentsProEditConfig": { "type": "object", "description": "Configuration for Pro Edit.", "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsProEditConfig", "properties": { "editInstructionPrompt": { "description": "A text string containing the user's edit instruction. Will be applied to the original URF.", "type": "string" }, "fromOperationId": { "description": "Required. The operation_id from a previous omni-cine generation whose OF and URF should be retrieved for editing.", "type": "string" }, "structuredPrompt": { "type": "string", "description": "A JSON string containing the user's modified URF. The URF Editing Preamble will diff this against the original URF to determine what changed." } } }, "GoogleCloudAiplatformV1FindNeighborsResponseNearestNeighbors": { "description": "Nearest neighbors for one query.", "type": "object", "properties": { "id": { "description": "The ID of the query datapoint.", "type": "string" }, "neighbors": { "items": { "$ref": "GoogleCloudAiplatformV1FindNeighborsResponseNeighbor" }, "description": "All its neighbors.", "type": "array" } }, "id": "GoogleCloudAiplatformV1FindNeighborsResponseNearestNeighbors" }, "GoogleCloudAiplatformV1BigQueryDestination": { "type": "object", "properties": { "outputUri": { "type": "string", "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`." } }, "id": "GoogleCloudAiplatformV1BigQueryDestination", "description": "The BigQuery location for the output content." }, "GoogleCloudAiplatformV1QuestionAnsweringRelevanceSpec": { "type": "object", "id": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceSpec", "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." }, "GenaiVertexV1ToolCallStep": { "properties": { "retrievalCall": { "$ref": "GenaiVertexV1RetrievalCallStep" }, "urlContextCall": { "$ref": "GenaiVertexV1UrlContextCallStep" }, "signature": { "format": "byte", "type": "string", "description": "A signature hash for backend validation." }, "id": { "description": "Required. A unique ID for this specific tool call.", "type": "string" }, "functionCall": { "$ref": "GenaiVertexV1FunctionCallStep" }, "googleMapsCall": { "$ref": "GenaiVertexV1GoogleMapsCallStep" }, "codeExecutionCall": { "$ref": "GenaiVertexV1CodeExecutionCallStep" }, "fileSearchCall": { "$ref": "GenaiVertexV1FileSearchCallStep" }, "googleSearchCall": { "$ref": "GenaiVertexV1GoogleSearchCallStep" }, "processingCall": { "$ref": "GenaiVertexV1ProcessingCallStep" } }, "id": "GenaiVertexV1ToolCallStep", "type": "object", "description": "Tool call step." }, "GoogleCloudAiplatformV1GroundingMetadataSourceFlaggingUri": { "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": { "flagContentUri": { "description": "The URI that can be used to flag the content.", "type": "string" }, "sourceId": { "type": "string", "description": "The ID of the place or review." } }, "type": "object", "id": "GoogleCloudAiplatformV1GroundingMetadataSourceFlaggingUri" }, "GoogleCloudAiplatformV1ImageConfigImageOutputOptions": { "id": "GoogleCloudAiplatformV1ImageConfigImageOutputOptions", "type": "object", "description": "The image output format for generated images.", "properties": { "mimeType": { "description": "Optional. The image format that the output should be saved as.", "type": "string" }, "compressionQuality": { "type": "integer", "format": "int32", "description": "Optional. The compression quality of the output image." } } }, "GoogleCloudAiplatformV1RetrieveMemoriesRequest": { "description": "Request message for MemoryBankService.RetrieveMemories.", "properties": { "similaritySearchParams": { "$ref": "GoogleCloudAiplatformV1RetrieveMemoriesRequestSimilaritySearchParams", "description": "Parameters for semantic similarity search based retrieval." }, "filterGroups": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1MemoryConjunctionFilter" }, "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\"))`." }, "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" }, "simpleRetrievalParams": { "$ref": "GoogleCloudAiplatformV1RetrieveMemoriesRequestSimpleRetrievalParams", "description": "Parameters for simple (non-similarity search) retrieval." }, "scope": { "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.", "additionalProperties": { "type": "string" }, "type": "object" }, "memoryTypes": { "type": "array", "items": { "type": "string", "enum": [ "MEMORY_TYPE_UNSPECIFIED", "NATURAL_LANGUAGE_COLLECTION", "STRUCTURED_PROFILE" ], "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. 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": "object", "id": "GoogleCloudAiplatformV1RetrieveMemoriesRequest" }, "GoogleCloudAiplatformV1NearestNeighborQueryEmbedding": { "properties": { "value": { "type": "array", "items": { "type": "number", "format": "float" }, "description": "Optional. Individual value in the embedding." } }, "description": "The embedding vector.", "id": "GoogleCloudAiplatformV1NearestNeighborQueryEmbedding", "type": "object" }, "GoogleCloudAiplatformV1AugmentPromptRequestModel": { "id": "GoogleCloudAiplatformV1AugmentPromptRequestModel", "description": "Metadata of the backend deployed model.", "properties": { "model": { "description": "Optional. The model that the user will send the augmented prompt for content generation.", "type": "string" }, "modelVersion": { "type": "string", "description": "Optional. The model version of the backend deployed model." } }, "type": "object" }, "GoogleCloudAiplatformV1ToolConfig": { "type": "object", "description": "Tool config. This config is shared for all tools provided in the request.", "properties": { "functionCallingConfig": { "description": "Optional. Function calling config.", "$ref": "GoogleCloudAiplatformV1FunctionCallingConfig" }, "retrievalConfig": { "description": "Optional. Retrieval config.", "$ref": "GoogleCloudAiplatformV1RetrievalConfig" } }, "id": "GoogleCloudAiplatformV1ToolConfig" }, "GenaiVertexV1TextContent": { "description": "A text content block. ", "properties": { "annotations": { "type": "array", "items": { "$ref": "GenaiVertexV1TextContentAnnotation" }, "description": "Citation information for model-generated content." }, "text": { "type": "string", "description": "Required. The text content." } }, "id": "GenaiVertexV1TextContent", "type": "object" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics": { "properties": { "confidenceThreshold": { "description": "The confidence threshold value used to compute the metrics.", "format": "float", "type": "number" }, "trackingPrecision": { "format": "float", "description": "Tracking precision.", "type": "number" }, "trackingRecall": { "description": "Tracking recall.", "type": "number", "format": "float" }, "boundingBoxIou": { "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).", "format": "float", "type": "number" }, "mismatchRate": { "type": "number", "description": "Mismatch rate, which measures the tracking consistency, i.e. correctness of instance ID continuity.", "format": "float" } }, "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics", "description": "Metrics for a single confidence threshold.", "type": "object" }, "GenaiVertexV1CodeMenderAgentConfigSessionConfig": { "type": "object", "id": "GenaiVertexV1CodeMenderAgentConfigSessionConfig", "description": "The configuration of CodeMender sessions.", "properties": { "maxRounds": { "description": "The maximum number of interaction rounds the agent is allowed to perform before reaching a timeout.", "type": "integer", "format": "int32" } } }, "GoogleCloudAiplatformV1Schema": { "properties": { "minItems": { "type": "string", "format": "int64", "description": "Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array." }, "anyOf": { "type": "array", "description": "Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.", "items": { "$ref": "GoogleCloudAiplatformV1Schema" } }, "properties": { "additionalProperties": { "$ref": "GoogleCloudAiplatformV1Schema" }, "description": "Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.", "type": "object" }, "maxProperties": { "format": "int64", "description": "Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.", "type": "string" }, "required": { "type": "array", "items": { "type": "string" }, "description": "Optional. If type is `OBJECT`, `required` lists the names of properties that must be present." }, "maximum": { "format": "double", "description": "Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.", "type": "number" }, "items": { "description": "Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.", "$ref": "GoogleCloudAiplatformV1Schema" }, "maxLength": { "type": "string", "format": "int64", "description": "Optional. If type is `STRING`, `max_length` specifies the maximum length of the string." }, "example": { "description": "Optional. Example of an instance of this schema.", "type": "any" }, "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\"]}`", "items": { "type": "string" }, "type": "array" }, "pattern": { "type": "string", "description": "Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match." }, "minLength": { "format": "int64", "description": "Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.", "type": "string" }, "type": { "type": "string", "enum": [ "TYPE_UNSPECIFIED", "STRING", "NUMBER", "INTEGER", "BOOLEAN", "ARRAY", "OBJECT", "NULL" ], "description": "Optional. Data type of the schema field.", "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" ] }, "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" }, "maxItems": { "description": "Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.", "type": "string", "format": "int64" }, "propertyOrdering": { "items": { "type": "string" }, "type": "array", "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." }, "defs": { "additionalProperties": { "$ref": "GoogleCloudAiplatformV1Schema" }, "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.", "type": "object" }, "additionalProperties": { "type": "any", "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." }, "format": { "type": "string", "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." }, "nullable": { "type": "boolean", "description": "Optional. Indicates if the value of this field can be null." }, "default": { "description": "Optional. Default value to use if the field is not specified.", "type": "any" }, "minimum": { "type": "number", "description": "Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.", "format": "double" }, "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" }, "title": { "description": "Optional. Title for the schema.", "type": "string" }, "minProperties": { "description": "Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.", "format": "int64", "type": "string" } }, "id": "GoogleCloudAiplatformV1Schema", "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).", "type": "object" }, "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectEntity": { "id": "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectEntity", "properties": { "entityIdSelector": { "description": "Required. Selectors choosing feature values of which entity id to be deleted from the EntityType.", "$ref": "GoogleCloudAiplatformV1EntityIdSelector" } }, "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.", "type": "object" }, "GoogleCloudAiplatformV1ExportFilterSplit": { "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": { "type": "string", "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." }, "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": "GoogleCloudAiplatformV1ExportFilterSplit", "type": "object" }, "GoogleCloudAiplatformV1FeatureViewSyncSyncSummary": { "properties": { "totalSlot": { "description": "Output only. BigQuery slot milliseconds consumed for the sync job.", "readOnly": true, "format": "int64", "type": "string" }, "systemWatermarkTime": { "format": "google-datetime", "type": "string", "description": "Lower bound of the system time watermark for the sync job. This is only set for continuously syncing feature views." }, "rowSynced": { "readOnly": true, "format": "int64", "description": "Output only. Total number of rows synced.", "type": "string" } }, "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.", "type": "object", "id": "GoogleCloudAiplatformV1FeatureViewSyncSyncSummary" }, "GoogleCloudAiplatformV1DeployedModel": { "type": "object", "id": "GoogleCloudAiplatformV1DeployedModel", "properties": { "fasterDeploymentConfig": { "description": "Configuration for faster model deployment.", "$ref": "GoogleCloudAiplatformV1FasterDeploymentConfig" }, "disableExplanations": { "description": "If true, deploy the model without explainable feature, regardless the existence of Model.explanation_spec or explanation_spec.", "type": "boolean" }, "modelVersionId": { "type": "string", "readOnly": true, "description": "Output only. The version ID of the model that is deployed." }, "gdcConnectedModel": { "type": "string", "description": "GDC pretrained / Gemini model name. The model name is a plain model name, e.g. gemini-1.5-flash-002." }, "status": { "$ref": "GoogleCloudAiplatformV1DeployedModelStatus", "readOnly": true, "description": "Output only. Runtime status of the deployed model." }, "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" }, "sharedResources": { "description": "The resource name of the shared DeploymentResourcePool to deploy on. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", "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" }, "systemLabels": { "additionalProperties": { "type": "string" }, "description": "System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only.", "type": "object" }, "displayName": { "description": "The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.", "type": "string" }, "explanationSpec": { "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.", "$ref": "GoogleCloudAiplatformV1ExplanationSpec" }, "automaticResources": { "description": "A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.", "$ref": "GoogleCloudAiplatformV1AutomaticResources" }, "createTime": { "readOnly": true, "format": "google-datetime", "description": "Output only. Timestamp when the DeployedModel was created.", "type": "string" }, "speculativeDecodingSpec": { "description": "Optional. Spec for configuring speculative decoding.", "$ref": "GoogleCloudAiplatformV1SpeculativeDecodingSpec" }, "dedicatedResources": { "$ref": "GoogleCloudAiplatformV1DedicatedResources", "description": "A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration." }, "enableAccessLogging": { "description": "If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each prediction request. Note that logs may incur a cost, especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option.", "type": "boolean" }, "checkpointId": { "type": "string", "description": "The checkpoint id of the model." }, "privateEndpoints": { "$ref": "GoogleCloudAiplatformV1PrivateEndpoints", "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 }, "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" }, "serviceAccount": { "type": "string", "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." } }, "description": "A deployment of a Model. Endpoints contain one or more DeployedModels." }, "GoogleCloudAiplatformV1CopyModelOperationMetadata": { "id": "GoogleCloudAiplatformV1CopyModelOperationMetadata", "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "type": "object", "description": "Details of ModelService.CopyModel operation." }, "GoogleCloudAiplatformV1SchemaPredictParamsVideoObjectTrackingPredictionParams": { "id": "GoogleCloudAiplatformV1SchemaPredictParamsVideoObjectTrackingPredictionParams", "type": "object", "description": "Prediction model parameters for Video Object Tracking.", "properties": { "minBoundingBoxSize": { "type": "number", "description": "Only bounding boxes with shortest edge at least that long as a relative value of video frame size are returned. Default value is 0.0.", "format": "float" }, "confidenceThreshold": { "type": "number", "format": "float", "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0" }, "maxPredictions": { "format": "int32", "type": "integer", "description": "The model only returns up to that many top, by confidence score, predictions per frame of the video. If this number is very high, the Model may return fewer predictions per frame. Default value is 50." } } }, "GoogleCloudAiplatformV1ExportModelRequestOutputConfig": { "properties": { "exportFormatId": { "description": "The ID of the format in which the Model must be exported. Each Model lists the export formats it supports. If no value is provided here, then the first from the list of the Model's supported formats is used by default.", "type": "string" }, "imageDestination": { "$ref": "GoogleCloudAiplatformV1ContainerRegistryDestination", "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`." }, "artifactDestination": { "$ref": "GoogleCloudAiplatformV1GcsDestination", "description": "The Cloud Storage location where the Model artifact is to be written to. Under the directory given as the destination a new one with name \"`model-export--`\", where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format, will be created. Inside, the Model and any of its supporting files will be written. This field should only be set when the `exportableContent` field of the [Model.supported_export_formats] object contains `ARTIFACT`." } }, "type": "object", "description": "Output configuration for the Model export.", "id": "GoogleCloudAiplatformV1ExportModelRequestOutputConfig" }, "GoogleCloudAiplatformV1SearchNearestEntitiesRequest": { "type": "object", "id": "GoogleCloudAiplatformV1SearchNearestEntitiesRequest", "description": "The request message for FeatureOnlineStoreService.SearchNearestEntities.", "properties": { "query": { "description": "Required. The query.", "$ref": "GoogleCloudAiplatformV1NearestNeighborQuery" }, "returnFullEntity": { "type": "boolean", "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." } } }, "GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature": { "description": "Noise sigma for a single feature.", "id": "GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature", "properties": { "sigma": { "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", "format": "float" }, "name": { "description": "The name of the input feature for which noise sigma is provided. The features are defined in explanation metadata inputs.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1ExplanationSpecOverride": { "id": "GoogleCloudAiplatformV1ExplanationSpecOverride", "type": "object", "description": "The ExplanationSpec entries that can be overridden at online explanation time.", "properties": { "examplesOverride": { "description": "The example-based explanations parameter overrides.", "$ref": "GoogleCloudAiplatformV1ExamplesOverride" }, "metadata": { "description": "The metadata to be overridden. If not specified, no metadata is overridden.", "$ref": "GoogleCloudAiplatformV1ExplanationMetadataOverride" }, "parameters": { "$ref": "GoogleCloudAiplatformV1ExplanationParameters", "description": "The parameters to be overridden. Note that the attribution method cannot be changed. If not specified, no parameter is overridden." } } }, "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSourceEvent": { "description": "A single conversation event.", "id": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSourceEvent", "properties": { "content": { "description": "Required. Represents the content of the event.", "$ref": "GoogleCloudAiplatformV1Content" } }, "type": "object" }, "GenaiVertexV1FileSearchCallStep": { "id": "GenaiVertexV1FileSearchCallStep", "type": "object", "description": "File Search call step.", "properties": {} }, "GoogleCloudAiplatformV1LogprobsResultCandidate": { "id": "GoogleCloudAiplatformV1LogprobsResultCandidate", "type": "object", "description": "A single token and its associated log probability.", "properties": { "tokenId": { "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", "type": "integer" }, "token": { "description": "The token's string representation.", "type": "string" }, "logProbability": { "format": "float", "type": "number", "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." } } }, "CloudAiLargeModelsVisionSemanticFilterResponse": { "id": "CloudAiLargeModelsVisionSemanticFilterResponse", "type": "object", "properties": { "passedSemanticFilter": { "type": "boolean", "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." }, "namedBoundingBoxes": { "items": { "$ref": "CloudAiLargeModelsVisionNamedBoundingBox" }, "description": "Class labels of the bounding boxes that failed the semantic filtering. Bounding box coordinates.", "type": "array" } } }, "GenaiVertexV1McpServer": { "description": "A MCPServer is a server that can be called by the model to perform actions.", "properties": { "url": { "description": "The full URL for the MCPServer endpoint. Example: \"https://api.example.com/mcp\"", "type": "string" }, "headers": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional: Fields for authentication headers, timeouts, etc., if needed." }, "allowedTools": { "items": { "$ref": "GenaiVertexV1AllowedTools" }, "description": "The allowed tools.", "type": "array" }, "name": { "description": "The name of the MCPServer.", "type": "string" } }, "id": "GenaiVertexV1McpServer", "type": "object" }, "GoogleCloudAiplatformV1UpgradeNotebookRuntimeRequest": { "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1UpgradeNotebookRuntimeRequest", "description": "Request message for NotebookService.UpgradeNotebookRuntime." }, "GoogleCloudAiplatformV1PurgeContextsMetadata": { "properties": { "genericMetadata": { "description": "Operation metadata for purging Contexts.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1PurgeContextsMetadata", "type": "object", "description": "Details of operations that perform MetadataService.PurgeContexts." }, "GoogleCloudAiplatformV1AgentEvent": { "id": "GoogleCloudAiplatformV1AgentEvent", "type": "object", "properties": { "eventTime": { "type": "string", "description": "Optional. The timestamp when the event occurred.", "format": "google-datetime" }, "content": { "$ref": "GoogleCloudAiplatformV1Content", "description": "Required. The content of the event (e.g., text response, tool call, tool response)." }, "author": { "type": "string", "description": "Required. The ID of the agent or entity that generated this event. Use \"user\" to denote events generated by the end-user." }, "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": { "$ref": "GoogleCloudAiplatformV1Tool" } }, "stateDelta": { "description": "Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "description": "Represents a single event in the execution trace." }, "GoogleCloudAiplatformV1ExamplesExampleGcsSource": { "description": "The Cloud Storage input instances.", "properties": { "dataFormat": { "enumDescriptions": [ "Format unspecified, used when unset.", "Examples are stored in JSONL files." ], "description": "The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported.", "type": "string", "enum": [ "DATA_FORMAT_UNSPECIFIED", "JSONL" ] }, "gcsSource": { "description": "The Cloud Storage location for the input instances.", "$ref": "GoogleCloudAiplatformV1GcsSource" } }, "id": "GoogleCloudAiplatformV1ExamplesExampleGcsSource", "type": "object" }, "GoogleCloudAiplatformV1ContainerRegistryDestination": { "description": "The Container Registry location for the container image.", "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" } }, "type": "object", "id": "GoogleCloudAiplatformV1ContainerRegistryDestination" }, "GoogleCloudAiplatformV1ResponseFormat": { "id": "GoogleCloudAiplatformV1ResponseFormat", "type": "object", "properties": { "image": { "$ref": "GoogleCloudAiplatformV1ImageResponseFormat", "description": "Image output format." }, "text": { "description": "Text output format.", "$ref": "GoogleCloudAiplatformV1TextResponseFormat" }, "video": { "description": "Video output format.", "$ref": "GoogleCloudAiplatformV1VideoResponseFormat" }, "audio": { "description": "Audio output format.", "$ref": "GoogleCloudAiplatformV1AudioResponseFormat" } }, "description": "Configuration for the model to configure output formatting and delivery." }, "GoogleCloudLocationListLocationsResponse": { "properties": { "locations": { "type": "array", "items": { "$ref": "GoogleCloudLocationLocation" }, "description": "A list of locations that matches the specified filter in the request." }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "id": "GoogleCloudLocationListLocationsResponse", "description": "The response message for Locations.ListLocations.", "type": "object" }, "GoogleCloudAiplatformV1EvaluationPrompt": { "description": "Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations.", "type": "object", "id": "GoogleCloudAiplatformV1EvaluationPrompt", "properties": { "text": { "description": "Text prompt.", "type": "string" }, "agentData": { "$ref": "GoogleCloudAiplatformV1AgentData", "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." }, "value": { "description": "Fields and values that can be used to populate the prompt template.", "type": "any" }, "promptTemplateData": { "$ref": "GoogleCloudAiplatformV1EvaluationPromptPromptTemplateData", "description": "Prompt template data." }, "userScenario": { "$ref": "GoogleCloudAiplatformV1EvaluationPromptUserScenario", "description": "Optional. The generated user scenario used to drive multi-turn agent running results." } } }, "GoogleCloudAiplatformV1TrajectoryExactMatchSpec": { "description": "Spec for TrajectoryExactMatch metric - returns 1 if tool calls in the reference trajectory exactly match the predicted trajectory, else 0.", "id": "GoogleCloudAiplatformV1TrajectoryExactMatchSpec", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1PublisherModelCallToActionOpenNotebooks": { "type": "object", "description": "Open notebooks.", "id": "GoogleCloudAiplatformV1PublisherModelCallToActionOpenNotebooks", "properties": { "notebooks": { "items": { "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" }, "description": "Required. Regional resource references to notebooks.", "type": "array" } } }, "GenaiVertexV1FileCitation": { "id": "GenaiVertexV1FileCitation", "properties": { "fileName": { "description": "The name of the file.", "type": "string" }, "source": { "description": "Source attributed for a portion of the text.", "type": "string" }, "pageNumber": { "description": "Page number of the cited document, if applicable.", "type": "integer", "format": "int32" }, "customMetadata": { "description": "User provided metadata about the retrieved context.", "type": "object", "additionalProperties": { "description": "Properties of the object.", "type": "any" } }, "mediaId": { "type": "string", "description": "Media ID in-case of image citations, if applicable." }, "documentUri": { "description": "The URI of the file.", "type": "string" } }, "type": "object", "description": "A file citation annotation." }, "GoogleCloudAiplatformV1EvaluationRunMetricRubricGenerationSpec": { "type": "object", "id": "GoogleCloudAiplatformV1EvaluationRunMetricRubricGenerationSpec", "description": "Specification for how rubrics should be generated.", "properties": { "modelConfig": { "description": "Optional. Configuration for the model used in rubric generation. Configs including sampling count and base model can be specified here. Flipping is not supported for rubric generation.", "$ref": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigAutoraterConfig" }, "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." }, "rubricContentType": { "enum": [ "RUBRIC_CONTENT_TYPE_UNSPECIFIED", "PROPERTY", "NL_QUESTION_ANSWER", "PYTHON_CODE_ASSERTION" ], "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." ], "type": "string", "description": "Optional. The type of rubric content to be generated." }, "promptTemplate": { "type": "string", "description": "Optional. Template for the prompt used to generate rubrics. The details should be updated based on the most-recent recipe requirements." }, "metricResourceName": { "type": "string", "description": "Optional. Resource name of the metric definition." } } }, "GoogleCloudAiplatformV1PipelineTemplateMetadata": { "id": "GoogleCloudAiplatformV1PipelineTemplateMetadata", "properties": { "version": { "type": "string", "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...\"." } }, "description": "Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry.", "type": "object" }, "GoogleCloudAiplatformV1QueryReasoningEngineRequest": { "description": "Request message for ReasoningEngineExecutionService.QueryReasoningEngine.", "properties": { "input": { "type": "object", "description": "Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc.", "additionalProperties": { "description": "Properties of the object.", "type": "any" } }, "classMethod": { "description": "Optional. Class method to be used for the query. It is optional and defaults to \"query\" if unspecified.", "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1QueryReasoningEngineRequest" }, "GoogleCloudAiplatformV1UploadModelResponse": { "id": "GoogleCloudAiplatformV1UploadModelResponse", "description": "Response message of ModelService.UploadModel operation.", "type": "object", "properties": { "model": { "type": "string", "description": "The name of the uploaded Model resource. Format: `projects/{project}/locations/{location}/models/{model}`" }, "modelVersionId": { "readOnly": true, "description": "Output only. The version ID of the model that is uploaded.", "type": "string" } } }, "GoogleCloudAiplatformV1MemoryConjunctionFilter": { "description": "A conjunction of filters that will be combined using AND logic.", "type": "object", "properties": { "filters": { "type": "array", "description": "Represents filters that will be combined using AND logic.", "items": { "$ref": "GoogleCloudAiplatformV1MemoryFilter" } } }, "id": "GoogleCloudAiplatformV1MemoryConjunctionFilter" }, "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfigSourceEntry": { "properties": { "type": { "enumDeprecated": [ false, false, true, false, false ], "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." ], "enum": [ "UNSPECIFIED", "WEB", "ENTERPRISE", "VERTEX_AI_SEARCH", "INLINE" ], "description": "The type of the grounding checking source." }, "vertexAiSearchDatastore": { "description": "The uri of the Vertex AI Search data source.", "type": "string" }, "inlineContext": { "description": "The grounding text passed inline with the Predict API. It can support up to 1 million bytes.", "type": "string" }, "enterpriseDatastore": { "description": "The uri of the Vertex AI Search data source. Deprecated. Use vertex_ai_search_datastore instead.", "type": "string", "deprecated": true } }, "type": "object", "description": "Single source entry for the grounding checking.", "id": "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfigSourceEntry" }, "GoogleCloudAiplatformV1OnlineEvaluator": { "id": "GoogleCloudAiplatformV1OnlineEvaluator", "description": "An OnlineEvaluator contains the configuration for an Online Evaluation.", "properties": { "state": { "description": "Output only. The state of the OnlineEvaluator.", "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.", "Indicates that the OnlineEvaluator is in a warning state. This can happen if, for example, some of the metrics in the `metric_sources` are invalid. Evaluation will still run with the remaining valid metrics." ], "readOnly": true, "type": "string", "enum": [ "STATE_UNSPECIFIED", "ACTIVE", "SUSPENDED", "FAILED", "WARNING" ] }, "stateDetails": { "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.", "items": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorStateDetails" }, "type": "array", "readOnly": true }, "metricSources": { "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.", "items": { "$ref": "GoogleCloudAiplatformV1MetricSource" }, "type": "array" }, "displayName": { "type": "string", "description": "Optional. Human-readable name for the OnlineEvaluator. The name doesn't have to be unique. The name can consist of any UTF-8 characters. The maximum length is `63` characters. If the display name exceeds max characters, an `INVALID_ARGUMENT` error is returned." }, "updateTime": { "description": "Output only. Timestamp when the OnlineEvaluator was last updated.", "type": "string", "format": "google-datetime", "readOnly": true }, "agentResource": { "type": "string", "description": "Required. Immutable. The name of the agent that the OnlineEvaluator evaluates periodically. This value is used to filter the traces with a matching cloud.resource_id and link the evaluation results with relevant dashboards/UIs. This field is immutable. Once set, it cannot be changed." }, "createTime": { "description": "Output only. Timestamp when the OnlineEvaluator was created.", "readOnly": true, "format": "google-datetime", "type": "string" }, "config": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorConfig", "description": "Required. Configuration for the OnlineEvaluator." }, "name": { "description": "Identifier. The resource name of the OnlineEvaluator. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}.", "type": "string" }, "cloudObservability": { "description": "Data source for the OnlineEvaluator, based on Google Cloud Observability stack (Cloud Trace & Cloud Logging).", "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservability" } }, "type": "object" }, "GoogleCloudAiplatformV1DeployedModelStatus": { "description": "Runtime status of the deployed model.", "properties": { "lastUpdateTime": { "format": "google-datetime", "description": "Output only. The time at which the status was last updated.", "type": "string", "readOnly": true }, "message": { "type": "string", "readOnly": true, "description": "Output only. The latest deployed model's status message (if any)." }, "availableReplicaCount": { "readOnly": true, "format": "int32", "type": "integer", "description": "Output only. The number of available replicas of the deployed model." } }, "id": "GoogleCloudAiplatformV1DeployedModelStatus", "type": "object" }, "GoogleCloudAiplatformV1NasJob": { "type": "object", "description": "Represents a Neural Architecture Search (NAS) job.", "id": "GoogleCloudAiplatformV1NasJob", "properties": { "nasJobOutput": { "$ref": "GoogleCloudAiplatformV1NasJobOutput", "description": "Output only. Output of the NasJob.", "readOnly": true }, "name": { "description": "Output only. Resource name of the NasJob.", "type": "string", "readOnly": true }, "satisfiesPzi": { "readOnly": true, "description": "Output only. Reserved for future use.", "type": "boolean" }, "error": { "description": "Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.", "$ref": "GoogleRpcStatus", "readOnly": true }, "encryptionSpec": { "description": "Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "startTime": { "readOnly": true, "type": "string", "description": "Output only. Time when the NasJob for the first time entered the `JOB_STATE_RUNNING` state.", "format": "google-datetime" }, "labels": { "type": "object", "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.", "additionalProperties": { "type": "string" } }, "nasJobSpec": { "description": "Required. The specification of a NasJob.", "$ref": "GoogleCloudAiplatformV1NasJobSpec" }, "updateTime": { "format": "google-datetime", "type": "string", "readOnly": true, "description": "Output only. Time when the NasJob was most recently updated." }, "displayName": { "type": "string", "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." }, "endTime": { "type": "string", "readOnly": true, "description": "Output only. Time when the NasJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", "format": "google-datetime" }, "createTime": { "description": "Output only. Time when the NasJob was created.", "readOnly": true, "type": "string", "format": "google-datetime" }, "state": { "type": "string", "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" ], "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." }, "enableRestrictedImageTraining": { "description": "Optional. Enable a separation of Custom model training and restricted image training for tenant project.", "deprecated": true, "type": "boolean" } } }, "GoogleCloudAiplatformV1RagQuery": { "properties": { "text": { "description": "Optional. The query in text format to get relevant contexts.", "type": "string" }, "ragRetrievalConfig": { "description": "Optional. The retrieval config for the query.", "$ref": "GoogleCloudAiplatformV1RagRetrievalConfig" } }, "type": "object", "description": "A query to retrieve relevant contexts.", "id": "GoogleCloudAiplatformV1RagQuery" }, "GoogleCloudAiplatformV1BatchReadFeatureValuesOperationMetadata": { "type": "object", "properties": { "genericMetadata": { "description": "Operation metadata for Featurestore batch read Features values.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1BatchReadFeatureValuesOperationMetadata", "description": "Details of operations that batch reads Feature values." }, "GoogleCloudAiplatformV1CompactSessionRequest": { "id": "GoogleCloudAiplatformV1CompactSessionRequest", "description": "Request message for SessionService.CompactSession.", "type": "object", "properties": { "compaction": { "description": "Required. The compaction configuration to apply. At least one compaction category (summarization or event editing) must be enabled within it.", "$ref": "GoogleCloudAiplatformV1CompactionConfig" } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation": { "type": "object", "properties": { "timestamp": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation" }, "text": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation" }, "repeatedCategorical": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation" }, "categorical": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation" }, "repeatedNumeric": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation" }, "repeatedText": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation" }, "auto": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation" }, "numeric": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation" }, "GoogleCloudAiplatformV1IndexDatapointCrowdingTag": { "type": "object", "id": "GoogleCloudAiplatformV1IndexDatapointCrowdingTag", "properties": { "crowdingAttribute": { "type": "string", "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." } }, "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." }, "GenaiVertexV1ReviewSnippet": { "type": "object", "id": "GenaiVertexV1ReviewSnippet", "properties": { "url": { "description": "A link that corresponds to the user review on Google Maps.", "type": "string" }, "reviewId": { "description": "The ID of the review snippet.", "type": "string" }, "title": { "description": "Title of the review.", "type": "string" } }, "description": "Encapsulates a snippet of a user review that answers a question about the features of a specific place in Google Maps." }, "GoogleCloudAiplatformV1DynamicRetrievalConfig": { "type": "object", "properties": { "mode": { "description": "The mode of the predictor to be used in dynamic retrieval.", "enumDescriptions": [ "Always trigger retrieval.", "Run retrieval only when system decides it is necessary." ], "enum": [ "MODE_UNSPECIFIED", "MODE_DYNAMIC" ], "type": "string" }, "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.", "id": "GoogleCloudAiplatformV1DynamicRetrievalConfig" }, "GoogleCloudAiplatformV1ExternalApi": { "properties": { "simpleSearchParams": { "description": "Parameters for the simple search API.", "$ref": "GoogleCloudAiplatformV1ExternalApiSimpleSearchParams" }, "elasticSearchParams": { "$ref": "GoogleCloudAiplatformV1ExternalApiElasticSearchParams", "description": "Parameters for the elastic search API." }, "authConfig": { "description": "The authentication config to access the API.", "$ref": "GoogleCloudAiplatformV1AuthConfig" }, "apiSpec": { "enum": [ "API_SPEC_UNSPECIFIED", "SIMPLE_SEARCH", "ELASTIC_SEARCH" ], "type": "string", "enumDescriptions": [ "Unspecified API spec. This value should not be used.", "Simple search API spec.", "Elastic search API spec." ], "description": "The API spec that the external API implements." }, "endpoint": { "type": "string", "description": "The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search" }, "apiAuth": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1ApiAuth", "description": "The authentication config to access the API. Deprecated. Please use auth_config instead." } }, "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.", "id": "GoogleCloudAiplatformV1ExternalApi", "type": "object" }, "GoogleCloudAiplatformV1StudySpecStudyStoppingConfig": { "description": "The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.", "id": "GoogleCloudAiplatformV1StudySpecStudyStoppingConfig", "type": "object", "properties": { "maxNumTrials": { "format": "int32", "type": "integer", "description": "If there are more than this many trials, stop the study." }, "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" }, "maximumRuntimeConstraint": { "$ref": "GoogleCloudAiplatformV1StudyTimeConstraint", "description": "If the specified time or duration has passed, stop the study." }, "maxDurationNoProgress": { "format": "google-duration", "type": "string", "description": "If the objective value has not improved for this much time, stop the study. WARNING: Effective only for single-objective studies." }, "minimumRuntimeConstraint": { "description": "Each \"stopping rule\" in this proto specifies an \"if\" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting `min_num_trials=5` and `always_stop_after= 1 hour` means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose \"if\" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to _resume_ a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study.", "$ref": "GoogleCloudAiplatformV1StudyTimeConstraint" }, "minNumTrials": { "type": "integer", "format": "int32", "description": "If there are fewer than this many COMPLETED trials, do not stop the study." }, "maxNumTrialsNoProgress": { "description": "If the objective value has not improved for this many consecutive trials, stop the study. WARNING: Effective only for single-objective studies.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1EventMetadata": { "properties": { "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" }, "longRunningToolIds": { "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.", "type": "array" }, "inputTranscription": { "description": "Optional. Audio transcription of user input.", "$ref": "GoogleCloudAiplatformV1Transcription" }, "turnComplete": { "description": "Optional. Indicates whether the response from the model is complete. Only used for streaming mode.", "type": "boolean" }, "customMetadata": { "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "type": "object", "description": "The custom metadata of the LlmResponse." }, "branch": { "description": "Optional. The branch of the event. The format is like agent_1.agent_2.agent_3, where agent_1 is the parent of agent_2, and agent_2 is the parent of agent_3. Branch is used when multiple child agents shouldn't see their siblings' conversation history.", "type": "string" }, "partial": { "type": "boolean", "description": "Optional. Indicates whether the text content is part of a unfinished text stream. Only used for streaming mode and when the content is plain text." }, "outputTranscription": { "$ref": "GoogleCloudAiplatformV1Transcription", "description": "Optional. Audio transcription of model output." }, "groundingMetadata": { "description": "Optional. Metadata returned to client when grounding is enabled.", "$ref": "GoogleCloudAiplatformV1GroundingMetadata" } }, "type": "object", "description": "Metadata relating to a LLM response event.", "id": "GoogleCloudAiplatformV1EventMetadata" }, "GoogleCloudAiplatformV1VertexRagStoreRagResource": { "id": "GoogleCloudAiplatformV1VertexRagStoreRagResource", "description": "The definition of the Rag resource.", "type": "object", "properties": { "ragFileIds": { "type": "array", "description": "Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.", "items": { "type": "string" } }, "ragCorpus": { "type": "string", "description": "Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`" } } }, "GoogleCloudAiplatformV1SearchFeaturesResponse": { "type": "object", "id": "GoogleCloudAiplatformV1SearchFeaturesResponse", "properties": { "features": { "type": "array", "description": "The Features matching the request. Fields returned: * `name` * `description` * `labels` * `create_time` * `update_time`", "items": { "$ref": "GoogleCloudAiplatformV1Feature" } }, "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" } }, "description": "Response message for FeaturestoreService.SearchFeatures." }, "GoogleCloudAiplatformV1MutateDeployedIndexResponse": { "id": "GoogleCloudAiplatformV1MutateDeployedIndexResponse", "description": "Response message for IndexEndpointService.MutateDeployedIndex.", "type": "object", "properties": { "deployedIndex": { "description": "The DeployedIndex that had been updated in the IndexEndpoint.", "$ref": "GoogleCloudAiplatformV1DeployedIndex" } } }, "GoogleCloudAiplatformV1ExactMatchMetricValue": { "type": "object", "id": "GoogleCloudAiplatformV1ExactMatchMetricValue", "properties": { "score": { "readOnly": true, "description": "Output only. Exact match score.", "type": "number", "format": "float" } }, "description": "Exact match metric value for an instance." }, "GoogleCloudAiplatformV1Scalar": { "type": "object", "description": "One point viewable on a scalar metric plot.", "id": "GoogleCloudAiplatformV1Scalar", "properties": { "value": { "type": "number", "description": "Value of the point at this step / timestamp.", "format": "double" } } }, "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityOpenTelemetry": { "type": "object", "id": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityOpenTelemetry", "properties": { "semconvVersion": { "type": "string", "description": "Required. Defines which version OTel Semantic Convention the data follows. Can be \"1.39.0\" or newer." } }, "description": "Configuration for data source following OpenTelemetry." }, "GoogleCloudAiplatformV1DeployModelResponse": { "type": "object", "properties": { "deployedModel": { "$ref": "GoogleCloudAiplatformV1DeployedModel", "description": "The DeployedModel that had been deployed in the Endpoint." } }, "id": "GoogleCloudAiplatformV1DeployModelResponse", "description": "Response message for EndpointService.DeployModel." }, "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilitySessionScopePredicate": { "properties": { "duration": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityNumericPredicate", "description": "Filter on the duration of a session (in seconds)." }, "totalTokenUsage": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityNumericPredicate", "description": "Filter on the total token usage within a session." }, "modelCallErrors": { "description": "Filter on the number of LLM call errors within a session.", "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityNumericPredicate" }, "modelCalls": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityNumericPredicate", "description": "Filter on the number of underlying LLM calls within a session." }, "userTurns": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityNumericPredicate", "description": "Filter on the number of user turns within a session." }, "toolCallErrors": { "description": "Filter on the number of tool call errors within a session.", "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityNumericPredicate" }, "serviceVersion": { "description": "Filter on the versions that served a session (`service.version` OTel resource attribute); matches if any of them is listed. At most one is allowed. On Vertex AI Agent Engine, this is the runtime revision id, currently set only for agents created via v1beta1.", "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityStringPredicate" }, "toolCalls": { "description": "Filter on the number of underlying tool calls within a session.", "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityNumericPredicate" } }, "id": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilitySessionScopePredicate", "type": "object", "description": "Defines a single filter predicate." }, "GoogleCloudAiplatformV1UpdateIndexOperationMetadata": { "description": "Runtime operation information for IndexService.UpdateIndex.", "id": "GoogleCloudAiplatformV1UpdateIndexOperationMetadata", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The operation generic information." }, "nearestNeighborSearchOperationMetadata": { "$ref": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadata", "description": "The operation metadata with regard to Matching Engine Index operation." } }, "type": "object" }, "GoogleCloudAiplatformV1DeployedModelRef": { "id": "GoogleCloudAiplatformV1DeployedModelRef", "properties": { "checkpointId": { "type": "string", "description": "Immutable. The ID of the Checkpoint deployed in the DeployedModel." }, "deployedModelId": { "type": "string", "description": "Immutable. An ID of a DeployedModel in the above Endpoint." }, "endpoint": { "type": "string", "description": "Immutable. A resource name of an Endpoint." } }, "type": "object", "description": "Points to a DeployedModel." }, "GenaiVertexV1RetrievalCallDelta": { "properties": { "arguments": { "$ref": "GenaiVertexV1RetrievalCallStepRetrievalStepArguments", "description": "Required. The arguments to pass to the Retrieval tool." }, "retrievalType": { "description": "The type of retrieval tools.", "enumDescriptions": [ "", "", "", "", "" ], "enum": [ "RETRIEVAL_TYPE_UNSPECIFIED", "RETRIEVAL_TYPE_VERTEX_AI_SEARCH", "RETRIEVAL_TYPE_RAG_STORE", "RETRIEVAL_TYPE_EXA_AI_SEARCH", "RETRIEVAL_TYPE_PARALLEL_AI_SEARCH" ], "type": "string" } }, "type": "object", "description": "Used by Vertex Retrieval tools such as Parallel AI, Exa AI, Vertex AI Search, etc. RetrievalType decides which tool is used.", "id": "GenaiVertexV1RetrievalCallDelta" }, "GoogleCloudAiplatformV1FluencyResult": { "properties": { "score": { "type": "number", "readOnly": true, "format": "float", "description": "Output only. Fluency score." }, "confidence": { "format": "float", "type": "number", "description": "Output only. Confidence for fluency score.", "readOnly": true }, "explanation": { "readOnly": true, "description": "Output only. Explanation for fluency score.", "type": "string" } }, "description": "Spec for fluency result.", "type": "object", "id": "GoogleCloudAiplatformV1FluencyResult" }, "GoogleCloudAiplatformV1CometInstance": { "id": "GoogleCloudAiplatformV1CometInstance", "description": "Spec for Comet instance - The fields used for evaluation are dependent on the comet version.", "type": "object", "properties": { "source": { "description": "Optional. Source text in original language.", "type": "string" }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "reference": { "type": "string", "description": "Optional. Ground truth used to compare against the prediction." } } }, "GoogleCloudAiplatformV1AgentResponseCustomization": { "description": "Customizes the agent's response to the end user when a `SemanticGovernancePolicy` is evaluated (for example, with a custom message shown on denial).", "type": "object", "id": "GoogleCloudAiplatformV1AgentResponseCustomization", "properties": { "denialMessage": { "description": "Optional. Custom message shown to the end user when the policy check results in a denial. Use this to explain the rationale to the user. Max 1000 characters.", "type": "string" } } }, "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfig": { "description": "The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated.", "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfig", "type": "object", "properties": { "enableFeatureAttributes": { "type": "boolean", "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." }, "explanationBaseline": { "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline", "description": "Predictions generated by the BatchPredictionJob using baseline dataset." } } }, "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigSimilaritySearchConfig": { "id": "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigSimilaritySearchConfig", "description": "Configuration for how to perform similarity search on memories.", "type": "object", "properties": { "embeddingModel": { "type": "string", "description": "Required. The model used to generate embeddings to lookup similar memories. Format: `projects/{project}/locations/{location}/publishers/google/models/{model}`." } } }, "GoogleCloudAiplatformV1SchemaPromptSpecTranslationOption": { "description": "Optional settings for translation prompt.", "id": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationOption", "type": "object", "properties": { "numberOfShots": { "format": "int32", "description": "How many shots to use.", "type": "integer" } } }, "GoogleCloudAiplatformV1ExplainResponse": { "properties": { "deployedModelId": { "description": "ID of the Endpoint's DeployedModel that served this explanation.", "type": "string" }, "explanations": { "items": { "$ref": "GoogleCloudAiplatformV1Explanation" }, "type": "array", "description": "The explanations of the Model's PredictResponse.predictions. It has the same number of elements as instances to be explained." }, "predictions": { "items": { "type": "any" }, "description": "The predictions that are the output of the predictions call. Same as PredictResponse.predictions.", "type": "array" } }, "description": "Response message for PredictionService.Explain.", "id": "GoogleCloudAiplatformV1ExplainResponse", "type": "object" }, "GoogleCloudAiplatformV1ExplanationMetadataInputMetadata": { "properties": { "modality": { "description": "Modality of the feature. Valid values are: numeric, image. Defaults to numeric.", "type": "string" }, "indexFeatureMapping": { "type": "array", "items": { "type": "string" }, "description": "A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR." }, "encodedBaselines": { "description": "A list of baselines for the encoded tensor. The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.", "type": "array", "items": { "type": "any" } }, "indicesTensorName": { "description": "Specifies the index of the values of the input tensor. Required when the input tensor is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.", "type": "string" }, "featureValueDomain": { "description": "The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.", "$ref": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain" }, "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" }, "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" }, "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." }, "inputTensorName": { "description": "Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow.", "type": "string" }, "visualization": { "description": "Visualization configurations for image explanation.", "$ref": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization" }, "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" }, "encoding": { "type": "string", "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.", "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]] ```" ] } }, "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.", "id": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadata" }, "GoogleCloudAiplatformV1BatchCancelPipelineJobsRequest": { "id": "GoogleCloudAiplatformV1BatchCancelPipelineJobsRequest", "description": "Request message for PipelineService.BatchCancelPipelineJobs.", "properties": { "names": { "type": "array", "items": { "type": "string" }, "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": "object" }, "GoogleCloudAiplatformV1DatasetDistribution": { "properties": { "median": { "description": "Output only. The median of the values in the population.", "readOnly": true, "type": "number", "format": "double" }, "min": { "readOnly": true, "description": "Output only. The minimum of the population values.", "format": "double", "type": "number" }, "p5": { "format": "double", "type": "number", "description": "Output only. The 5th percentile of the values in the population.", "readOnly": true }, "buckets": { "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1DatasetDistributionDistributionBucket" }, "description": "Output only. Defines the histogram bucket.", "type": "array" }, "mean": { "readOnly": true, "format": "double", "type": "number", "description": "Output only. The arithmetic mean of the values in the population." }, "sum": { "description": "Output only. Sum of a given population of values.", "readOnly": true, "format": "double", "type": "number" }, "max": { "description": "Output only. The maximum of the population values.", "format": "double", "type": "number", "readOnly": true }, "p95": { "format": "double", "type": "number", "description": "Output only. The 95th percentile of the values in the population.", "readOnly": true } }, "id": "GoogleCloudAiplatformV1DatasetDistribution", "description": "Distribution computed over a tuning dataset.", "type": "object" }, "GoogleCloudAiplatformV1DatasetDistributionDistributionBucket": { "description": "Dataset bucket used to create a histogram for the distribution given a population of values.", "type": "object", "id": "GoogleCloudAiplatformV1DatasetDistributionDistributionBucket", "properties": { "left": { "description": "Output only. Left bound of the bucket.", "format": "double", "readOnly": true, "type": "number" }, "count": { "readOnly": true, "format": "int64", "type": "string", "description": "Output only. Number of values in the bucket." }, "right": { "type": "number", "format": "double", "description": "Output only. Right bound of the bucket.", "readOnly": true } } }, "GoogleCloudAiplatformV1SandboxEnvironmentSnapshot": { "type": "object", "id": "GoogleCloudAiplatformV1SandboxEnvironmentSnapshot", "properties": { "displayName": { "description": "Required. The display name of the SandboxEnvironmentSnapshot.", "type": "string" }, "ttl": { "description": "Optional. Input only. The TTL for the sandbox environment snapshot. The expiration time is computed: now + TTL.", "type": "string", "format": "google-duration" }, "sourceSandboxEnvironment": { "description": "Required. The resource name of the source SandboxEnvironment this snapshot was taken from.", "type": "string" }, "sizeBytes": { "readOnly": true, "type": "string", "format": "int64", "description": "Optional. Output only. Size of the snapshot data in bytes." }, "expireTime": { "format": "google-datetime", "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.", "type": "string" }, "createTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. The timestamp when this SandboxEnvironmentSnapshot was created." }, "parentSnapshot": { "type": "string", "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.", "readOnly": true }, "owner": { "type": "string", "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." }, "name": { "description": "Identifier. The resource name of the SandboxEnvironmentSnapshot. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentSnapshots/{sandbox_environment_snapshot}`", "type": "string" }, "postSnapshotAction": { "enum": [ "POST_SNAPSHOT_ACTION_UNSPECIFIED", "RUNNING", "PAUSE" ], "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.", "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." ], "type": "string" }, "updateTime": { "format": "google-datetime", "description": "Output only. The timestamp when this SandboxEnvironment was most recently updated.", "type": "string", "readOnly": true } }, "description": "SandboxEnvironmentSnapshot is a snapshot of the SandboxEnvironment." }, "GoogleCloudAiplatformV1ModelEvaluationModelEvaluationExplanationSpec": { "id": "GoogleCloudAiplatformV1ModelEvaluationModelEvaluationExplanationSpec", "type": "object", "properties": { "explanationType": { "type": "string", "description": "Explanation type. For AutoML Image Classification models, possible values are: * `image-integrated-gradients` * `image-xrai`" }, "explanationSpec": { "description": "Explanation spec details.", "$ref": "GoogleCloudAiplatformV1ExplanationSpec" } } }, "GoogleCloudAiplatformV1StudySpec": { "type": "object", "id": "GoogleCloudAiplatformV1StudySpec", "properties": { "studyStoppingConfig": { "description": "Conditions for automated stopping of a Study. Enable automated stopping by configuring at least one condition.", "$ref": "GoogleCloudAiplatformV1StudySpecStudyStoppingConfig" }, "convexAutomatedStoppingSpec": { "description": "The automated early stopping spec using convex stopping rule.", "$ref": "GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpec" }, "measurementSelectionType": { "enumDescriptions": [ "Will be treated as LAST_MEASUREMENT.", "Use the last measurement reported.", "Use the best measurement reported." ], "description": "Describe which measurement selection type will be used", "type": "string", "enum": [ "MEASUREMENT_SELECTION_TYPE_UNSPECIFIED", "LAST_MEASUREMENT", "BEST_MEASUREMENT" ] }, "observationNoise": { "enumDescriptions": [ "The default noise level chosen by Vertex AI.", "Vertex AI assumes that the objective function is (nearly) perfectly reproducible, and will never repeat the same Trial parameters.", "Vertex AI will estimate the amount of noise in metric evaluations, it may repeat the same Trial parameters more than once." ], "enum": [ "OBSERVATION_NOISE_UNSPECIFIED", "LOW", "HIGH" ], "type": "string", "description": "The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline." }, "metrics": { "items": { "$ref": "GoogleCloudAiplatformV1StudySpecMetricSpec" }, "description": "Required. Metric specs for the Study.", "type": "array" }, "medianAutomatedStoppingSpec": { "description": "The automated early stopping spec using median rule.", "$ref": "GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpec" }, "parameters": { "type": "array", "description": "Required. The set of parameters to tune.", "items": { "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpec" } }, "decayCurveStoppingSpec": { "description": "The automated early stopping spec using decay curve rule.", "$ref": "GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpec" }, "algorithm": { "enumDescriptions": [ "The default algorithm used by Vertex AI for [hyperparameter tuning](https://cloud.google.com/vertex-ai/docs/training/hyperparameter-tuning-overview) and [Vertex AI Vizier](https://cloud.google.com/vertex-ai/docs/vizier).", "Simple grid search within the feasible space. To use grid search, all parameters must be `INTEGER`, `CATEGORICAL`, or `DISCRETE`.", "Simple random search within the feasible space." ], "type": "string", "description": "The search algorithm specified for the Study.", "enum": [ "ALGORITHM_UNSPECIFIED", "GRID_SEARCH", "RANDOM_SEARCH" ] } }, "description": "Represents specification of a Study." }, "GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfig": { "properties": { "desiredMinSafeTrialsFraction": { "type": "number", "description": "Desired minimum fraction of safe trials (over total number of trials) that should be targeted by the algorithm at any time during the study (best effort). This should be between 0.0 and 1.0 and a value of 0.0 means that there is no minimum and an algorithm proceeds without targeting any specific fraction. A value of 1.0 means that the algorithm attempts to only Suggest safe Trials.", "format": "double" }, "safetyThreshold": { "description": "Safety threshold (boundary value between safe and unsafe). NOTE that if you leave SafetyMetricConfig unset, a default value of 0 will be used.", "format": "double", "type": "number" } }, "id": "GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfig", "description": "Used in safe optimization to specify threshold levels and risk tolerance.", "type": "object" }, "GoogleCloudAiplatformV1SlackSource": { "description": "The Slack source for the ImportRagFilesRequest.", "properties": { "channels": { "type": "array", "description": "Required. The Slack channels.", "items": { "$ref": "GoogleCloudAiplatformV1SlackSourceSlackChannels" } } }, "id": "GoogleCloudAiplatformV1SlackSource", "type": "object" }, "CloudAiLargeModelsVisionGenerateVideoRequestImage": { "description": "The image bytes or Cloud Storage URI to make the prediction on.", "type": "object", "properties": { "blobId": { "description": "Blob ID of the image. This is used for storing the large images in the request.", "type": "string" }, "bytesBase64Encoded": { "type": "string", "description": "Base64 encoded bytes string representing the image." }, "gcsUri": { "type": "string" }, "mimeType": { "type": "string", "description": "The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/png" } }, "id": "CloudAiLargeModelsVisionGenerateVideoRequestImage" }, "GoogleCloudAiplatformV1QuestionAnsweringQualityResult": { "type": "object", "description": "Spec for question answering quality result.", "id": "GoogleCloudAiplatformV1QuestionAnsweringQualityResult", "properties": { "explanation": { "type": "string", "readOnly": true, "description": "Output only. Explanation for question answering quality score." }, "score": { "type": "number", "format": "float", "description": "Output only. Question Answering Quality score.", "readOnly": true }, "confidence": { "readOnly": true, "format": "float", "description": "Output only. Confidence for question answering quality score.", "type": "number" } } }, "GoogleCloudAiplatformV1SchemaPredictInstanceVideoActionRecognitionPredictionInstance": { "id": "GoogleCloudAiplatformV1SchemaPredictInstanceVideoActionRecognitionPredictionInstance", "type": "object", "properties": { "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": { "type": "string", "description": "The Google Cloud Storage location of the video on which to perform the prediction." }, "mimeType": { "type": "string", "description": "The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime" }, "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" } }, "description": "Prediction input format for Video Action Recognition." }, "GoogleCloudAiplatformV1RagCorpus": { "properties": { "satisfiesPzs": { "type": "boolean", "description": "Output only. Reserved for future use.", "readOnly": true }, "description": { "type": "string", "description": "Optional. The description of the RagCorpus." }, "name": { "description": "Output only. The resource name of the RagCorpus.", "readOnly": true, "type": "string" }, "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.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "createTime": { "type": "string", "description": "Output only. Timestamp when this RagCorpus was created.", "format": "google-datetime", "readOnly": true }, "satisfiesPzi": { "readOnly": true, "description": "Output only. Reserved for future use.", "type": "boolean" }, "vertexAiSearchConfig": { "description": "Optional. Immutable. The config for the Vertex AI Search.", "$ref": "GoogleCloudAiplatformV1VertexAiSearchConfig" }, "corpusStatus": { "$ref": "GoogleCloudAiplatformV1CorpusStatus", "readOnly": true, "description": "Output only. RagCorpus state." }, "displayName": { "description": "Required. The display name of the RagCorpus. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "vectorDbConfig": { "description": "Optional. Immutable. The config for the Vector DBs.", "$ref": "GoogleCloudAiplatformV1RagVectorDbConfig" }, "updateTime": { "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when this RagCorpus was last updated.", "readOnly": true } }, "description": "A RagCorpus is a RagFile container and a project can have multiple RagCorpora.", "id": "GoogleCloudAiplatformV1RagCorpus", "type": "object" }, "GoogleCloudAiplatformV1ImportDataRequest": { "id": "GoogleCloudAiplatformV1ImportDataRequest", "type": "object", "description": "Request message for DatasetService.ImportData.", "properties": { "importConfigs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ImportDataConfig" }, "description": "Required. The desired input locations. The contents of all input locations will be imported in one batch." } } }, "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchResults": { "description": "Results for TrajectoryAnyOrderMatch metric.", "type": "object", "id": "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchResults", "properties": { "trajectoryAnyOrderMatchMetricValues": { "type": "array", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchMetricValue" }, "description": "Output only. TrajectoryAnyOrderMatch metric values." } } }, "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsResponse": { "properties": {}, "id": "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsResponse", "type": "object", "description": "Response message for MetadataService.AddContextArtifactsAndExecutions." }, "GoogleCloudAiplatformV1ExplanationSpec": { "id": "GoogleCloudAiplatformV1ExplanationSpec", "description": "Specification of Model explanation.", "type": "object", "properties": { "parameters": { "$ref": "GoogleCloudAiplatformV1ExplanationParameters", "description": "Required. Parameters that configure explaining of the Model's predictions." }, "metadata": { "description": "Optional. Metadata describing the Model's input and output for explanation.", "$ref": "GoogleCloudAiplatformV1ExplanationMetadata" } } }, "GoogleCloudAiplatformV1StudySpecMetricSpec": { "properties": { "goal": { "description": "Required. The optimization goal of the metric.", "enum": [ "GOAL_TYPE_UNSPECIFIED", "MAXIMIZE", "MINIMIZE" ], "enumDescriptions": [ "Goal Type will default to maximize.", "Maximize the goal metric.", "Minimize the goal metric." ], "type": "string" }, "safetyConfig": { "description": "Used for safe search. In the case, the metric will be a safety metric. You must provide a separate metric for objective metric.", "$ref": "GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfig" }, "metricId": { "description": "Required. The ID of the metric. Must not contain whitespaces and must be unique amongst all MetricSpecs.", "type": "string" } }, "type": "object", "description": "Represents a metric to optimize.", "id": "GoogleCloudAiplatformV1StudySpecMetricSpec" }, "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySource": { "description": "A Feature Registry source for features that need to be synced to Online Store.", "properties": { "projectNumber": { "description": "Optional. The project number of the parent project of the Feature Groups.", "format": "int64", "type": "string" }, "featureGroups": { "items": { "$ref": "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroup" }, "description": "Required. List of features that need to be synced to Online Store.", "type": "array" } }, "id": "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySource", "type": "object" }, "GoogleCloudAiplatformV1BatchCreateTensorboardRunsResponse": { "description": "Response message for TensorboardService.BatchCreateTensorboardRuns.", "properties": { "tensorboardRuns": { "items": { "$ref": "GoogleCloudAiplatformV1TensorboardRun" }, "description": "The created TensorboardRuns.", "type": "array" } }, "id": "GoogleCloudAiplatformV1BatchCreateTensorboardRunsResponse", "type": "object" }, "GoogleCloudAiplatformV1MetadataStore": { "description": "Instance of a metadata store. Contains a set of metadata that can be queried.", "type": "object", "properties": { "dataplexConfig": { "description": "Optional. Dataplex integration settings.", "$ref": "GoogleCloudAiplatformV1MetadataStoreDataplexConfig" }, "createTime": { "description": "Output only. Timestamp when this MetadataStore was created.", "readOnly": true, "format": "google-datetime", "type": "string" }, "state": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1MetadataStoreMetadataStoreState", "description": "Output only. State information of the MetadataStore." }, "name": { "type": "string", "description": "Output only. The resource name of the MetadataStore instance.", "readOnly": true }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this MetadataStore was last updated.", "format": "google-datetime" }, "description": { "description": "Description of the MetadataStore.", "type": "string" }, "encryptionSpec": { "description": "Customer-managed encryption key spec for a Metadata Store. If set, this Metadata Store and all sub-resources of this Metadata Store are secured using this key.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" } }, "id": "GoogleCloudAiplatformV1MetadataStore" }, "GoogleCloudAiplatformV1ReadIndexDatapointsRequest": { "id": "GoogleCloudAiplatformV1ReadIndexDatapointsRequest", "description": "The request message for MatchService.ReadIndexDatapoints.", "type": "object", "properties": { "ids": { "items": { "type": "string" }, "type": "array", "description": "IDs of the datapoints to be searched for." }, "deployedIndexId": { "description": "The ID of the DeployedIndex that will serve the request.", "type": "string" } } }, "GoogleCloudAiplatformV1Checkpoint": { "type": "object", "properties": { "checkpointId": { "description": "The ID of the checkpoint.", "type": "string" }, "epoch": { "description": "The epoch of the checkpoint.", "type": "string", "format": "int64" }, "step": { "description": "The step of the checkpoint.", "format": "int64", "type": "string" } }, "description": "Describes the machine learning model version checkpoint.", "id": "GoogleCloudAiplatformV1Checkpoint" }, "GoogleCloudAiplatformV1DirectRawPredictRequest": { "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.", "type": "string", "format": "byte" } }, "id": "GoogleCloudAiplatformV1DirectRawPredictRequest", "type": "object", "description": "Request message for PredictionService.DirectRawPredict." }, "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigOutputConfig": { "description": "The output config for the evaluation run.", "properties": { "gcsDestination": { "description": "Cloud Storage destination for evaluation output.", "$ref": "GoogleCloudAiplatformV1GcsDestination" }, "bigqueryDestination": { "description": "BigQuery destination for evaluation output.", "$ref": "GoogleCloudAiplatformV1BigQueryDestination" } }, "type": "object", "id": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigOutputConfig" }, "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueCondition": { "id": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueCondition", "description": "Represents the spec to match integer values from parent parameter.", "type": "object", "properties": { "values": { "type": "array", "description": "Required. Matches values of the parent parameter of 'INTEGER' type. All values must lie in `integer_value_spec` of parent parameter.", "items": { "type": "string", "format": "int64" } } } }, "GoogleCloudAiplatformV1DataItemView": { "id": "GoogleCloudAiplatformV1DataItemView", "type": "object", "description": "A container for a single DataItem and Annotations on it.", "properties": { "dataItem": { "description": "The DataItem.", "$ref": "GoogleCloudAiplatformV1DataItem" }, "annotations": { "items": { "$ref": "GoogleCloudAiplatformV1Annotation" }, "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.", "type": "array" }, "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" } } }, "GoogleCloudAiplatformV1EvaluationRunInferenceConfig": { "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": { "generationConfig": { "description": "Optional. Generation config.", "$ref": "GoogleCloudAiplatformV1GenerationConfig" }, "agentRunConfig": { "$ref": "GoogleCloudAiplatformV1EvaluationRunInferenceConfigAgentRunConfig", "description": "Optional. Agent run config." }, "agents": { "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.", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1AgentConfig" }, "type": "object" }, "parallelism": { "description": "Optional. The parallelism of the evaluation run for the inference step. If not specified, the default parallelism will be used.", "type": "integer", "format": "int32" }, "promptTemplate": { "$ref": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigPromptTemplate", "description": "Optional. The prompt template used for inference. The values for variables in the prompt template are defined in EvaluationItem.EvaluationPrompt.PromptTemplateData.values. If not specified, the prompt template in the EvaluationConfig will be used." }, "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": "GoogleCloudAiplatformV1EvaluationRunInferenceConfig", "type": "object" }, "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec": { "description": "Represent spec for search trials.", "type": "object", "id": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec", "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" }, "maxTrialCount": { "description": "Required. The maximum number of Neural Architecture Search (NAS) trials to run.", "type": "integer", "format": "int32" }, "maxParallelTrialCount": { "format": "int32", "description": "Required. The maximum number of trials to run in parallel.", "type": "integer" }, "searchTrialJobSpec": { "description": "Required. The spec of a search trial job. The same spec applies to all search trials.", "$ref": "GoogleCloudAiplatformV1CustomJobSpec" } } }, "GoogleCloudAiplatformV1TranslationConfig": { "properties": { "targetLanguageCode": { "description": "Required. The target language for translation. Supported values are BCP-47 language codes (e.g. \"en\", \"es\", \"fr\").", "type": "string" }, "echoTargetLanguage": { "description": "Optional. If `true`, the model will generate audio when the target language is spoken, essentially it will parrot the input. If `false`, we will not produce audio for the target language.", "type": "boolean" } }, "type": "object", "description": "Config for translation features.", "id": "GoogleCloudAiplatformV1TranslationConfig" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation": { "properties": { "columnName": { "type": "string" } }, "type": "object", "description": "Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index.", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation" }, "GenaiVertexV1FunctionResultStep": { "description": "Result of a function tool call.", "id": "GenaiVertexV1FunctionResultStep", "type": "object", "properties": { "isError": { "type": "boolean", "description": "Whether the tool call resulted in an error." }, "name": { "type": "string", "description": "The name of the tool that was called." }, "result": { "$ref": "GenaiVertexV1Value", "description": "Required. The result of the tool call." } } }, "GoogleCloudAiplatformV1CreateMetadataStoreOperationMetadata": { "description": "Details of operations that perform MetadataService.CreateMetadataStore.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Operation metadata for creating a MetadataStore." } }, "type": "object", "id": "GoogleCloudAiplatformV1CreateMetadataStoreOperationMetadata" }, "GoogleCloudAiplatformV1ExplainRequest": { "properties": { "parameters": { "description": "The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.", "type": "any" }, "deployedModelId": { "type": "string", "description": "If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split." }, "explanationSpecOverride": { "description": "If specified, overrides the explanation_spec of the DeployedModel. Can be used for explaining prediction results with different configurations, such as: - Explaining top-5 predictions results as opposed to top-1; - Increasing path count or step count of the attribution methods to reduce approximate errors; - Using different baselines for explaining the prediction results.", "$ref": "GoogleCloudAiplatformV1ExplanationSpecOverride" }, "instances": { "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.", "type": "array" } }, "id": "GoogleCloudAiplatformV1ExplainRequest", "type": "object", "description": "Request message for PredictionService.Explain." }, "GoogleCloudAiplatformV1CloudLoggingConfig": { "type": "object", "id": "GoogleCloudAiplatformV1CloudLoggingConfig", "properties": { "resourceType": { "type": "string", "description": "Optional. MonitoredResource type. Defaults to \"global\" if unspecified." }, "resourceLabels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. MonitoredResource labels to associate the log with. The backend will automatically inject project and location." }, "project": { "type": "string", "description": "Optional. Google Cloud project to write logs to. Defaults to the request project." }, "tracingContext": { "description": "Optional. Tracing context for the evaluation run.", "$ref": "GoogleCloudAiplatformV1CloudLoggingConfigTracingContext" } }, "description": "Specifies configuration for exporting evaluation results to Cloud Logging." }, "GoogleCloudAiplatformV1MigratableResourceAutomlDataset": { "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.", "id": "GoogleCloudAiplatformV1MigratableResourceAutomlDataset" }, "GoogleCloudAiplatformV1CustomCodeExecutionSpec": { "id": "GoogleCloudAiplatformV1CustomCodeExecutionSpec", "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." }, "GoogleCloudAiplatformV1IngestionDirectContentsSourceEvent": { "description": "A single event to ingest.", "type": "object", "properties": { "eventTime": { "type": "string", "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.", "format": "google-datetime" }, "content": { "description": "Required. The content of the event.", "$ref": "GoogleCloudAiplatformV1Content" }, "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" } }, "id": "GoogleCloudAiplatformV1IngestionDirectContentsSourceEvent" }, "GoogleCloudAiplatformV1LookupStudyRequest": { "description": "Request message for VizierService.LookupStudy.", "properties": { "displayName": { "type": "string", "description": "Required. The user-defined display name of the Study" } }, "id": "GoogleCloudAiplatformV1LookupStudyRequest", "type": "object" }, "GoogleCloudAiplatformV1MetricxResult": { "description": "Spec for MetricX result - calculates the MetricX score for the given instance using the version specified in the spec.", "id": "GoogleCloudAiplatformV1MetricxResult", "properties": { "score": { "format": "float", "readOnly": true, "description": "Output only. MetricX score. Range depends on version.", "type": "number" } }, "type": "object" }, "GoogleCloudAiplatformV1GroundednessInstance": { "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" } }, "id": "GoogleCloudAiplatformV1GroundednessInstance", "description": "Spec for groundedness instance.", "type": "object" }, "GoogleCloudAiplatformV1SemanticGovernancePolicy": { "description": "Represents a governance policy applied to a specific Agent and optionally a specific Tool within that Agent.", "id": "GoogleCloudAiplatformV1SemanticGovernancePolicy", "properties": { "description": { "type": "string", "description": "Optional. The description of the SemanticGovernancePolicy." }, "updateTime": { "description": "Output only. Timestamp when this SemanticGovernancePolicy was last updated.", "format": "google-datetime", "readOnly": true, "type": "string" }, "agent": { "type": "string", "description": "Required. The name of the agent in Agent Registry that is affected by this policy. Format: `projects/{project}/locations/{location}/agents/{agent}`" }, "etag": { "description": "Optional. Used to perform consistent read-modify-write transactions. If provided, the request will only succeed if the etag matches the current value. Otherwise, an ABORTED error will be returned.", "type": "string" }, "createTime": { "format": "google-datetime", "type": "string", "readOnly": true, "description": "Output only. Timestamp when this SemanticGovernancePolicy was created." }, "agentIdentity": { "type": "string", "description": "Output only. Represents the principal of the agent, used by the Policy Decision Point (PDP) for governance checks. For more information, see https://docs.cloud.google.com/agent-builder/agent-engine/agent-identity Format: `principal://TRUST_DOMAIN/NAMESPACE/AGENT_NAME` Example: `principal://agents.global.org-ORGANIZATION_ID.system.id.goog/resources/aiplatform/projects/PROJECT_NUMBER/locations/LOCATION/reasoningEngines/AGENT_ENGINE_ID`", "readOnly": true }, "agentResponseCustomization": { "$ref": "GoogleCloudAiplatformV1AgentResponseCustomization", "description": "Optional. Settings for customizing the agent's response to end users when this policy is evaluated, such as messages displayed when the policy denies a request." }, "displayName": { "description": "Optional. The user-defined name of the SemanticGovernancePolicy.", "type": "string" }, "naturalLanguageConstraint": { "description": "Required. The natural language constraint of the SemanticGovernancePolicy.", "type": "string" }, "mcpTools": { "description": "Optional. The McpTools that are affected by this policy.", "items": { "$ref": "GoogleCloudAiplatformV1SemanticGovernancePolicyMcpTool" }, "type": "array" }, "dryRun": { "type": "boolean", "description": "Optional. If true, this policy is evaluated and its result is reported, but the policy is not enforced: a violation does not block the agent's action. Use this to validate a policy against real traffic before turning enforcement on. Defaults to `false`, meaning the policy is enforced. This setting applies only to this policy. If the SemanticGovernancePolicyEngine for the project is itself in dry run, every policy behaves as dry run regardless of this field." }, "name": { "description": "Identifier. Resource name of the SemanticGovernancePolicy.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1Segment": { "type": "object", "properties": { "endIndex": { "type": "integer", "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.", "format": "int32", "readOnly": true }, "startIndex": { "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.", "type": "integer", "format": "int32", "readOnly": true }, "text": { "description": "Output only. The text of the segment.", "type": "string", "readOnly": true }, "partIndex": { "type": "integer", "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.", "readOnly": true, "format": "int32" } }, "description": "A segment of the content.", "id": "GoogleCloudAiplatformV1Segment" }, "GoogleCloudAiplatformV1RubricCritiqueResult": { "type": "object", "id": "GoogleCloudAiplatformV1RubricCritiqueResult", "description": "Rubric critique result.", "properties": { "verdict": { "type": "boolean", "readOnly": true, "description": "Output only. Verdict for the rubric - true if the rubric is met, false otherwise." }, "rubric": { "readOnly": true, "type": "string", "description": "Output only. Rubric to be evaluated." } } }, "GoogleCloudAiplatformV1TensorboardTimeSeriesMetadata": { "type": "object", "properties": { "maxBlobSequenceLength": { "format": "int64", "type": "string", "readOnly": true, "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." }, "maxWallTime": { "format": "google-datetime", "description": "Output only. Max wall clock timestamp of all data points within a TensorboardTimeSeries.", "type": "string", "readOnly": true }, "maxStep": { "description": "Output only. Max step index of all data points within a TensorboardTimeSeries.", "format": "int64", "type": "string", "readOnly": true } }, "description": "Describes metadata for a TensorboardTimeSeries.", "id": "GoogleCloudAiplatformV1TensorboardTimeSeriesMetadata" }, "GenaiVertexV1Field": { "properties": { "name": { "type": "string" }, "value": { "$ref": "GenaiVertexV1Value" } }, "id": "GenaiVertexV1Field", "description": "Represents a single field in a struct.", "type": "object" }, "GoogleCloudAiplatformV1FeatureGroupBigQuery": { "id": "GoogleCloudAiplatformV1FeatureGroupBigQuery", "properties": { "bigQuerySource": { "description": "Required. Immutable. The BigQuery source URI that points to either a BigQuery Table or View.", "$ref": "GoogleCloudAiplatformV1BigQuerySource" }, "staticDataSource": { "description": "Optional. Set if the data source is not a time-series.", "type": "boolean" }, "dense": { "type": "boolean", "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." }, "entityIdColumns": { "items": { "type": "string" }, "type": "array", "description": "Optional. Columns to construct entity_id / row keys. If not provided defaults to `entity_id`." }, "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.", "$ref": "GoogleCloudAiplatformV1FeatureGroupBigQueryTimeSeries" } }, "type": "object", "description": "Input source type for BigQuery Tables and Views." }, "GoogleCloudAiplatformV1ToolCallValidMetricValue": { "id": "GoogleCloudAiplatformV1ToolCallValidMetricValue", "description": "Tool call valid metric value for an instance.", "properties": { "score": { "readOnly": true, "description": "Output only. Tool call valid score.", "type": "number", "format": "float" } }, "type": "object" }, "GoogleCloudAiplatformV1ContainerSpec": { "type": "object", "description": "The spec of a Container.", "id": "GoogleCloudAiplatformV1ContainerSpec", "properties": { "imageUri": { "description": "Required. The URI of a container image in the Container Registry that is to be run on each worker replica.", "type": "string" }, "args": { "type": "array", "items": { "type": "string" }, "description": "The arguments to be passed when starting the container." }, "command": { "description": "The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.", "type": "array", "items": { "type": "string" } }, "env": { "description": "Environment variables to be passed to the container. Maximum limit is 100.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1EnvVar" } } } }, "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition": { "description": "Represents the spec to match categorical values from parent parameter.", "id": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition", "type": "object", "properties": { "values": { "items": { "type": "string" }, "type": "array", "description": "Required. Matches values of the parent parameter of 'CATEGORICAL' type. All values must exist in `categorical_value_spec` of parent parameter." } } }, "GoogleCloudAiplatformV1ExplanationMetadata": { "id": "GoogleCloudAiplatformV1ExplanationMetadata", "type": "object", "description": "Metadata describing the Model's input and output for explanation.", "properties": { "latentSpaceSource": { "type": "string", "description": "Name of the source to generate embeddings for example based explanations." }, "inputs": { "type": "object", "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.", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadata" } }, "outputs": { "additionalProperties": { "$ref": "GoogleCloudAiplatformV1ExplanationMetadataOutputMetadata" }, "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" }, "featureAttributionsSchemaUri": { "type": "string", "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." } } }, "GoogleTypeDate": { "properties": { "day": { "type": "integer", "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." }, "year": { "format": "int32", "description": "Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.", "type": "integer" }, "month": { "description": "Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.", "type": "integer", "format": "int32" } }, "type": "object", "id": "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" }, "GoogleCloudAiplatformV1SchemaVideoActionRecognitionAnnotation": { "description": "Annotation details specific to video action recognition.", "type": "object", "id": "GoogleCloudAiplatformV1SchemaVideoActionRecognitionAnnotation", "properties": { "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "annotationSpecId": { "type": "string", "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." }, "timeSegment": { "$ref": "GoogleCloudAiplatformV1SchemaTimeSegment", "description": "This Annotation applies to the time period represented by the TimeSegment. If it's not set, the Annotation applies to the whole video." } } }, "GoogleCloudAiplatformV1EvaluationInstanceInteractionsDataSource": { "type": "object", "properties": { "geminiAgentConfig": { "$ref": "GoogleCloudAiplatformV1GeminiAgentConfig", "description": "Optional. Gemini Agent (Vertex AI Agent resource)." }, "interaction": { "description": "Required. The interaction to evaluate. Format: `projects/{project}/locations/{location}/interactions/{interaction}`.", "type": "string" } }, "id": "GoogleCloudAiplatformV1EvaluationInstanceInteractionsDataSource", "description": "Source for populating `AgentData` from an Interactions API interaction." }, "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectEntity": { "id": "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectEntity", "properties": { "offlineStorageDeletedEntityRowCount": { "type": "string", "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.", "format": "int64" }, "onlineStorageDeletedEntityCount": { "type": "string", "format": "int64", "description": "The count of deleted entities in the online storage. Each entity ID corresponds to one entity." } }, "description": "Response message if the request uses the SelectEntity option.", "type": "object" }, "GoogleCloudAiplatformV1TrialContext": { "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": { "$ref": "GoogleCloudAiplatformV1TrialParameter" } } }, "id": "GoogleCloudAiplatformV1TrialContext" }, "GoogleCloudAiplatformV1EvaluationPromptUserScenario": { "type": "object", "id": "GoogleCloudAiplatformV1EvaluationPromptUserScenario", "description": "User scenario to help simulate multi-turn agent running results.", "properties": { "startingPrompt": { "type": "string", "description": "Required. The prompt that starts the conversation between the simulated user and the agent under test." }, "conversationPlan": { "type": "string", "description": "Required. The plan for the conversation, used to drive the multi-turn agent run and generate the simulated agent evaluation dataset." } } }, "GoogleCloudAiplatformV1CustomOutput": { "description": "Spec for custom output.", "properties": { "rawOutputs": { "description": "Output only. List of raw output strings.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1RawOutput" } }, "type": "object", "id": "GoogleCloudAiplatformV1CustomOutput" }, "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfig": { "type": "object", "description": "Specification for a Memory Bank.", "id": "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfig", "properties": { "disableMemoryRevisions": { "description": "If true, no memory revisions will be created for any requests to the Memory Bank.", "type": "boolean" }, "similaritySearchConfig": { "$ref": "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigSimilaritySearchConfig", "description": "Optional. Configuration for how to perform similarity search on memories. If not set, the Memory Bank will use the default embedding model `text-embedding-005`." }, "customizationConfigs": { "items": { "$ref": "GoogleCloudAiplatformV1MemoryBankCustomizationConfig" }, "type": "array", "description": "Optional. Configuration for how to customize Memory Bank behavior for a particular scope." }, "generationConfig": { "description": "Optional. Configuration for how to generate memories for the Memory Bank.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigGenerationConfig" }, "ttlConfig": { "description": "Optional. Configuration for automatic TTL (\"time-to-live\") of the memories in the Memory Bank. If not set, TTL will not be applied automatically. The TTL can be explicitly set by modifying the `expire_time` of each Memory resource.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigTtlConfig" } } }, "GoogleCloudAiplatformV1IndexPrivateEndpoints": { "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.", "properties": { "matchGrpcAddress": { "description": "Output only. The ip address used to send match gRPC requests.", "type": "string", "readOnly": true }, "serviceAttachment": { "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled.", "readOnly": true, "type": "string" }, "pscAutomatedEndpoints": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1PscAutomatedEndpoints" }, "readOnly": true, "description": "Output only. PscAutomatedEndpoints is populated if private service connect is enabled if PscAutomatedConfig is set." } }, "type": "object", "id": "GoogleCloudAiplatformV1IndexPrivateEndpoints" }, "GoogleCloudAiplatformV1MutateDeployedModelRequest": { "type": "object", "properties": { "deployedModel": { "description": "Required. The DeployedModel to be mutated within the Endpoint. Only the following fields can be mutated: * `min_replica_count` in either DedicatedResources or AutomaticResources * `max_replica_count` in either DedicatedResources or AutomaticResources * `required_replica_count` in DedicatedResources * autoscaling_metric_specs * `disable_container_logging` (v1 only) * `enable_container_logging` (v1beta1 only) * `scale_to_zero_spec` in DedicatedResources (v1beta1 only) * `initial_replica_count` in DedicatedResources (v1beta1 only)", "$ref": "GoogleCloudAiplatformV1DeployedModel" }, "updateMask": { "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask.", "format": "google-fieldmask", "type": "string" } }, "description": "Request message for EndpointService.MutateDeployedModel.", "id": "GoogleCloudAiplatformV1MutateDeployedModelRequest" }, "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis": { "id": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis", "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.", "type": "object", "properties": { "state": { "description": "Whether to enable / disable / inherite default hebavior for import features analysis.", "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." ], "type": "string", "enum": [ "STATE_UNSPECIFIED", "DEFAULT", "ENABLED", "DISABLED" ] }, "anomalyDetectionBaseline": { "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." ], "type": "string", "enum": [ "BASELINE_UNSPECIFIED", "LATEST_STATS", "MOST_RECENT_SNAPSHOT_STATS", "PREVIOUS_IMPORT_FEATURES_STATS" ], "description": "The baseline used to do anomaly detection for the statistics generated by import features analysis." } } }, "GoogleCloudAiplatformV1CopyModelRequest": { "description": "Request message for ModelService.CopyModel.", "properties": { "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" }, "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" }, "modelId": { "type": "string", "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." }, "customServiceAccount": { "description": "Optional. The user-provided custom service account to use to do the copy model. 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 destination project where the model is copied to, i.e., the project specified in the `parent` field of this request and have the Vertex AI Service Agent role in the source project. Requires the user copying the Model to have the `iam.serviceAccounts.actAs` permission on this service account.", "type": "string" }, "encryptionSpec": { "description": "Customer-managed encryption key options. If this is set, then the Model copy will be encrypted with the provided encryption key.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" } }, "type": "object", "id": "GoogleCloudAiplatformV1CopyModelRequest" }, "GoogleCloudAiplatformV1FluencyInstance": { "type": "object", "description": "Spec for fluency instance.", "id": "GoogleCloudAiplatformV1FluencyInstance", "properties": { "prediction": { "type": "string", "description": "Required. Output of the evaluated model." } } }, "GoogleCloudAiplatformV1CorpusStatus": { "properties": { "errorStatus": { "description": "Output only. Only when the `state` field is ERROR.", "type": "string", "readOnly": true }, "state": { "enum": [ "UNKNOWN", "INITIALIZED", "ACTIVE", "ERROR" ], "description": "Output only. RagCorpus life state.", "type": "string", "readOnly": true, "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." ] } }, "id": "GoogleCloudAiplatformV1CorpusStatus", "type": "object", "description": "RagCorpus status." }, "GoogleCloudAiplatformV1ModelExplanation": { "properties": { "meanAttributions": { "readOnly": true, "type": "array", "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.", "items": { "$ref": "GoogleCloudAiplatformV1Attribution" } } }, "id": "GoogleCloudAiplatformV1ModelExplanation", "description": "Aggregated explanation metrics for a Model over a set of instances.", "type": "object" }, "GoogleCloudAiplatformV1CachedContentUsageMetadata": { "type": "object", "description": "Metadata on the usage of the cached content.", "properties": { "videoDurationSeconds": { "type": "integer", "description": "Duration of video in seconds.", "format": "int32" }, "audioDurationSeconds": { "description": "Duration of audio in seconds.", "format": "int32", "type": "integer" }, "totalTokenCount": { "description": "Total number of tokens that the cached content consumes.", "type": "integer", "format": "int32" }, "imageCount": { "format": "int32", "description": "Number of images.", "type": "integer" }, "textCount": { "format": "int32", "type": "integer", "description": "Number of text characters." } }, "id": "GoogleCloudAiplatformV1CachedContentUsageMetadata" }, "GoogleCloudAiplatformV1ListOnlineEvaluatorsResponse": { "description": "Response message for ListOnlineEvaluators.", "properties": { "onlineEvaluators": { "description": "A list of OnlineEvaluators matching the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluator" } }, "nextPageToken": { "description": "A token to retrieve the next page. Absence of this field indicates there are no subsequent pages.", "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1ListOnlineEvaluatorsResponse" }, "GoogleCloudAiplatformV1MigratableResourceAutomlModel": { "id": "GoogleCloudAiplatformV1MigratableResourceAutomlModel", "description": "Represents one Model in automl.googleapis.com.", "properties": { "model": { "type": "string", "description": "Full resource name of automl Model. Format: `projects/{project}/locations/{location}/models/{model}`." }, "modelDisplayName": { "description": "The Model's display name in automl.googleapis.com.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1AddTrialMeasurementRequest": { "type": "object", "description": "Request message for VizierService.AddTrialMeasurement.", "properties": { "measurement": { "description": "Required. The measurement to be added to a Trial.", "$ref": "GoogleCloudAiplatformV1Measurement" } }, "id": "GoogleCloudAiplatformV1AddTrialMeasurementRequest" }, "GoogleCloudAiplatformV1ExportDataResponse": { "type": "object", "id": "GoogleCloudAiplatformV1ExportDataResponse", "properties": { "dataStats": { "description": "Only present for custom code training export use case. Records data stats, i.e., train/validation/test item/annotation counts calculated during the export operation.", "$ref": "GoogleCloudAiplatformV1ModelDataStats" }, "exportedFiles": { "type": "array", "description": "All of the files that are exported in this export operation. For custom code training export, only three (training, validation and test) Cloud Storage paths in wildcard format are populated (for example, gs://.../training-*).", "items": { "type": "string" } } }, "description": "Response message for DatasetService.ExportData." }, "GoogleCloudAiplatformV1ListDatasetVersionsResponse": { "id": "GoogleCloudAiplatformV1ListDatasetVersionsResponse", "properties": { "nextPageToken": { "type": "string", "description": "The standard List next-page token." }, "datasetVersions": { "items": { "$ref": "GoogleCloudAiplatformV1DatasetVersion" }, "description": "A list of DatasetVersions that matches the specified filter in the request.", "type": "array" } }, "description": "Response message for DatasetService.ListDatasetVersions.", "type": "object" }, "GoogleCloudAiplatformV1GenerateLossClustersRequest": { "id": "GoogleCloudAiplatformV1GenerateLossClustersRequest", "type": "object", "properties": { "configs": { "type": "array", "description": "Required. Configuration for the analysis algorithm. Analysis for multiple metrics and multiple candidates could be specified.", "items": { "$ref": "GoogleCloudAiplatformV1LossAnalysisConfig" } }, "inlineResults": { "description": "Inline evaluation results. Useful for ephemeral analysis in notebooks/SDKs where data isn't persisted.", "$ref": "GoogleCloudAiplatformV1GenerateLossClustersRequestEvaluationResultList" }, "evaluationSet": { "description": "Reference to a persisted EvaluationSet. The service will read items from this set.", "type": "string" } }, "description": "Request message for EvaluationAnalyticsService.GenerateLossClusters." }, "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigPromptTemplate": { "description": "Prompt template used for inference.", "type": "object", "properties": { "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" }, "gcsUri": { "description": "Prompt template stored in Cloud Storage. Format: \"gs://my-bucket/file-name.txt\".", "type": "string" } }, "id": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigPromptTemplate" }, "GoogleCloudAiplatformV1SessionEvent": { "properties": { "name": { "type": "string", "description": "Identifier. The resource name of the event. Format:`projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}/events/{event}`." }, "actions": { "$ref": "GoogleCloudAiplatformV1EventActions", "description": "Optional. Actions executed by the agent." }, "timestamp": { "type": "string", "description": "Required. Timestamp when the event was created on client side.", "format": "google-datetime" }, "errorCode": { "type": "string", "description": "Optional. Error code if the response is an error. Code varies by model." }, "content": { "description": "Optional. Content of the event provided by the author.", "$ref": "GoogleCloudAiplatformV1Content" }, "invocationId": { "description": "Required. The invocation id of the event, multiple events can have the same invocation id.", "type": "string" }, "rawEvent": { "description": "Optional. Weakly typed raw event data in proto struct format.", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "type": "object" }, "errorMessage": { "type": "string", "description": "Optional. Error message if the response is an error." }, "author": { "description": "Required. The name of the agent that sent the event, or user.", "type": "string" }, "eventMetadata": { "$ref": "GoogleCloudAiplatformV1EventMetadata", "description": "Optional. Metadata relating to this event." } }, "type": "object", "description": "An event represents a message from either the user or agent.", "id": "GoogleCloudAiplatformV1SessionEvent" }, "GoogleCloudAiplatformV1MemoryBankCustomizationConfigConsolidationConfig": { "description": "Represents configuration for customizing how memories are consolidated.", "id": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigConsolidationConfig", "properties": { "revisionsPerCandidateCount": { "format": "int32", "type": "integer", "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." } }, "type": "object" }, "GoogleCloudAiplatformV1DeployRequestEndpointConfig": { "type": "object", "properties": { "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": { "type": "string", "description": "Optional. The user-specified display name of the endpoint. If not set, a default name will be used." }, "dedicatedEndpointDisabled": { "type": "boolean", "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." }, "privateServiceConnectConfig": { "$ref": "GoogleCloudAiplatformV1PrivateServiceConnectConfig", "description": "Optional. Configuration for private service connect. If set, the endpoint will be exposed through private service connect." }, "dedicatedEndpointEnabled": { "deprecated": true, "type": "boolean", "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." }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "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." } }, "id": "GoogleCloudAiplatformV1DeployRequestEndpointConfig", "description": "The endpoint config to use for the deployment." }, "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec": { "description": "The spec of multi-trial Neural Architecture Search (NAS).", "type": "object", "id": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec", "properties": { "trainTrialSpec": { "$ref": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec", "description": "Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched." }, "searchTrialSpec": { "description": "Required. Spec for search trials.", "$ref": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec" }, "metric": { "description": "Metric specs for the NAS job. Validation for this field is done at `multi_trial_algorithm_spec` field.", "$ref": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec" }, "multiTrialAlgorithm": { "enumDescriptions": [ "Defaults to `REINFORCEMENT_LEARNING`.", "The Reinforcement Learning Algorithm for Multi-trial Neural Architecture Search (NAS).", "The Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS)." ], "enum": [ "MULTI_TRIAL_ALGORITHM_UNSPECIFIED", "REINFORCEMENT_LEARNING", "GRID_SEARCH" ], "type": "string", "description": "The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`." } } }, "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchMetricValue": { "description": "TrajectoryAnyOrderMatch metric value for an instance.", "properties": { "score": { "format": "float", "readOnly": true, "type": "number", "description": "Output only. TrajectoryAnyOrderMatch score." } }, "id": "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchMetricValue", "type": "object" }, "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityViewData": { "id": "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityViewData", "properties": { "values": { "description": "Feature values list if values, successive in time, are requested. If the requested number of values is greater than the number of existing Feature values, nonexistent values are omitted instead of being returned as empty.", "$ref": "GoogleCloudAiplatformV1FeatureValueList" }, "value": { "$ref": "GoogleCloudAiplatformV1FeatureValue", "description": "Feature value if a single value is requested." } }, "type": "object", "description": "Container to hold value(s), successive in time, for one Feature from the request." }, "GoogleCloudAiplatformV1Schedule": { "description": "An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.", "type": "object", "properties": { "lastPauseTime": { "description": "Output only. Timestamp when this Schedule was last paused. Unset if never paused.", "readOnly": true, "format": "google-datetime", "type": "string" }, "createTime": { "type": "string", "format": "google-datetime", "readOnly": true, "description": "Output only. Timestamp when this Schedule was created." }, "allowQueueing": { "description": "Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.", "type": "boolean" }, "startedRunCount": { "description": "Output only. The number of runs started by this schedule.", "format": "int64", "type": "string", "readOnly": true }, "createNotebookExecutionJobRequest": { "$ref": "GoogleCloudAiplatformV1CreateNotebookExecutionJobRequest", "description": "Request for NotebookService.CreateNotebookExecutionJob." }, "displayName": { "type": "string", "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." }, "state": { "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." ], "description": "Output only. The state of this Schedule.", "readOnly": true, "type": "string", "enum": [ "STATE_UNSPECIFIED", "ACTIVE", "PAUSED", "COMPLETED" ] }, "endTime": { "format": "google-datetime", "type": "string", "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." }, "lastResumeTime": { "description": "Output only. Timestamp when this Schedule was last resumed. Unset if never resumed from pause.", "type": "string", "format": "google-datetime", "readOnly": true }, "maxConcurrentActiveRunCount": { "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", "format": "int64" }, "createPipelineJobRequest": { "description": "Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).", "$ref": "GoogleCloudAiplatformV1CreatePipelineJobRequest" }, "lastScheduledRunResponse": { "$ref": "GoogleCloudAiplatformV1ScheduleRunResponse", "readOnly": true, "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." }, "nextRunTime": { "type": "string", "readOnly": true, "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." }, "startTime": { "description": "Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.", "format": "google-datetime", "type": "string" }, "catchUp": { "type": "boolean", "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.", "readOnly": true }, "maxRunCount": { "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.", "type": "string" }, "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" }, "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" }, "name": { "description": "Immutable. The resource name of the Schedule.", "type": "string" }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this Schedule was updated.", "type": "string", "readOnly": true } }, "id": "GoogleCloudAiplatformV1Schedule" }, "GoogleCloudAiplatformV1SchemaPredictParamsImageSegmentationPredictionParams": { "type": "object", "description": "Prediction model parameters for Image Segmentation.", "id": "GoogleCloudAiplatformV1SchemaPredictParamsImageSegmentationPredictionParams", "properties": { "confidenceThreshold": { "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.", "format": "float", "type": "number" } } }, "GoogleCloudAiplatformV1SchemaPredictPredictionImageObjectDetectionPredictionResult": { "id": "GoogleCloudAiplatformV1SchemaPredictPredictionImageObjectDetectionPredictionResult", "properties": { "confidences": { "items": { "type": "number", "format": "float" }, "type": "array", "description": "The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids." }, "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": { "type": "array", "description": "The resource IDs of the AnnotationSpecs that had been identified, ordered by the confidence score descendingly.", "items": { "format": "int64", "type": "string" } } }, "type": "object", "description": "Prediction output format for Image Object Detection." }, "GoogleCloudAiplatformV1LogprobsResultTopCandidates": { "type": "object", "id": "GoogleCloudAiplatformV1LogprobsResultTopCandidates", "properties": { "candidates": { "items": { "$ref": "GoogleCloudAiplatformV1LogprobsResultCandidate" }, "description": "The list of candidate tokens, sorted by log probability in descending order.", "type": "array" } }, "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." }, "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataConversationTurn": { "description": "Represents a single turn/invocation in the conversation.", "id": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataConversationTurn", "type": "object", "properties": { "turnIndex": { "type": "integer", "format": "int32", "description": "Required. The 0-based index of the turn in the conversation sequence." }, "events": { "items": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataAgentEvent" }, "description": "Optional. The list of events that occurred during this turn.", "type": "array" }, "turnId": { "type": "string", "description": "Optional. A unique identifier for the turn. Useful for referencing specific turns across systems." } } }, "GoogleCloudAiplatformV1UndeployIndexRequest": { "properties": { "deployedIndexId": { "description": "Required. The ID of the DeployedIndex to be undeployed from the IndexEndpoint.", "type": "string" } }, "type": "object", "description": "Request message for IndexEndpointService.UndeployIndex.", "id": "GoogleCloudAiplatformV1UndeployIndexRequest" }, "GoogleCloudAiplatformV1CometResult": { "properties": { "score": { "format": "float", "type": "number", "readOnly": true, "description": "Output only. Comet score. Range depends on version." } }, "id": "GoogleCloudAiplatformV1CometResult", "description": "Spec for Comet result - calculates the comet score for the given instance using the version specified in the spec.", "type": "object" }, "GoogleCloudAiplatformV1GcsDestination": { "id": "GoogleCloudAiplatformV1GcsDestination", "type": "object", "properties": { "outputUriPrefix": { "type": "string", "description": "Required. Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist." } }, "description": "The Google Cloud Storage location where the output is to be written to." }, "GenaiVertexV1InteractionStreamingEvent": { "properties": { "interactionStatusUpdate": { "description": "The interaction status data, used for interaction.status_update events.", "$ref": "GenaiVertexV1InteractionStatusUpdate" }, "stepStart": { "$ref": "GenaiVertexV1StepStart", "description": "The step start data, used for step.start events. Step-based streaming event, used when steps are enabled." }, "stepDelta": { "$ref": "GenaiVertexV1StepDelta", "description": "The step delta data, used for step.delta events. Step-based streaming event, used when steps are enabled." }, "interactionCreatedEvent": { "$ref": "GenaiVertexV1InteractionCreatedSseEvent", "description": "The interaction data, used for interaction.created events. Used when steps are enabled." }, "interactionCompletedEvent": { "description": "The interaction data, used for interaction.completed events. Used when steps are enabled.", "$ref": "GenaiVertexV1InteractionCompletedSseEvent" }, "stepStop": { "description": "The step stop data, used for step.stop events. Step-based streaming event, used when steps are enabled.", "$ref": "GenaiVertexV1StepStop" }, "errorEvent": { "description": "The error event data, used for error events.", "$ref": "GenaiVertexV1ErrorEvent" }, "eventId": { "type": "string", "description": "The event_id token to be used to resume the interaction stream, from this event." } }, "type": "object", "id": "GenaiVertexV1InteractionStreamingEvent" }, "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig": { "properties": { "annotatedDataset": { "description": "Required. Full resource name of data labeling AnnotatedDataset. Format: `projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}`.", "type": "string" } }, "type": "object", "description": "Config for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery.", "id": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig" }, "GoogleCloudAiplatformV1PurgeArtifactsMetadata": { "id": "GoogleCloudAiplatformV1PurgeArtifactsMetadata", "description": "Details of operations that perform MetadataService.PurgeArtifacts.", "properties": { "genericMetadata": { "description": "Operation metadata for purging Artifacts.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "type": "object" }, "GoogleCloudAiplatformV1SummarizationVerbosityInstance": { "properties": { "context": { "description": "Required. Text to be summarized.", "type": "string" }, "prediction": { "type": "string", "description": "Required. Output of the evaluated model." }, "instruction": { "description": "Optional. Summarization prompt for LLM.", "type": "string" }, "reference": { "type": "string", "description": "Optional. Ground truth used to compare against the prediction." } }, "id": "GoogleCloudAiplatformV1SummarizationVerbosityInstance", "description": "Spec for summarization verbosity instance.", "type": "object" }, "GoogleCloudAiplatformV1MutateDeployedModelResponse": { "id": "GoogleCloudAiplatformV1MutateDeployedModelResponse", "properties": { "deployedModel": { "$ref": "GoogleCloudAiplatformV1DeployedModel", "description": "The DeployedModel that's being mutated." } }, "type": "object", "description": "Response message for EndpointService.MutateDeployedModel." }, "GoogleCloudAiplatformV1GenerationConfig": { "type": "object", "properties": { "maxOutputTokens": { "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", "type": "integer" }, "speechConfig": { "description": "Optional. The speech generation config.", "$ref": "GoogleCloudAiplatformV1SpeechConfig" }, "candidateCount": { "type": "integer", "format": "int32", "description": "Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one." }, "presencePenalty": { "type": "number", "format": "float", "description": "Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0]." }, "routingConfig": { "$ref": "GoogleCloudAiplatformV1GenerationConfigRoutingConfig", "description": "Optional. Routing configuration." }, "audioTimestamp": { "type": "boolean", "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." }, "imageConfig": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1ImageConfig", "description": "Optional. Config for image generation features. Deprecated: Use `response_format.image` instead." }, "frequencyPenalty": { "type": "number", "format": "float", "description": "Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0]." }, "responseMimeType": { "deprecated": true, "type": "string", "description": "Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead." }, "translationConfig": { "description": "Optional. Config for translation.", "$ref": "GoogleCloudAiplatformV1TranslationConfig" }, "audioTranscriptionConfig": { "$ref": "GoogleCloudAiplatformV1AudioTranscriptionConfig", "description": "Optional. Configuration for audio transcription (speech recognition)." }, "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" }, "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" }, "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" }, "logprobs": { "type": "integer", "format": "int32", "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." }, "temperature": { "type": "number", "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]." }, "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.", "items": { "type": "string" }, "type": "array" }, "responseModalities": { "type": "array", "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.", "items": { "type": "string", "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "AUDIO", "VIDEO" ], "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`. Deprecated: Use `response_format` instead.", "deprecated": true, "type": "any" }, "topK": { "format": "float", "type": "number", "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." }, "responseSchema": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1Schema", "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`. Deprecated: Use `response_format` instead." }, "mediaResolution": { "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.", "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)." ], "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "MEDIA_RESOLUTION_LOW", "MEDIA_RESOLUTION_MEDIUM", "MEDIA_RESOLUTION_HIGH" ], "type": "string" }, "responseFormat": { "type": "array", "description": "Optional. New response format field for the model to configure output formatting and delivery.", "items": { "$ref": "GoogleCloudAiplatformV1ResponseFormat" } }, "seed": { "format": "int32", "description": "Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the \"random\" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.", "type": "integer" }, "thinkingConfig": { "$ref": "GoogleCloudAiplatformV1GenerationConfigThinkingConfig", "description": "Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking." } }, "id": "GoogleCloudAiplatformV1GenerationConfig", "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." }, "GoogleCloudAiplatformV1GoogleMapsGroundingTypes": { "description": "Defines the types of Google Maps grounding that can be enabled and their configurations.", "type": "object", "id": "GoogleCloudAiplatformV1GoogleMapsGroundingTypes", "properties": { "places": { "$ref": "GoogleCloudAiplatformV1GoogleMapsPlaces", "description": "Optional. Enables grounding with Google Maps Places. This is the default grounding type when no `GroundingTypes` are specified." }, "routing": { "$ref": "GoogleCloudAiplatformV1GoogleMapsRouting", "description": "Optional. Enables grounding with Google Maps Routing APIs (ComputeRoutes and SearchAlongRoute)." } } }, "GoogleCloudAiplatformV1AddContextChildrenResponse": { "id": "GoogleCloudAiplatformV1AddContextChildrenResponse", "properties": {}, "type": "object", "description": "Response message for MetadataService.AddContextChildren." }, "GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifact": { "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" } }, "id": "GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifact", "type": "object", "description": "The type of an input artifact." }, "GoogleCloudAiplatformV1ToolNameMatchSpec": { "description": "Spec for tool name match metric.", "properties": {}, "type": "object", "id": "GoogleCloudAiplatformV1ToolNameMatchSpec" }, "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesResponse": { "id": "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesResponse", "type": "object", "description": "Response message for TensorboardService.BatchCreateTensorboardTimeSeries.", "properties": { "tensorboardTimeSeries": { "description": "The created TensorboardTimeSeries.", "items": { "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" }, "type": "array" } } }, "GoogleCloudAiplatformV1NotebookExecutionJobCustomEnvironmentSpecShieldedInstanceConfig": { "properties": { "enableIntegrityMonitoring": { "description": "Optional. Whether the VM instance has integrity monitoring enabled.", "type": "boolean" }, "enableSecureBoot": { "type": "boolean", "description": "Optional. Whether the VM instance has Secure Boot enabled. Disabled by default." }, "enableVtpm": { "description": "Optional. Whether the VM instance has vTPM enabled.", "type": "boolean" } }, "type": "object", "id": "GoogleCloudAiplatformV1NotebookExecutionJobCustomEnvironmentSpecShieldedInstanceConfig", "description": "A set of Shielded VM options for the execution VM. Mirrors `google.cloud.notebooks.v2.ShieldedInstanceConfig`. See https://cloud.google.com/compute/docs/instances/modifying-shielded-vm." }, "GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpec": { "properties": { "defaultValue": { "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.", "format": "int64", "type": "string" }, "maxValue": { "description": "Required. Inclusive maximum value of the parameter.", "type": "string", "format": "int64" }, "minValue": { "description": "Required. Inclusive minimum value of the parameter.", "format": "int64", "type": "string" } }, "type": "object", "description": "Value specification for a parameter in `INTEGER` type.", "id": "GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpec" }, "GoogleTypeLatLng": { "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.", "properties": { "longitude": { "format": "double", "description": "The longitude in degrees. It must be in the range [-180.0, +180.0].", "type": "number" }, "latitude": { "description": "The latitude in degrees. It must be in the range [-90.0, +90.0].", "format": "double", "type": "number" } }, "type": "object", "id": "GoogleTypeLatLng" }, "GoogleCloudAiplatformV1TunedModel": { "description": "The Model Registry Model and Online Prediction Endpoint associated with this TuningJob.", "properties": { "model": { "readOnly": true, "type": "string", "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}`" }, "endpoint": { "type": "string", "description": "Output only. A resource name of an Endpoint. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`.", "readOnly": true }, "checkpoints": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1TunedModelCheckpoint" }, "description": "Output only. The checkpoints associated with this TunedModel. This field is only populated for tuning jobs that enable intermediate checkpoints.", "readOnly": true } }, "type": "object", "id": "GoogleCloudAiplatformV1TunedModel" }, "CloudAiLargeModelsVisionImageRAIScores": { "properties": { "agileWatermarkDetectionScore": { "type": "number", "description": "Agile watermark score for image.", "format": "double" } }, "id": "CloudAiLargeModelsVisionImageRAIScores", "description": "RAI scores for generated image returned.", "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation", "properties": { "columnName": { "type": "string" } }, "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. * A boolean value that indicates whether the value is valid." }, "GoogleCloudAiplatformV1RagRetrievalConfigRankingRankService": { "description": "Config for Rank Service.", "properties": { "modelName": { "type": "string", "description": "Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`" } }, "type": "object", "id": "GoogleCloudAiplatformV1RagRetrievalConfigRankingRankService" }, "GoogleCloudAiplatformV1GenerationConfigThinkingConfig": { "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.", "type": "object", "id": "GoogleCloudAiplatformV1GenerationConfigThinkingConfig", "properties": { "includeThoughts": { "type": "boolean", "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." }, "thinkingBudget": { "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.", "type": "integer", "format": "int32" }, "thinkingLevel": { "enumDescriptions": [ "Unspecified thinking level.", "Low thinking level.", "Medium thinking level.", "High thinking level.", "MINIMAL thinking level." ], "enum": [ "THINKING_LEVEL_UNSPECIFIED", "LOW", "MEDIUM", "HIGH", "MINIMAL" ], "description": "Optional. The number of thoughts tokens that the model should generate.", "type": "string" } } }, "GenaiVertexV1InteractionUsageGroundingToolCount": { "type": "object", "properties": { "type": { "enumDescriptions": [ "Default value. This value is unused.", "Grounding with Google Web Search and Image Search, & Web Grounding for Enterprise.", "Grounding with Google Maps.", "Grounding with customer's data, for example, VertexAISearch." ], "description": "The grounding tool type associated with the count.", "enum": [ "TYPE_UNSPECIFIED", "GOOGLE_SEARCH", "GOOGLE_MAPS", "RETRIEVAL" ], "type": "string" }, "count": { "description": "The number of grounding tool counts.", "type": "integer", "format": "int32" } }, "id": "GenaiVertexV1InteractionUsageGroundingToolCount", "description": "The number of grounding tool counts." }, "GoogleCloudAiplatformV1ResumeModelDeploymentMonitoringJobRequest": { "description": "Request message for JobService.ResumeModelDeploymentMonitoringJob.", "id": "GoogleCloudAiplatformV1ResumeModelDeploymentMonitoringJobRequest", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1SandboxEnvironmentTemplateResourceRequirements": { "properties": { "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\")." }, "requests": { "additionalProperties": { "type": "string" }, "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" } }, "type": "object", "description": "Message to define resource requests and limits (mirroring Kubernetes) for each sandbox instance created from this template.", "id": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateResourceRequirements" }, "GoogleCloudAiplatformV1PairwiseSummarizationQualityInstance": { "id": "GoogleCloudAiplatformV1PairwiseSummarizationQualityInstance", "description": "Spec for pairwise summarization quality instance.", "type": "object", "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" } } }, "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig": { "type": "object", "description": "The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.", "properties": { "trainingDataset": { "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDataset", "description": "Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified." }, "predictionDriftDetectionConfig": { "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig", "description": "The config for drift of prediction data." }, "explanationConfig": { "description": "The config for integrating with Vertex Explainable AI.", "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfig" }, "trainingPredictionSkewDetectionConfig": { "description": "The config for skew between training data and prediction data.", "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig" } }, "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig" }, "GenaiVertexV1GoogleSearchCallStep": { "description": "Google Search call step.", "id": "GenaiVertexV1GoogleSearchCallStep", "properties": { "arguments": { "$ref": "GenaiVertexV1GoogleSearchCallStepGoogleSearchCallStepArguments", "description": "Required. The arguments to pass to Google Search." }, "searchType": { "type": "string", "description": "The type of search grounding enabled.", "enum": [ "SEARCH_TYPE_UNSPECIFIED", "SEARCH_TYPE_WEB_SEARCH", "SEARCH_TYPE_IMAGE_SEARCH", "SEARCH_TYPE_ENTERPRISE_WEB_SEARCH" ], "enumDescriptions": [ "Unspecified search type. This value should not be used.", "Setting this field enables web search. Only text results are returned.", "Setting this field enables image search. Image bytes are returned.", "Setting this field enables enterprise web search." ] } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef": { "type": "object", "properties": { "id": { "description": "ID of the AnnotationSpec.", "type": "string" }, "displayName": { "type": "string", "description": "Display name of the AnnotationSpec." } }, "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef" }, "GoogleCloudAiplatformV1GroundingChunkRetrievedContext": { "description": "Context retrieved from a data source to ground the model's response. This is used when a retrieval tool fetches information from a user-provided corpus or a public dataset.", "properties": { "uri": { "description": "The URI of the retrieved data source.", "type": "string" }, "ragChunk": { "$ref": "GoogleCloudAiplatformV1RagChunk", "description": "Additional context for a Retrieval-Augmented Generation (RAG) retrieval result. This is populated only when the RAG retrieval tool is used." }, "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" } }, "type": "object", "id": "GoogleCloudAiplatformV1GroundingChunkRetrievedContext" }, "GoogleCloudAiplatformV1UndeployIndexResponse": { "description": "Response message for IndexEndpointService.UndeployIndex.", "id": "GoogleCloudAiplatformV1UndeployIndexResponse", "properties": {}, "type": "object" }, "GoogleCloudAiplatformV1ReadFeatureValuesRequest": { "properties": { "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" }, "featureSelector": { "description": "Required. Selector choosing Features of the target EntityType.", "$ref": "GoogleCloudAiplatformV1FeatureSelector" } }, "description": "Request message for FeaturestoreOnlineServingService.ReadFeatureValues.", "id": "GoogleCloudAiplatformV1ReadFeatureValuesRequest", "type": "object" }, "GoogleCloudAiplatformV1TrainingConfig": { "description": "CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.", "properties": { "timeoutTrainingMilliHours": { "type": "string", "description": "The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.", "format": "int64" } }, "id": "GoogleCloudAiplatformV1TrainingConfig", "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation", "properties": { "columnName": { "type": "string" } }, "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.", "type": "object" }, "GoogleCloudAiplatformV1TensorboardBlobSequence": { "type": "object", "description": "One point viewable on a blob metric plot, but mostly just a wrapper message to work around repeated fields can't be used directly within `oneof` fields.", "id": "GoogleCloudAiplatformV1TensorboardBlobSequence", "properties": { "values": { "description": "List of blobs contained within the sequence.", "items": { "$ref": "GoogleCloudAiplatformV1TensorboardBlob" }, "type": "array" } } }, "GoogleCloudAiplatformV1RayClusterAutoscalingSpec": { "id": "GoogleCloudAiplatformV1RayClusterAutoscalingSpec", "properties": { "idleTimeoutMinutes": { "description": "Optional. The number of minutes that need to pass before an idle worker node is removed by the autoscaler. Default is 5 mins.", "type": "string", "format": "int64" }, "upscalingSpeed": { "type": "string", "description": "Optional. The number of nodes allowed to be pending as a multiple of the current number of nodes. [OSS Ray reference](https://docs.ray.io/en/latest/cluster/vms/user-guides/configuring-autoscaling.html#upscaling-and-downscaling-speed)", "format": "int64" } }, "description": "Ray cluster level autoscaling configuration.", "type": "object" }, "GenaiVertexV1Retrieval": { "id": "GenaiVertexV1Retrieval", "properties": { "vertexAiSearchConfig": { "$ref": "GenaiVertexV1VertexAISearchConfig", "description": "Used to specify configuration for VertexAISearch." }, "retrievalTypes": { "type": "array", "items": { "type": "string", "enum": [ "RETRIEVAL_TYPE_UNSPECIFIED", "RETRIEVAL_TYPE_VERTEX_AI_SEARCH", "RETRIEVAL_TYPE_RAG_STORE", "RETRIEVAL_TYPE_EXA_AI_SEARCH", "RETRIEVAL_TYPE_PARALLEL_AI_SEARCH" ], "enumDescriptions": [ "", "", "", "", "" ] }, "description": "The types of file retrieval to enable." }, "exaAiSearchConfig": { "description": "Used to specify configuration for ExaAISearch.", "$ref": "GenaiVertexV1ExaAISearchConfig" }, "ragStoreConfig": { "$ref": "GenaiVertexV1RagStoreConfig", "description": "Used to specify configuration for RagStore." }, "parallelAiSearchConfig": { "description": "Used to specify configuration for ParallelAISearch.", "$ref": "GenaiVertexV1ParallelAISearchConfig" } }, "type": "object", "description": "A tool that can be used by the model to retrieve files." }, "GoogleCloudAiplatformV1ExportModelRequest": { "id": "GoogleCloudAiplatformV1ExportModelRequest", "type": "object", "description": "Request message for ModelService.ExportModel.", "properties": { "outputConfig": { "$ref": "GoogleCloudAiplatformV1ExportModelRequestOutputConfig", "description": "Required. The desired output location and configuration." } } }, "GoogleCloudAiplatformV1DnsPeeringConfig": { "id": "GoogleCloudAiplatformV1DnsPeeringConfig", "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": { "targetNetwork": { "description": "Required. The VPC network name in the target_project where the DNS zone specified by 'domain' is visible.", "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" }, "domain": { "type": "string", "description": "Required. The DNS name suffix of the zone being peered to, e.g., \"my-internal-domain.corp.\". Must end with a dot." } }, "type": "object" }, "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec": { "id": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec", "properties": { "metricId": { "description": "Required. The ID of the metric. Must not contain whitespaces.", "type": "string" }, "goal": { "description": "Required. The optimization goal of the metric.", "enum": [ "GOAL_TYPE_UNSPECIFIED", "MAXIMIZE", "MINIMIZE" ], "type": "string", "enumDescriptions": [ "Goal Type will default to maximize.", "Maximize the goal metric.", "Minimize the goal metric." ] } }, "type": "object", "description": "Represents a metric to optimize." }, "GoogleCloudAiplatformV1ExportFeatureValuesRequestFullExport": { "properties": { "startTime": { "type": "string", "format": "google-datetime", "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." }, "endTime": { "format": "google-datetime", "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." } }, "type": "object", "id": "GoogleCloudAiplatformV1ExportFeatureValuesRequestFullExport", "description": "Describes exporting all historical Feature values of all entities of the EntityType between [start_time, end_time]." }, "GoogleCloudAiplatformV1RagRetrievalConfigFilter": { "id": "GoogleCloudAiplatformV1RagRetrievalConfigFilter", "type": "object", "properties": { "metadataFilter": { "description": "Optional. String for metadata filtering.", "type": "string" }, "vectorDistanceThreshold": { "type": "number", "description": "Optional. Only returns contexts with vector distance smaller than the threshold.", "format": "double" }, "vectorSimilarityThreshold": { "format": "double", "description": "Optional. Only returns contexts with vector similarity larger than the threshold.", "type": "number" } }, "description": "Config for filters." }, "GoogleCloudAiplatformV1TensorboardTimeSeries": { "id": "GoogleCloudAiplatformV1TensorboardTimeSeries", "description": "TensorboardTimeSeries maps to times series produced in training runs", "properties": { "valueType": { "description": "Required. Immutable. Type of TensorboardTimeSeries value.", "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." ] }, "description": { "description": "Description of this TensorboardTimeSeries.", "type": "string" }, "pluginData": { "format": "byte", "type": "string", "description": "Data of the current plugin, with the size limited to 65KB." }, "metadata": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeriesMetadata", "description": "Output only. Scalar, Tensor, or Blob metadata for this TensorboardTimeSeries." }, "createTime": { "type": "string", "description": "Output only. Timestamp when this TensorboardTimeSeries was created.", "readOnly": true, "format": "google-datetime" }, "pluginName": { "type": "string", "description": "Immutable. Name of the plugin this time series pertain to. Such as Scalar, Tensor, Blob" }, "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" }, "updateTime": { "readOnly": true, "description": "Output only. Timestamp when this TensorboardTimeSeries was last updated.", "type": "string", "format": "google-datetime" }, "name": { "type": "string", "description": "Output only. Name of the TensorboardTimeSeries.", "readOnly": true }, "etag": { "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1WriteFeatureValuesPayload": { "type": "object", "id": "GoogleCloudAiplatformV1WriteFeatureValuesPayload", "description": "Contains Feature values to be written for a specific entity.", "properties": { "entityId": { "description": "Required. The ID of the entity.", "type": "string" }, "featureValues": { "additionalProperties": { "$ref": "GoogleCloudAiplatformV1FeatureValue" }, "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" } } }, "GoogleCloudAiplatformV1RagManagedDbConfigScaled": { "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": {}, "id": "GoogleCloudAiplatformV1RagManagedDbConfigScaled", "type": "object" }, "GoogleCloudAiplatformV1CompletionStats": { "id": "GoogleCloudAiplatformV1CompletionStats", "type": "object", "description": "Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.", "properties": { "successfulCount": { "format": "int64", "readOnly": true, "description": "Output only. The number of entities that had been processed successfully.", "type": "string" }, "incompleteCount": { "type": "string", "readOnly": true, "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" }, "failedCount": { "format": "int64", "readOnly": true, "type": "string", "description": "Output only. The number of entities for which any error was encountered." }, "successfulForecastPointCount": { "format": "int64", "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.", "type": "string" } } }, "GoogleCloudAiplatformV1ShieldedVmConfig": { "description": "A set of Shielded Instance options. See [Images using supported Shielded VM features](https://cloud.google.com/compute/docs/instances/modifying-shielded-vm).", "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" } }, "type": "object", "id": "GoogleCloudAiplatformV1ShieldedVmConfig" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata", "type": "object", "description": "Model metadata specific to Seq2Seq Plus Forecasting.", "properties": { "evaluatedDataItemsBigqueryUri": { "description": "BigQuery destination uri for exported evaluated examples.", "type": "string" }, "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." } } }, "GoogleCloudAiplatformV1Content": { "type": "object", "properties": { "role": { "type": "string", "description": "Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'." }, "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": "GoogleCloudAiplatformV1Part" } } }, "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.", "id": "GoogleCloudAiplatformV1Content" }, "GoogleCloudAiplatformV1DeployRequest": { "id": "GoogleCloudAiplatformV1DeployRequest", "description": "Request message for ModelGardenService.Deploy.", "type": "object", "properties": { "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" }, "huggingFaceModelId": { "type": "string", "description": "The Hugging Face model to deploy. Format: Hugging Face model ID like `google/gemma-2-2b-it`." }, "deployConfig": { "$ref": "GoogleCloudAiplatformV1DeployRequestDeployConfig", "description": "Optional. The deploy config to use for the deployment. If not specified, the default deploy config will be used." }, "modelConfig": { "$ref": "GoogleCloudAiplatformV1DeployRequestModelConfig", "description": "Optional. The model config to use for the deployment. If not specified, the default model 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.", "$ref": "GoogleCloudAiplatformV1DeployRequestEndpointConfig" } } }, "GoogleCloudAiplatformV1CandidateResponse": { "description": "Responses from model or agent.", "properties": { "text": { "type": "string", "description": "Text response." }, "error": { "$ref": "GoogleRpcStatus", "readOnly": true, "description": "Output only. Error while scraping model or agent." }, "agentData": { "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.", "$ref": "GoogleCloudAiplatformV1AgentData" }, "value": { "description": "Fields and values that can be used to populate the response template.", "type": "any" }, "candidate": { "type": "string", "description": "Required. The name of the candidate that produced the response." } }, "id": "GoogleCloudAiplatformV1CandidateResponse", "type": "object" }, "GoogleCloudAiplatformV1MigrateResourceRequestMigrateMlEngineModelVersionConfig": { "properties": { "modelDisplayName": { "description": "Required. Display name of the model in Vertex AI. System will pick a display name if unspecified.", "type": "string" }, "modelVersion": { "description": "Required. Full resource name of ml engine model version. Format: `projects/{project}/models/{model}/versions/{version}`.", "type": "string" }, "endpoint": { "type": "string", "description": "Required. The ml.googleapis.com endpoint that this model version should be migrated from. Example values: * ml.googleapis.com * us-centrall-ml.googleapis.com * europe-west4-ml.googleapis.com * asia-east1-ml.googleapis.com" } }, "id": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateMlEngineModelVersionConfig", "description": "Config for migrating version in ml.googleapis.com to Vertex AI's Model.", "type": "object" }, "GoogleCloudAiplatformV1ServingProfile": { "properties": { "updateTime": { "format": "google-datetime", "type": "string", "readOnly": true, "description": "Output only. Timestamp when the ServingProfile was last updated." }, "cmekConfig": { "description": "CMEK configuration for the ServingProfile.", "$ref": "GoogleCloudAiplatformV1ServingProfileCmekConfig" }, "displayName": { "description": "Required. The display name of the ServingProfile. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "description": { "description": "Optional. The description of the ServingProfile.", "type": "string" }, "createTime": { "readOnly": true, "format": "google-datetime", "description": "Output only. Timestamp when the ServingProfile was created.", "type": "string" }, "name": { "description": "Identifier. The resource name of the ServingProfile.", "type": "string" }, "scope": { "type": "string", "description": "Required. The specific API this ServingProfile applies to.", "enumDescriptions": [ "Default value. This value is unused. When users create a ServingProfile, they must choose a scope.", "The scope for Gemini Live.", "The scope for Interactions API.", "The scope for Response API." ], "enum": [ "SERVING_PROFILE_SCOPE_UNSPECIFIED", "GEMINI_LIVE", "INTERACTIONS_API", "RESPONSE_API" ] } }, "description": "Configures the serving behavior for a resource-less GenAI serving.", "type": "object", "id": "GoogleCloudAiplatformV1ServingProfile" }, "GoogleCloudAiplatformV1AssignNotebookRuntimeOperationMetadata": { "id": "GoogleCloudAiplatformV1AssignNotebookRuntimeOperationMetadata", "description": "Metadata information for NotebookService.AssignNotebookRuntime.", "type": "object", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" }, "progressMessage": { "type": "string", "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime." } } }, "GoogleCloudAiplatformV1SandboxEnvironmentSpec": { "id": "GoogleCloudAiplatformV1SandboxEnvironmentSpec", "type": "object", "description": "The specification of a SandboxEnvironment.", "properties": { "codeExecutionEnvironment": { "description": "Optional. The code execution environment.", "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentSpecCodeExecutionEnvironment" }, "shellEnvironment": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentSpecShellEnvironment", "description": "Optional. The shell environment for executing shell commands and scripts." } } }, "GoogleCloudAiplatformV1NotebookSoftwareConfig": { "properties": { "env": { "description": "Optional. Environment variables to be passed to the container. Maximum limit is 100.", "items": { "$ref": "GoogleCloudAiplatformV1EnvVar" }, "type": "array" }, "colabImage": { "description": "Optional. Google-managed NotebookRuntime colab image.", "$ref": "GoogleCloudAiplatformV1ColabImage" }, "postStartupScriptConfig": { "description": "Optional. Post startup script config.", "$ref": "GoogleCloudAiplatformV1PostStartupScriptConfig" } }, "description": "Notebook Software Config. This is passed to the backend when user makes software configurations in UI.", "type": "object", "id": "GoogleCloudAiplatformV1NotebookSoftwareConfig" }, "GoogleCloudAiplatformV1Tool": { "type": "object", "properties": { "enterpriseWebSearch": { "description": "Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.", "$ref": "GoogleCloudAiplatformV1EnterpriseWebSearch" }, "googleSearch": { "description": "Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.", "$ref": "GoogleCloudAiplatformV1ToolGoogleSearch" }, "googleSearchRetrieval": { "description": "Optional. Specialized retrieval tool that is powered by Google Search.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1GoogleSearchRetrieval" }, "retrieval": { "description": "Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.", "$ref": "GoogleCloudAiplatformV1Retrieval" }, "functionDeclarations": { "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.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1FunctionDeclaration" } }, "parallelAiSearch": { "description": "Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation", "$ref": "GoogleCloudAiplatformV1ToolParallelAiSearch" }, "codeExecution": { "description": "Optional. CodeExecution tool type. Enables the model to execute code as part of generation.", "$ref": "GoogleCloudAiplatformV1ToolCodeExecution" }, "urlContext": { "$ref": "GoogleCloudAiplatformV1UrlContext", "description": "Optional. Tool to support URL context retrieval." }, "exaAiSearch": { "$ref": "GoogleCloudAiplatformV1ToolExaAiSearch", "description": "Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation" }, "computerUse": { "$ref": "GoogleCloudAiplatformV1ToolComputerUse", "description": "Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations." }, "googleMaps": { "$ref": "GoogleCloudAiplatformV1GoogleMaps", "description": "Optional. GoogleMaps tool type. Tool to support Google Maps in Model." } }, "description": "Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).", "id": "GoogleCloudAiplatformV1Tool" }, "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSource": { "description": "A conversation source for the example. This is similar to `DirectContentsSource`.", "properties": { "events": { "description": "Optional. Represents the input conversation events for the example.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSourceEvent" } } }, "id": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSource", "type": "object" }, "GoogleCloudAiplatformV1ColabImage": { "type": "object", "id": "GoogleCloudAiplatformV1ColabImage", "properties": { "releaseName": { "type": "string", "description": "Optional. The release name of the NotebookRuntime Colab image, e.g. \"py310\". If not specified, detault to the latest release." }, "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\"" } }, "description": "Colab image of the runtime." }, "GoogleCloudAiplatformV1NotebookRuntimeTemplateRef": { "properties": { "notebookRuntimeTemplate": { "type": "string", "description": "Immutable. A resource name of the NotebookRuntimeTemplate." } }, "id": "GoogleCloudAiplatformV1NotebookRuntimeTemplateRef", "type": "object", "description": "Points to a NotebookRuntimeTemplateRef." }, "GoogleCloudAiplatformV1TrajectoryExactMatchInstance": { "description": "Spec for TrajectoryExactMatch instance.", "properties": { "predictedTrajectory": { "$ref": "GoogleCloudAiplatformV1Trajectory", "description": "Required. Spec for predicted tool call trajectory." }, "referenceTrajectory": { "$ref": "GoogleCloudAiplatformV1Trajectory", "description": "Required. Spec for reference tool call trajectory." } }, "id": "GoogleCloudAiplatformV1TrajectoryExactMatchInstance", "type": "object" }, "GoogleCloudAiplatformV1VertexAISearch": { "properties": { "engine": { "description": "Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`", "type": "string" }, "dataStoreSpecs": { "items": { "$ref": "GoogleCloudAiplatformV1VertexAISearchDataStoreSpec" }, "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" }, "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" }, "maxResults": { "format": "int32", "description": "Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.", "type": "integer" } }, "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", "type": "object", "id": "GoogleCloudAiplatformV1VertexAISearch" }, "GoogleCloudAiplatformV1SchemaPredictPredictionImageSegmentationPredictionResult": { "properties": { "categoryMask": { "type": "string", "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." }, "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.", "id": "GoogleCloudAiplatformV1SchemaPredictPredictionImageSegmentationPredictionResult", "type": "object" }, "GoogleCloudAiplatformV1FeatureViewOptimizedConfig": { "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": "GoogleCloudAiplatformV1AutomaticResources" } }, "id": "GoogleCloudAiplatformV1FeatureViewOptimizedConfig", "type": "object" }, "GoogleCloudAiplatformV1EvaluationInstance": { "id": "GoogleCloudAiplatformV1EvaluationInstance", "type": "object", "properties": { "rubricGroups": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1RubricGroup" }, "description": "Optional. Named groups of rubrics associated with the prompt. This is used for rubric-based evaluations where rubrics can be referenced by a key. The key could represent versions, associated metrics, etc." }, "reference": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceInstanceData", "description": "Optional. Data used to populate placeholder `reference` in a metric prompt template." }, "interactionsDataSource": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceInteractionsDataSource", "description": "Optional. Source for populating `AgentData` from an Interactions API interaction. If set, no other agent data source fields (`cloud_trace_agent_data_source`, `agent_eval_data`, `agent_data`) may be set. The request will be rejected with INVALID_ARGUMENT if multiple agent data sources are provided." }, "agentEvalData": { "description": "Optional. Data used for agent evaluation.", "$ref": "GoogleCloudAiplatformV1AgentData" }, "prompt": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceInstanceData", "description": "Optional. Data used to populate placeholder `prompt` in a metric prompt template." }, "response": { "description": "Optional. Data used to populate placeholder `response` in a metric prompt template.", "$ref": "GoogleCloudAiplatformV1EvaluationInstanceInstanceData" }, "agentData": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentData", "description": "Optional. Deprecated: Use `agent_eval_data` instead. Data used for agent evaluation.", "deprecated": true }, "otherData": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceMapInstance", "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." } }, "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" }, "GoogleCloudAiplatformV1Candidate": { "id": "GoogleCloudAiplatformV1Candidate", "type": "object", "properties": { "content": { "description": "Output only. The content of the candidate.", "$ref": "GoogleCloudAiplatformV1Content", "readOnly": true }, "citationMetadata": { "readOnly": true, "description": "Output only. A collection of citations that apply to the generated content.", "$ref": "GoogleCloudAiplatformV1CitationMetadata" }, "groundingMetadata": { "description": "Output only. Metadata returned when grounding is enabled. It contains the sources used to ground the generated content.", "$ref": "GoogleCloudAiplatformV1GroundingMetadata", "readOnly": true }, "index": { "description": "Output only. The 0-based index of this candidate in the list of generated responses. This is useful for distinguishing between multiple candidates when `candidate_count` \u003e 1.", "readOnly": true, "type": "integer", "format": "int32" }, "urlContextMetadata": { "$ref": "GoogleCloudAiplatformV1UrlContextMetadata", "description": "Output only. Metadata returned when the model uses the `url_context` tool to get information from a user-provided URL.", "readOnly": true }, "logprobsResult": { "readOnly": true, "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\".", "$ref": "GoogleCloudAiplatformV1LogprobsResult" }, "safetyRatings": { "description": "Output only. A list of ratings for the safety of a response candidate. There is at most one rating per category.", "items": { "$ref": "GoogleCloudAiplatformV1SafetyRating" }, "type": "array", "readOnly": true }, "finishMessage": { "readOnly": true, "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" }, "continuationToken": { "readOnly": true, "format": "byte", "description": "Output only. An optional opaque continuation token returned when `finish_reason` is `CONTINUATION`. Clients can pass this token in a subsequent `GenerateContentRequest` to continue generation.", "type": "string" }, "finishReason": { "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", "MALFORMED_RESPONSE", "CONTINUATION" ], "type": "string", "readOnly": true, "description": "Output only. The reason why the model stopped generating tokens. If empty, the model has not stopped generating.", "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.", "Finishes due to malformed response.", "Token generation was stopped because the response reached the per-request token limit, but generation is not yet complete. The model response can be continued via a subsequent request using the returned `continuation_token`." ] }, "avgLogprobs": { "readOnly": true, "format": "double", "type": "number", "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." } }, "description": "A response candidate generated from the model." }, "GoogleCloudAiplatformV1CsvDestination": { "id": "GoogleCloudAiplatformV1CsvDestination", "type": "object", "description": "The storage details for CSV output content.", "properties": { "gcsDestination": { "description": "Required. Google Cloud Storage location.", "$ref": "GoogleCloudAiplatformV1GcsDestination" } } }, "GoogleCloudAiplatformV1ToolParameterKeyMatchInstance": { "description": "Spec for tool parameter key match instance.", "type": "object", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "reference": { "description": "Required. Ground truth used to compare against the prediction.", "type": "string" } }, "id": "GoogleCloudAiplatformV1ToolParameterKeyMatchInstance" }, "GoogleCloudAiplatformV1AugmentPromptRequest": { "description": "Request message for AugmentPrompt.", "type": "object", "properties": { "vertexRagStore": { "$ref": "GoogleCloudAiplatformV1VertexRagStore", "description": "Optional. Retrieves contexts from the Vertex RagStore." }, "contents": { "items": { "$ref": "GoogleCloudAiplatformV1Content" }, "type": "array", "description": "Optional. Input content to augment, only text format is supported for now." }, "model": { "description": "Optional. Metadata of the backend deployed model.", "$ref": "GoogleCloudAiplatformV1AugmentPromptRequestModel" } }, "id": "GoogleCloudAiplatformV1AugmentPromptRequest" }, "GoogleCloudAiplatformV1ReasoningEngineSpecBuildSpec": { "id": "GoogleCloudAiplatformV1ReasoningEngineSpecBuildSpec", "properties": { "workerPool": { "description": "Optional. Identifier. The resource name of the Cloud Build WorkerPool to use for the build. Format: `projects/{project}/locations/{location}/workerPools/{worker_pool}`", "type": "string" }, "serviceAccount": { "description": "Optional. The service account that Cloud Build uses to run the build. This field is only applicable when `worker_pool` is specified (i.e., for custom worker pools). If `worker_pool` is not specified, this field is ignored and the build runs using the Google-managed service agent. Format: `projects/{project}/serviceAccounts/{service_account}` or `{service_account}@{project}.iam.gserviceaccount.com`", "type": "string" } }, "description": "Specification for building container image.", "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs", "type": "object", "properties": { "timeColumn": { "description": "The name of the column that identifies time order in the time series. This column must be available at forecast.", "type": "string" }, "timeSeriesIdentifierColumn": { "type": "string", "description": "The name of the column that identifies the time series." }, "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" }, "hierarchyConfig": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHierarchyConfig", "description": "Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies." }, "contextWindow": { "type": "string", "format": "int64", "description": "The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field." }, "optimizationObjective": { "description": "Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * \"minimize-rmse\" (default) - Minimize root-mean-squared error (RMSE). * \"minimize-mae\" - Minimize mean-absolute error (MAE). * \"minimize-rmsle\" - Minimize root-mean-squared log error (RMSLE). * \"minimize-rmspe\" - Minimize root-mean-squared percentage error (RMSPE). * \"minimize-wape-mae\" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * \"minimize-quantile-loss\" - Minimize the quantile loss at the quantiles defined in `quantiles`. * \"minimize-mape\" - Minimize the mean absolute percentage error.", "type": "string" }, "exportEvaluatedDataItemsConfig": { "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig" }, "dataGranularity": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity", "description": "Expected difference in time granularity between rows in the data." }, "unavailableAtForecastColumns": { "type": "array", "description": "Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day.", "items": { "type": "string" } }, "targetColumn": { "type": "string", "description": "The name of the column that the Model is to predict values for. This column must be unavailable at forecast." }, "timeSeriesAttributeColumns": { "description": "Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color.", "items": { "type": "string" }, "type": "array" }, "additionalExperiments": { "items": { "type": "string" }, "type": "array", "description": "Additional experiment flags for the time series forcasting training." }, "transformations": { "description": "Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using \".\" as the delimiter.", "items": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation" }, "type": "array" }, "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" }, "forecastHorizon": { "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", "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.", "type": "string", "format": "int64" }, "holidayRegions": { "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.", "type": "array" }, "windowConfig": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig", "description": "Config containing strategy for generating sliding windows." }, "quantiles": { "type": "array", "items": { "type": "number", "format": "double" }, "description": "Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique." }, "availableAtForecastColumns": { "type": "array", "items": { "type": "string" }, "description": "Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day." } } }, "GoogleCloudAiplatformV1UpdateExplanationDatasetResponse": { "id": "GoogleCloudAiplatformV1UpdateExplanationDatasetResponse", "type": "object", "description": "Response message of ModelService.UpdateExplanationDataset operation.", "properties": {} }, "GoogleCloudAiplatformV1ActivateOnlineEvaluatorOperationMetadata": { "id": "GoogleCloudAiplatformV1ActivateOnlineEvaluatorOperationMetadata", "type": "object", "properties": { "genericMetadata": { "description": "Common part of operation metadata.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "description": "Metadata for the ActivateOnlineEvaluator operation." }, "GoogleCloudAiplatformV1FulfillmentResult": { "type": "object", "description": "Spec for fulfillment result.", "id": "GoogleCloudAiplatformV1FulfillmentResult", "properties": { "explanation": { "readOnly": true, "description": "Output only. Explanation for fulfillment score.", "type": "string" }, "confidence": { "description": "Output only. Confidence for fulfillment score.", "readOnly": true, "type": "number", "format": "float" }, "score": { "type": "number", "format": "float", "description": "Output only. Fulfillment score.", "readOnly": true } } }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionRecognitionMetrics": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionRecognitionMetrics", "properties": { "evaluatedActionCount": { "format": "int32", "description": "The number of ground truth actions used to create this evaluation.", "type": "integer" }, "videoActionMetrics": { "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetrics" }, "type": "array", "description": "The metric entries for precision window lengths: 1s,2s,3s." } }, "description": "Model evaluation metrics for video action recognition.", "type": "object" }, "GoogleCloudAiplatformV1ModelGardenSource": { "properties": { "skipHfModelCache": { "description": "Optional. Whether to avoid pulling the model from the HF cache.", "type": "boolean" }, "versionId": { "type": "string", "description": "Optional. The model garden source model version ID." }, "publicModelName": { "type": "string", "description": "Required. The model garden source model resource name." } }, "description": "Contains information about the source of the models generated from Model Garden.", "id": "GoogleCloudAiplatformV1ModelGardenSource", "type": "object" }, "GoogleCloudAiplatformV1TrajectoryPrecisionMetricValue": { "description": "TrajectoryPrecision metric value for an instance.", "id": "GoogleCloudAiplatformV1TrajectoryPrecisionMetricValue", "properties": { "score": { "readOnly": true, "description": "Output only. TrajectoryPrecision score.", "type": "number", "format": "float" } }, "type": "object" }, "GoogleCloudAiplatformV1StudyTimeConstraint": { "properties": { "maxDuration": { "type": "string", "format": "google-duration", "description": "Counts the wallclock time passed since the creation of this Study." }, "endTime": { "description": "Compares the wallclock time to this time. Must use UTC timezone.", "type": "string", "format": "google-datetime" } }, "description": "Time-based Constraint for Study", "type": "object", "id": "GoogleCloudAiplatformV1StudyTimeConstraint" }, "GoogleCloudAiplatformV1GenAiAdvancedFeaturesConfigRagConfig": { "description": "Configuration for Retrieval Augmented Generation feature.", "type": "object", "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": "GoogleCloudAiplatformV1GenAiAdvancedFeaturesConfigRagConfig" }, "GenaiVertexV1ProcessingResultStep": { "type": "object", "description": "The result of a server-initiated media processing step.", "properties": {}, "id": "GenaiVertexV1ProcessingResultStep" }, "GoogleCloudAiplatformV1NotebookRuntime": { "id": "GoogleCloudAiplatformV1NotebookRuntime", "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.", "type": "object", "properties": { "expirationTime": { "readOnly": true, "format": "google-datetime", "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.", "type": "string" }, "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" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "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." }, "proxyUri": { "description": "Output only. The proxy endpoint used to access the NotebookRuntime.", "type": "string", "readOnly": true }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" }, "updateTime": { "description": "Output only. Timestamp when this NotebookRuntime was most recently updated.", "type": "string", "readOnly": true, "format": "google-datetime" }, "reservationAffinity": { "description": "Output only. Reservation Affinity of the notebook runtime.", "$ref": "GoogleCloudAiplatformV1NotebookReservationAffinity", "readOnly": true }, "description": { "description": "The description of the NotebookRuntime.", "type": "string" }, "runtimeUser": { "type": "string", "description": "Required. The user email of the NotebookRuntime." }, "notebookRuntimeType": { "readOnly": true, "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." ], "type": "string", "enum": [ "NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED", "USER_DEFINED", "ONE_CLICK" ], "description": "Output only. The type of the notebook runtime." }, "name": { "description": "Output only. The resource name of the NotebookRuntime.", "readOnly": true, "type": "string" }, "softwareConfig": { "$ref": "GoogleCloudAiplatformV1NotebookSoftwareConfig", "readOnly": true, "description": "Output only. Software config of the notebook runtime." }, "networkTags": { "description": "Optional. The Compute Engine tags to add to runtime (see [Tagging instances](https://cloud.google.com/vpc/docs/add-remove-network-tags)).", "type": "array", "items": { "type": "string" } }, "version": { "readOnly": true, "description": "Output only. The VM os image version of NotebookRuntime.", "type": "string" }, "isUpgradable": { "description": "Output only. Whether NotebookRuntime is upgradable.", "readOnly": true, "type": "boolean" }, "satisfiesPzs": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "idleShutdownConfig": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1NotebookIdleShutdownConfig", "description": "Output only. The idle shutdown configuration of the notebook runtime." }, "machineSpec": { "$ref": "GoogleCloudAiplatformV1MachineSpec", "description": "Output only. The specification of a single machine used by the notebook runtime.", "readOnly": true }, "shieldedVmConfig": { "description": "Output only. Runtime Shielded VM spec.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1ShieldedVmConfig" }, "dataPersistentDiskSpec": { "readOnly": true, "description": "Output only. The specification of persistent disk attached to the notebook runtime as data disk storage.", "$ref": "GoogleCloudAiplatformV1PersistentDiskSpec" }, "networkSpec": { "$ref": "GoogleCloudAiplatformV1NetworkSpec", "description": "Output only. Network spec of the notebook runtime.", "readOnly": true }, "serviceAccount": { "readOnly": true, "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.", "type": "string" }, "healthState": { "enum": [ "HEALTH_STATE_UNSPECIFIED", "HEALTHY", "UNHEALTHY" ], "description": "Output only. The health state of the NotebookRuntime.", "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 }, "notebookRuntimeTemplateRef": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplateRef", "description": "Output only. The pointer to NotebookRuntimeTemplate this NotebookRuntime is created from." }, "createTime": { "format": "google-datetime", "type": "string", "readOnly": true, "description": "Output only. Timestamp when this NotebookRuntime was created." }, "runtimeState": { "readOnly": true, "description": "Output only. The runtime (instance) state of the NotebookRuntime.", "enumDescriptions": [ "Unspecified runtime state.", "NotebookRuntime is in running state.", "NotebookRuntime is in starting state. This is when the runtime is being started from a stopped state.", "NotebookRuntime is in stopping state.", "NotebookRuntime is in stopped state.", "NotebookRuntime is in upgrading state. It is in the middle of upgrading process.", "NotebookRuntime was unable to start/stop properly.", "NotebookRuntime is in invalid state. Cannot be recovered." ], "enum": [ "RUNTIME_STATE_UNSPECIFIED", "RUNNING", "BEING_STARTED", "BEING_STOPPED", "STOPPED", "BEING_UPGRADED", "ERROR", "INVALID" ], "type": "string" }, "encryptionSpec": { "description": "Output only. Customer-managed encryption key spec for the notebook runtime.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "eucConfig": { "$ref": "GoogleCloudAiplatformV1NotebookEucConfig", "description": "Output only. EUC configuration of the notebook runtime.", "readOnly": true } } }, "GoogleCloudAiplatformV1MigratableResource": { "id": "GoogleCloudAiplatformV1MigratableResource", "description": "Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com.", "properties": { "mlEngineModelVersion": { "$ref": "GoogleCloudAiplatformV1MigratableResourceMlEngineModelVersion", "readOnly": true, "description": "Output only. Represents one Version in ml.googleapis.com." }, "lastMigrateTime": { "type": "string", "format": "google-datetime", "readOnly": true, "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." }, "automlDataset": { "$ref": "GoogleCloudAiplatformV1MigratableResourceAutomlDataset", "readOnly": true, "description": "Output only. Represents one Dataset in automl.googleapis.com." }, "dataLabelingDataset": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1MigratableResourceDataLabelingDataset", "readOnly": true, "description": "Output only. Deprecated: Data Labeling Dataset migration is no longer supported. Represents one Dataset in datalabeling.googleapis.com." }, "automlModel": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1MigratableResourceAutomlModel", "description": "Output only. Represents one Model in automl.googleapis.com." }, "lastUpdateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this MigratableResource was last updated.", "readOnly": true, "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1ToolParameterKVMatchResults": { "id": "GoogleCloudAiplatformV1ToolParameterKVMatchResults", "properties": { "toolParameterKvMatchMetricValues": { "description": "Output only. Tool parameter key value match metric values.", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1ToolParameterKVMatchMetricValue" }, "type": "array" } }, "description": "Results for tool parameter key value match metric.", "type": "object" }, "CloudAiLargeModelsVisionGenerateVideoExperimentsColorAlignmentConfig": { "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsColorAlignmentConfig", "type": "object", "description": "Configuration for color alignment.", "properties": { "enable": { "description": "Optional. If true, enable alignment.", "type": "boolean" } } }, "GenaiVertexV1GoogleSearchResultContentGoogleSearchResult": { "id": "GenaiVertexV1GoogleSearchResultContentGoogleSearchResult", "properties": { "searchSuggestions": { "type": "string", "description": "Web content snippet that can be embedded in a web page or an app webview." } }, "description": "The result of the Google Search.", "type": "object" }, "GoogleCloudAiplatformV1CancelNasJobRequest": { "type": "object", "description": "Request message for JobService.CancelNasJob.", "properties": {}, "id": "GoogleCloudAiplatformV1CancelNasJobRequest" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec": { "properties": { "trialJobSpec": { "$ref": "GoogleCloudAiplatformV1CustomJobSpec", "description": "The spec of a trial job. The same spec applies to the CustomJobs created in all the trials." }, "studySpec": { "description": "Study configuration of the HyperparameterTuningJob.", "$ref": "GoogleCloudAiplatformV1StudySpec" }, "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" }, "parallelTrialCount": { "type": "integer", "description": "The desired number of Trials to run in parallel.", "format": "int32" }, "maxTrialCount": { "type": "integer", "description": "The desired total number of Trials.", "format": "int32" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec" }, "GenaiVertexV1GoogleMapsCallStep": { "description": "Google Maps call step.", "properties": { "arguments": { "$ref": "GenaiVertexV1GoogleMapsCallStepGoogleMapsCallStepArguments", "description": "The arguments to pass to the Google Maps tool." } }, "type": "object", "id": "GenaiVertexV1GoogleMapsCallStep" }, "GoogleCloudAiplatformV1TimeSeriesData": { "type": "object", "id": "GoogleCloudAiplatformV1TimeSeriesData", "description": "All the data stored in a TensorboardTimeSeries.", "properties": { "values": { "type": "array", "description": "Required. Data points in this time series.", "items": { "$ref": "GoogleCloudAiplatformV1TimeSeriesDataPoint" } }, "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.", "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" ], "type": "string" } } }, "GoogleCloudAiplatformV1GoogleMapsRouting": { "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1GoogleMapsRouting", "description": "Grounding with Google Maps Routing APIs (ComputeRoutes and SearchAlongRoute)." }, "GenaiVertexV1DeleteInteractionResponse": { "properties": {}, "description": "Response for InteractionService.DeleteInteraction.", "id": "GenaiVertexV1DeleteInteractionResponse", "type": "object" }, "GoogleCloudAiplatformV1MemoryGenerationTriggerConfig": { "type": "object", "properties": { "generationRule": { "description": "Optional. Represents the active rule that determines when to flush the buffer. If not set, then the stream will be force flushed immediately.", "$ref": "GoogleCloudAiplatformV1MemoryGenerationTriggerConfigGenerationTriggerRule" } }, "description": "Represents configuration for triggering generation.", "id": "GoogleCloudAiplatformV1MemoryGenerationTriggerConfig" }, "GenaiVertexV1UrlContext": { "description": "A tool that can be used by the model to fetch URL context.", "type": "object", "properties": {}, "id": "GenaiVertexV1UrlContext" }, "GoogleCloudAiplatformV1Probe": { "type": "object", "description": "Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.", "properties": { "exec": { "$ref": "GoogleCloudAiplatformV1ProbeExecAction", "description": "ExecAction probes the health of a container by executing a command." }, "failureThreshold": { "type": "integer", "description": "Number of consecutive failures before the probe is considered failed. Defaults to 3. Minimum value is 1. Maps to Kubernetes probe argument 'failureThreshold'.", "format": "int32" }, "httpGet": { "$ref": "GoogleCloudAiplatformV1ProbeHttpGetAction", "description": "HttpGetAction probes the health of a container by sending an HTTP GET request." }, "tcpSocket": { "$ref": "GoogleCloudAiplatformV1ProbeTcpSocketAction", "description": "TcpSocketAction probes the health of a container by opening a TCP socket connection." }, "timeoutSeconds": { "type": "integer", "format": "int32", "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'." }, "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" }, "periodSeconds": { "format": "int32", "type": "integer", "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'." }, "grpc": { "description": "GrpcAction probes the health of a container by sending a gRPC request.", "$ref": "GoogleCloudAiplatformV1ProbeGrpcAction" }, "initialDelaySeconds": { "description": "Number of seconds to wait before starting the probe. Defaults to 0. Minimum value is 0. Maps to Kubernetes probe argument 'initialDelaySeconds'.", "type": "integer", "format": "int32" } }, "id": "GoogleCloudAiplatformV1Probe" }, "GoogleCloudAiplatformV1EvaluationInstanceMapInstance": { "description": "Instance data specified as a map.", "properties": { "mapInstance": { "additionalProperties": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceInstanceData" }, "description": "Optional. Map of instance data.", "type": "object" } }, "type": "object", "id": "GoogleCloudAiplatformV1EvaluationInstanceMapInstance" }, "GoogleCloudAiplatformV1DeleteOnlineEvaluatorOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Generic operation metadata." } }, "id": "GoogleCloudAiplatformV1DeleteOnlineEvaluatorOperationMetadata", "description": "Metadata for the DeleteOnlineEvaluator operation.", "type": "object" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetrics": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetrics", "type": "object", "description": "UNIMPLEMENTED. Track matching model metrics for a single track match threshold and multiple label match confidence thresholds.", "properties": { "meanBoundingBoxIou": { "format": "float", "description": "The mean bounding box iou over all confidence thresholds.", "type": "number" }, "iouThreshold": { "type": "number", "description": "The intersection-over-union threshold value between bounding boxes across frames used to compute this metric entry.", "format": "float" }, "confidenceMetrics": { "type": "array", "description": "Metrics for each label-match `confidenceThreshold` from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is derived from them.", "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics" } }, "meanTrackingAveragePrecision": { "description": "The mean average precision over all confidence thresholds.", "type": "number", "format": "float" }, "meanMismatchRate": { "format": "float", "type": "number", "description": "The mean mismatch rate over all confidence thresholds." } } }, "GoogleCloudAiplatformV1FeatureViewSyncConfig": { "type": "object", "description": "Configuration for Sync. Only one option is set.", "id": "GoogleCloudAiplatformV1FeatureViewSyncConfig", "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 ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, \"CRON_TZ=America/New_York 1 * * * *\", or \"TZ=America/New_York 1 * * * *\".", "type": "string" } } }, "CloudAiLargeModelsVisionGenerateVideoRequestAudio": { "properties": { "mimeType": { "description": "The MIME type of the content of the audio. Only audio in below listed MIME types are supported. - audio/wav - audio/mp3 - audio/mpeg", "type": "string" }, "blobId": { "description": "Blob ID of the audio. This is used for storing the large audio in the request.", "type": "string" }, "gcsUri": { "type": "string" }, "bytesBase64Encoded": { "type": "string", "description": "Base64 encoded bytes string representing the audio." } }, "id": "CloudAiLargeModelsVisionGenerateVideoRequestAudio", "type": "object", "description": "The raw bytes or Cloud Storage URI for an audio input." }, "GoogleCloudAiplatformV1ListSessionsResponse": { "description": "Response message for SessionService.ListSessions.", "id": "GoogleCloudAiplatformV1ListSessionsResponse", "properties": { "nextPageToken": { "type": "string", "description": "A token, which can be sent as ListSessionsRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages." }, "sessions": { "type": "array", "description": "A list of sessions matching the request.", "items": { "$ref": "GoogleCloudAiplatformV1Session" } } }, "type": "object" }, "GoogleCloudAiplatformV1PSCAutomationConfig": { "description": "PSC config that is used to automatically create PSC endpoints in the user projects.", "id": "GoogleCloudAiplatformV1PSCAutomationConfig", "properties": { "projectId": { "type": "string", "description": "Required. Project id used to create forwarding rule." }, "ipAddress": { "description": "Output only. IP address rule created by the PSC service automation.", "type": "string", "readOnly": true }, "state": { "type": "string", "description": "Output only. The state of the PSC service automation.", "readOnly": true, "enum": [ "PSC_AUTOMATION_STATE_UNSPECIFIED", "PSC_AUTOMATION_STATE_SUCCESSFUL", "PSC_AUTOMATION_STATE_FAILED" ], "enumDescriptions": [ "Should not be used.", "The PSC service automation is successful.", "The PSC service automation has failed." ] }, "forwardingRule": { "type": "string", "description": "Output only. Forwarding rule created by the PSC service automation.", "readOnly": true }, "errorMessage": { "type": "string", "description": "Output only. Error message if the PSC service automation failed.", "readOnly": true }, "network": { "type": "string", "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": "object" }, "GoogleCloudAiplatformV1DatasetVersion": { "properties": { "name": { "readOnly": true, "description": "Output only. Identifier. The resource name of the DatasetVersion. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "type": "string" }, "createTime": { "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when this DatasetVersion was created.", "readOnly": true }, "modelReference": { "type": "string", "readOnly": true, "description": "Output only. Reference to the public base model last used by the dataset version. Only set for prompt dataset versions." }, "metadata": { "type": "any", "description": "Required. Output only. Additional information about the DatasetVersion.", "readOnly": true }, "bigQueryDatasetName": { "readOnly": true, "type": "string", "description": "Output only. Name of the associated BigQuery dataset." }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "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" }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this DatasetVersion was last updated.", "readOnly": true, "type": "string" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" } }, "description": "Describes the dataset version.", "id": "GoogleCloudAiplatformV1DatasetVersion", "type": "object" }, "GoogleCloudAiplatformV1AsyncRetrieveContextsRequest": { "type": "object", "description": "Request message for VertexRagService.AsyncRetrieveContexts.", "properties": { "query": { "$ref": "GoogleCloudAiplatformV1RagQuery", "description": "Required. Single RAG retrieve query." }, "tools": { "items": { "$ref": "GoogleCloudAiplatformV1Tool" }, "description": "Optional. The tools to use for AskContexts.", "type": "array" } }, "id": "GoogleCloudAiplatformV1AsyncRetrieveContextsRequest" }, "GenaiVertexV1TextAnnotationDelta": { "properties": { "annotations": { "items": { "$ref": "GenaiVertexV1TextContentAnnotation" }, "description": "Citation information for model-generated content.", "type": "array" } }, "type": "object", "id": "GenaiVertexV1TextAnnotationDelta" }, "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfig": { "description": "OnlineServingConfig specifies the details for provisioning online serving resources.", "id": "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfig", "type": "object", "properties": { "scaling": { "description": "Online serving scaling configuration. Only one of `fixed_node_count` and `scaling` can be set. Setting one will reset the other.", "$ref": "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScaling" }, "fixedNodeCount": { "type": "integer", "format": "int32", "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." } } }, "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsRequest": { "type": "object", "description": "Request message for MetadataService.AddContextArtifactsAndExecutions.", "id": "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsRequest", "properties": { "artifacts": { "description": "The resource names of the Artifacts to attribute to the Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`", "items": { "type": "string" }, "type": "array" }, "executions": { "type": "array", "items": { "type": "string" }, "description": "The resource names of the Executions to associate with the Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`" } } }, "GoogleCloudAiplatformV1ActiveLearningConfig": { "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.", "id": "GoogleCloudAiplatformV1ActiveLearningConfig", "type": "object", "properties": { "maxDataItemCount": { "type": "string", "description": "Max number of human labeled DataItems.", "format": "int64" }, "maxDataItemPercentage": { "description": "Max percent of total DataItems for human labeling.", "type": "integer", "format": "int32" }, "trainingConfig": { "$ref": "GoogleCloudAiplatformV1TrainingConfig", "description": "CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems." }, "sampleConfig": { "description": "Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.", "$ref": "GoogleCloudAiplatformV1SampleConfig" } } }, "GoogleCloudAiplatformV1RougeMetricValue": { "type": "object", "id": "GoogleCloudAiplatformV1RougeMetricValue", "description": "Rouge metric value for an instance.", "properties": { "score": { "description": "Output only. Rouge score.", "type": "number", "format": "float", "readOnly": true } } }, "GoogleCloudAiplatformV1GcsSource": { "properties": { "uris": { "type": "array", "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.", "items": { "type": "string" } } }, "description": "The Google Cloud Storage location for the input content.", "id": "GoogleCloudAiplatformV1GcsSource", "type": "object" }, "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentConfig": { "id": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentConfig", "properties": { "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" }, "subAgents": { "items": { "type": "string" }, "type": "array", "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." }, "tools": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentConfigTools", "description": "List of tools." }, "toolsText": { "description": "A JSON string containing a list of tools available to an agent with info such as name, description, parameters and required parameters.", "type": "string" }, "description": { "description": "Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.", "type": "string" }, "agentId": { "description": "Optional. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.", "type": "string" }, "developerInstruction": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceInstanceData", "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." } }, "description": "Deprecated: Use `google.cloud.aiplatform.master.AgentConfig` in `agent_eval_data` instead. Configuration for an Agent.", "deprecated": true, "type": "object" }, "GoogleCloudAiplatformV1UpdateFeatureGroupOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Operation metadata for FeatureGroup." } }, "id": "GoogleCloudAiplatformV1UpdateFeatureGroupOperationMetadata", "type": "object", "description": "Details of operations that perform update FeatureGroup." }, "CloudAiLargeModelsVisionImageImageSize": { "id": "CloudAiLargeModelsVisionImageImageSize", "type": "object", "description": "Image size.", "properties": { "channels": { "type": "integer", "format": "int32" }, "width": { "format": "int32", "type": "integer" }, "height": { "type": "integer", "format": "int32" } } }, "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservability": { "id": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservability", "properties": { "sessionScope": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilitySessionScope", "description": "Scope online evaluation to OTel sessions (i.e. group of traces with the same conversation ID)." }, "traceScope": { "description": "Scope online evaluation to single traces.", "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityTraceScope" }, "traceView": { "description": "Optional. Optional trace view that will be used to query traces. If empty, the `_AllSpans` view from `_Trace` US bucket will be used, i.e. `projects/{project_id}/locations/us/buckets/_Trace/datasets/Spans/views/_AllSpans`.", "type": "string" }, "logView": { "description": "Optional. Optional log view that will be used to query logs. If empty, the project's default view (`projects/{project_id}`) will be used.", "type": "string" }, "openTelemetry": { "description": "Data source follows OpenTelemetry convention.", "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityOpenTelemetry" } }, "type": "object", "description": "Data source for the OnlineEvaluator, based on Google Cloud Observability stack (Cloud Trace & Cloud Logging)." }, "GenaiVertexV1RetrievalResultDelta": { "type": "object", "properties": { "isError": { "type": "boolean", "description": "Whether the retrieval resulted in an error." } }, "description": "Used by Vertex Retrieval tools such as Parallel AI, Exa AI, Vertex AI Search, etc. ToolResultDelta.type", "id": "GenaiVertexV1RetrievalResultDelta" }, "GoogleCloudAiplatformV1EvaluationRunInferenceConfigSessionInput": { "type": "object", "id": "GoogleCloudAiplatformV1EvaluationRunInferenceConfigSessionInput", "properties": { "userId": { "description": "Optional. The user id for the agent session. The ID can be up to 128 characters long.", "type": "string" }, "parameters": { "description": "Optional. Additional parameters for the session, like app_name, etc. For example, {\"app_name\": \"my-app\"}.", "additionalProperties": { "type": "string" }, "type": "object" }, "sessionState": { "description": "Optional. Session specific memory which stores key conversation points.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "description": "Session input to run an Agent." }, "GoogleCloudAiplatformV1PartMediaResolution": { "id": "GoogleCloudAiplatformV1PartMediaResolution", "properties": { "level": { "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": "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" } }, "description": "per part media resolution. Media resolution for the input media.", "type": "object" }, "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestPassThroughField": { "description": "Describe pass-through fields in read_instance source.", "type": "object", "id": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestPassThroughField", "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" } } }, "GoogleCloudAiplatformV1WriteFeatureValuesResponse": { "description": "Response message for FeaturestoreOnlineServingService.WriteFeatureValues.", "id": "GoogleCloudAiplatformV1WriteFeatureValuesResponse", "properties": {}, "type": "object" }, "GoogleCloudAiplatformV1FilterSplit": { "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. ", "id": "GoogleCloudAiplatformV1FilterSplit", "type": "object", "properties": { "trainingFilter": { "type": "string", "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." }, "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" }, "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" } } }, "GoogleCloudAiplatformV1TensorboardExperiment": { "type": "object", "properties": { "createTime": { "readOnly": true, "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when this TensorboardExperiment was created." }, "name": { "readOnly": true, "type": "string", "description": "Output only. Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`" }, "updateTime": { "type": "string", "format": "google-datetime", "readOnly": true, "description": "Output only. Timestamp when this TensorboardExperiment was last updated." }, "labels": { "type": "object", "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.", "additionalProperties": { "type": "string" } }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "displayName": { "description": "User provided name of this TensorboardExperiment.", "type": "string" }, "description": { "description": "Description of this TensorboardExperiment.", "type": "string" }, "source": { "type": "string", "description": "Immutable. Source of the TensorboardExperiment. Example: a custom training job." } }, "description": "A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard.", "id": "GoogleCloudAiplatformV1TensorboardExperiment" }, "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInstance": { "id": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInstance", "type": "object", "properties": { "reference": { "type": "string", "description": "Optional. Ground truth used to compare against the prediction." }, "context": { "type": "string", "description": "Optional. Text provided as context to answer the question." }, "prediction": { "type": "string", "description": "Required. Output of the evaluated model." }, "instruction": { "type": "string", "description": "Required. The question asked and other instruction in the inference prompt." } }, "description": "Spec for question answering relevance instance." }, "GoogleCloudAiplatformV1AudioTranscriptionConfig": { "description": "Configuration for speech recognition (transcription).", "id": "GoogleCloudAiplatformV1AudioTranscriptionConfig", "type": "object", "properties": { "wordTimestamp": { "type": "boolean", "description": "Optional. Configures word-level timestamp generation." }, "languageCodes": { "items": { "type": "string" }, "description": "Optional. BCP-47 language codes providing hints about the languages present in the audio. If omitted or empty, defaults to automatic language detection.", "type": "array" }, "mode": { "enumDescriptions": [ "Unspecified transcription mode.", "Verbatim transcription mode.", "Smart transcription mode." ], "description": "Optional. Configures transcription mode. Supported values: `VERBATIM`, `SMART`. If unspecified, defaults to `VERBATIM` transcription. In `SMART` mode, the model performs disfluency removal (eliminating filler words, repetitions, and false starts), light grammatical cleanup, automatic formatting (paragraphs, bullet points, numbered lists), and minor user edits (inline self-corrections). Timestamps and diarization are incompatible with mode `SMART`.", "type": "string", "enum": [ "MODE_UNSPECIFIED", "VERBATIM", "SMART" ] }, "diarization": { "description": "Optional. Configures speaker diarization.", "type": "boolean" }, "languageAuto": { "$ref": "GoogleCloudAiplatformV1AudioTranscriptionConfigLanguageAuto", "description": "Optional. Deprecated: Use top-level `language_codes` instead. The model will detect the language automatically.", "deprecated": true }, "adaptationPhrases": { "type": "array", "description": "Optional. Deprecated: Use `custom_vocabulary` instead. A list of phrases to bias the speech recognition model towards.", "items": { "type": "string" }, "deprecated": true }, "customVocabulary": { "type": "array", "items": { "type": "string" }, "description": "Optional. A list of custom vocabulary phrases to bias the speech recognition model toward recognizing specific terms." }, "languageHints": { "description": "Optional. Deprecated: Use top-level `language_codes` instead. Specifies one or more languages in the audio.", "$ref": "GoogleCloudAiplatformV1AudioTranscriptionConfigLanguageHints", "deprecated": true } } }, "GenaiVertexV1RagStoreConfigRagRetrievalConfigRankingRankService": { "type": "object", "id": "GenaiVertexV1RagStoreConfigRagRetrievalConfigRankingRankService", "properties": { "modelName": { "type": "string", "description": "Optional. The model name of the rank service." } }, "description": "Config for Rank Service." }, "GoogleCloudAiplatformV1IdMatcher": { "properties": { "ids": { "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.", "items": { "type": "string" }, "type": "array" } }, "description": "Matcher for Features of an EntityType by Feature ID.", "type": "object", "id": "GoogleCloudAiplatformV1IdMatcher" }, "GoogleCloudAiplatformV1SpecialistPool": { "id": "GoogleCloudAiplatformV1SpecialistPool", "type": "object", "properties": { "specialistManagersCount": { "format": "int32", "type": "integer", "readOnly": true, "description": "Output only. The number of managers in this SpecialistPool." }, "specialistManagerEmails": { "type": "array", "description": "The email addresses of the managers in the SpecialistPool.", "items": { "type": "string" } }, "specialistWorkerEmails": { "description": "The email addresses of workers in the SpecialistPool.", "items": { "type": "string" }, "type": "array" }, "displayName": { "type": "string", "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." }, "pendingDataLabelingJobs": { "items": { "type": "string" }, "readOnly": true, "description": "Output only. The resource name of the pending data labeling jobs.", "type": "array" }, "name": { "description": "Required. The resource name of the SpecialistPool.", "type": "string" } }, "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." }, "GenaiVertexV1GoogleMapsResultStepGoogleMapsResultItem": { "id": "GenaiVertexV1GoogleMapsResultStepGoogleMapsResultItem", "description": "The result of the Google Maps.", "type": "object", "properties": { "places": { "type": "array", "items": { "$ref": "GenaiVertexV1GoogleMapsResultStepGoogleMapsResultItemGoogleMapsResultPlaces" } }, "widgetContextToken": { "type": "string" } } }, "GoogleCloudAiplatformV1AuthConfigHttpBasicAuthConfig": { "type": "object", "id": "GoogleCloudAiplatformV1AuthConfigHttpBasicAuthConfig", "properties": { "credentialSecret": { "description": "Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.", "type": "string" } }, "description": "Config for HTTP Basic Authentication." }, "GoogleCloudAiplatformV1ListAgentsResponse": { "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass this value as ListAgentsRequest.page_token in a subsequent call.", "type": "string" }, "agents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Agent" }, "description": "The agents matching the request." } }, "description": "Response message for AgentService.ListAgents.", "type": "object", "id": "GoogleCloudAiplatformV1ListAgentsResponse" }, "GoogleCloudAiplatformV1SchemaImageBoundingBoxAnnotation": { "type": "object", "properties": { "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "xMin": { "format": "double", "type": "number", "description": "The leftmost coordinate of the bounding box." }, "yMax": { "description": "The bottommost coordinate of the bounding box.", "format": "double", "type": "number" }, "xMax": { "format": "double", "description": "The rightmost coordinate of the bounding box.", "type": "number" }, "yMin": { "type": "number", "description": "The topmost coordinate of the bounding box.", "format": "double" }, "annotationSpecId": { "type": "string", "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." } }, "id": "GoogleCloudAiplatformV1SchemaImageBoundingBoxAnnotation", "description": "Annotation details specific to image object detection." }, "GoogleApiHttpBody": { "properties": { "data": { "format": "byte", "type": "string", "description": "The HTTP request/response body as raw binary." }, "extensions": { "type": "array", "description": "Application specific response metadata. Must be set in the first response for streaming APIs.", "items": { "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." }, "type": "object" } }, "contentType": { "description": "The HTTP Content-Type header value specifying the content type of the body.", "type": "string" } }, "id": "GoogleApiHttpBody", "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.", "type": "object" }, "GoogleCloudAiplatformV1QuestionAnsweringQualityInstance": { "description": "Spec for question answering quality instance.", "type": "object", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "context": { "description": "Required. Text to answer the question.", "type": "string" }, "instruction": { "description": "Required. Question Answering prompt for LLM.", "type": "string" }, "reference": { "type": "string", "description": "Optional. Ground truth used to compare against the prediction." } }, "id": "GoogleCloudAiplatformV1QuestionAnsweringQualityInstance" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity": { "type": "object", "properties": { "unit": { "type": "string", "description": "The time granularity unit of this time period. The supported units are: * \"minute\" * \"hour\" * \"day\" * \"week\" * \"month\" * \"year\"" }, "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.", "type": "string", "format": "int64" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity", "description": "A duration of time expressed in time granularity units." }, "GoogleCloudAiplatformV1ModelDataStats": { "id": "GoogleCloudAiplatformV1ModelDataStats", "description": "Stats of data used for train or evaluate the Model.", "properties": { "trainingDataItemsCount": { "format": "int64", "type": "string", "description": "Number of DataItems that were used for training this Model." }, "testAnnotationsCount": { "description": "Number of Annotations that are used for evaluating this Model. If the Model is evaluated multiple times, this will be the number of test Annotations used by the first evaluation. If the Model is not evaluated, the number is 0.", "format": "int64", "type": "string" }, "validationDataItemsCount": { "type": "string", "description": "Number of DataItems that were used for validating this Model during training.", "format": "int64" }, "validationAnnotationsCount": { "type": "string", "format": "int64", "description": "Number of Annotations that are used for validating this Model during training." }, "testDataItemsCount": { "description": "Number of DataItems that were used for evaluating this Model. If the Model is evaluated multiple times, this will be the number of test DataItems used by the first evaluation. If the Model is not evaluated, the number is 0.", "type": "string", "format": "int64" }, "trainingAnnotationsCount": { "description": "Number of Annotations that are used for training this Model.", "type": "string", "format": "int64" } }, "type": "object" }, "GoogleCloudAiplatformV1MetadataSchema": { "id": "GoogleCloudAiplatformV1MetadataSchema", "properties": { "schema": { "type": "string", "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)" }, "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" }, "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." ] }, "createTime": { "readOnly": true, "description": "Output only. Timestamp when this MetadataSchema was created.", "type": "string", "format": "google-datetime" }, "description": { "type": "string", "description": "Description of the Metadata Schema" }, "name": { "description": "Output only. The resource name of the MetadataSchema.", "type": "string", "readOnly": true } }, "description": "Instance of a general MetadataSchema.", "type": "object" }, "GoogleCloudAiplatformV1SchemaPredictInstanceVideoObjectTrackingPredictionInstance": { "id": "GoogleCloudAiplatformV1SchemaPredictInstanceVideoObjectTrackingPredictionInstance", "description": "Prediction input format for Video Object Tracking.", "type": "object", "properties": { "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" }, "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" }, "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" } } }, "GoogleCloudAiplatformV1TrajectoryRecallInstance": { "type": "object", "id": "GoogleCloudAiplatformV1TrajectoryRecallInstance", "properties": { "predictedTrajectory": { "$ref": "GoogleCloudAiplatformV1Trajectory", "description": "Required. Spec for predicted tool call trajectory." }, "referenceTrajectory": { "$ref": "GoogleCloudAiplatformV1Trajectory", "description": "Required. Spec for reference tool call trajectory." } }, "description": "Spec for TrajectoryRecall instance." }, "GoogleCloudAiplatformV1QuestionAnsweringQualityInput": { "type": "object", "description": "Input for question answering quality metric.", "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1QuestionAnsweringQualityInstance", "description": "Required. Question answering quality instance." }, "metricSpec": { "description": "Required. Spec for question answering quality score metric.", "$ref": "GoogleCloudAiplatformV1QuestionAnsweringQualitySpec" } }, "id": "GoogleCloudAiplatformV1QuestionAnsweringQualityInput" }, "GenaiVertexV1GenerationConfig": { "type": "object", "description": "Configuration parameters for model interactions.", "properties": { "maxOutputTokens": { "format": "int32", "description": "The maximum number of tokens to include in the response.", "type": "integer" }, "topP": { "format": "float", "type": "number", "description": "The maximum cumulative probability of tokens to consider when sampling.", "deprecated": true }, "thinkingSummaries": { "type": "string", "enum": [ "THINKING_SUMMARIES_UNSPECIFIED", "THINKING_SUMMARIES_AUTO", "THINKING_SUMMARIES_NONE" ], "enumDescriptions": [ "Default value. This value is unused.", "Auto thinking summaries.", "No thinking summaries." ], "description": "Whether to include thought summaries in the response." }, "videoConfig": { "description": "Configuration for video generation.", "$ref": "GenaiVertexV1VideoConfig" }, "seed": { "format": "int32", "type": "integer", "description": "Seed used in decoding for reproducibility." }, "transcriptionConfig": { "description": "Optional. Configuration for speech recognition (transcription). If present, ASR is enabled.", "$ref": "GenaiVertexV1TranscriptionConfig" }, "temperature": { "deprecated": true, "format": "float", "description": "Controls the randomness of the output.", "type": "number" }, "toolChoiceConfig": { "description": "The config for the tool choice.", "$ref": "GenaiVertexV1ToolChoiceConfig" }, "toolChoiceMode": { "type": "string", "description": "The mode of the tool choice.", "enum": [ "TOOL_CHOICE_TYPE_UNSPECIFIED", "AUTO", "ANY", "NONE", "VALIDATED" ], "enumDescriptions": [ "Default value. This value is unused.", "Auto tool choice.", "Any tool choice.", "No tool choice.", "Validated tool choice." ] }, "structuredSpeechConfig": { "$ref": "GenaiVertexV1SpeakerConfig", "description": "Speech and multi-speaker configuration." }, "stopSequences": { "description": "A list of character sequences that will stop output interaction.", "items": { "type": "string" }, "type": "array" }, "thinkingLevel": { "description": "The level of thought tokens that the model should generate.", "enum": [ "THINKING_LEVEL_UNSPECIFIED", "THINKING_LEVEL_MINIMAL", "THINKING_LEVEL_LOW", "THINKING_LEVEL_MEDIUM", "THINKING_LEVEL_HIGH" ], "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "Little to no thinking.", "Low thinking level.", "Medium thinking level.", "High thinking level." ] } }, "id": "GenaiVertexV1GenerationConfig" }, "CloudAiLargeModelsVisionRaiInfoDetectedLabels": { "description": "Filters returning list of deteceted labels, scores, and bounding boxes.", "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabels", "properties": { "raiCategory": { "description": "The RAI category for the deteceted labels.", "type": "string" }, "entities": { "description": "The list of detected entities for the rai signal.", "type": "array", "items": { "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity" } } }, "type": "object" }, "CloudAiPlatformCommonCreatePipelineJobApiErrorDetail": { "id": "CloudAiPlatformCommonCreatePipelineJobApiErrorDetail", "description": "Create API error message for Vertex Pipeline.", "type": "object", "properties": { "errorCause": { "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" ], "type": "string" }, "publicMessage": { "type": "string", "description": "Public messages contains actionable items for the error cause." } } }, "GoogleCloudAiplatformV1UndeployIndexOperationMetadata": { "type": "object", "id": "GoogleCloudAiplatformV1UndeployIndexOperationMetadata", "description": "Runtime operation information for IndexEndpointService.UndeployIndex.", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1ExportDataConfig": { "description": "Describes what part of the Dataset is to be exported, the destination of the export and how to export.", "properties": { "gcsDestination": { "$ref": "GoogleCloudAiplatformV1GcsDestination", "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." }, "annotationSchemaUri": { "description": "The 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 ExportDataRequest.name. Only used for custom training data export use cases. Only applicable to Datasets that have DataItems and Annotations. 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" }, "filterSplit": { "description": "Split based on the provided filters for each set.", "$ref": "GoogleCloudAiplatformV1ExportFilterSplit" }, "savedQueryId": { "description": "The ID of a SavedQuery (annotation set) under the Dataset specified by ExportDataRequest.name used for filtering Annotations for training. Only used for custom training data export use cases. Only applicable to Datasets that have SavedQueries. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.", "type": "string" }, "annotationsFilter": { "description": "An expression for filtering what part of the Dataset is to be exported. Only Annotations that match this filter will be exported. The filter syntax is the same as in ListAnnotations.", "type": "string" }, "exportUse": { "enum": [ "EXPORT_USE_UNSPECIFIED", "CUSTOM_CODE_TRAINING" ], "type": "string", "enumDescriptions": [ "Regular user export.", "Export for custom code training." ], "description": "Indicates the usage of the exported files." }, "fractionSplit": { "description": "Split based on fractions defining the size of each set.", "$ref": "GoogleCloudAiplatformV1ExportFractionSplit" } }, "id": "GoogleCloudAiplatformV1ExportDataConfig", "type": "object" }, "GoogleCloudAiplatformV1ComputationBasedMetricSpec": { "properties": { "type": { "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." ], "description": "Required. The type of the computation based metric." }, "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." } } }, "id": "GoogleCloudAiplatformV1ComputationBasedMetricSpec", "type": "object", "description": "Specification for a computation based metric." }, "CloudAiLargeModelsVisionGenerateVideoResponse": { "properties": { "videos": { "description": "List of videos, used to align naming with the external response.", "type": "array", "items": { "$ref": "CloudAiLargeModelsVisionGenerateVideoResponseVideo" } }, "raiMediaFilteredReasons": { "description": "Returns rai failure reasons if any.", "items": { "type": "string" }, "type": "array" }, "generatedSamples": { "type": "array", "description": "The generates samples.", "items": { "$ref": "CloudAiLargeModelsVisionMedia" } }, "raiMediaFilteredCount": { "format": "int32", "description": "Returns if any videos were filtered due to RAI policies.", "type": "integer" } }, "id": "CloudAiLargeModelsVisionGenerateVideoResponse", "type": "object", "description": "Generate video response." }, "GoogleCloudAiplatformV1ReservationAffinity": { "properties": { "key": { "type": "string", "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." }, "reservationAffinityType": { "type": "string", "enum": [ "TYPE_UNSPECIFIED", "NO_RESERVATION", "ANY_RESERVATION", "SPECIFIC_RESERVATION" ], "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." ], "description": "Required. Specifies the reservation affinity type." }, "values": { "items": { "type": "string" }, "description": "Optional. Corresponds to the label values of a reservation resource. This must be the resource name of the reservation, reservation block, or reservation sub- block.", "type": "array" } }, "id": "GoogleCloudAiplatformV1ReservationAffinity", "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.", "type": "object" }, "GenaiVertexV1ToolChoiceConfig": { "description": "The tool choice configuration containing allowed tools.", "properties": { "allowedTools": { "description": "The allowed tools.", "$ref": "GenaiVertexV1AllowedTools" } }, "id": "GenaiVertexV1ToolChoiceConfig", "type": "object" }, "GoogleCloudAiplatformV1EvaluateInstancesResponse": { "description": "Response message for EvaluationService.EvaluateInstances.", "properties": { "trajectoryPrecisionResults": { "$ref": "GoogleCloudAiplatformV1TrajectoryPrecisionResults", "description": "Result for trajectory precision metric." }, "questionAnsweringQualityResult": { "description": "Question answering only metrics. Result for question answering quality metric.", "$ref": "GoogleCloudAiplatformV1QuestionAnsweringQualityResult" }, "groundednessResult": { "$ref": "GoogleCloudAiplatformV1GroundednessResult", "description": "Result for groundedness metric." }, "safetyResult": { "$ref": "GoogleCloudAiplatformV1SafetyResult", "description": "Result for safety metric." }, "summarizationHelpfulnessResult": { "$ref": "GoogleCloudAiplatformV1SummarizationHelpfulnessResult", "description": "Result for summarization helpfulness metric." }, "metricxResult": { "description": "Result for Metricx metric.", "$ref": "GoogleCloudAiplatformV1MetricxResult" }, "pairwiseMetricResult": { "description": "Result for pairwise metric.", "$ref": "GoogleCloudAiplatformV1PairwiseMetricResult" }, "trajectorySingleToolUseResults": { "$ref": "GoogleCloudAiplatformV1TrajectorySingleToolUseResults", "description": "Results for trajectory single tool use metric." }, "trajectoryInOrderMatchResults": { "$ref": "GoogleCloudAiplatformV1TrajectoryInOrderMatchResults", "description": "Result for trajectory in order match metric." }, "pointwiseMetricResult": { "description": "Generic metrics. Result for pointwise metric.", "$ref": "GoogleCloudAiplatformV1PointwiseMetricResult" }, "fluencyResult": { "description": "LLM-based metric evaluation result. General text generation metrics, applicable to other categories. Result for fluency metric.", "$ref": "GoogleCloudAiplatformV1FluencyResult" }, "toolParameterKeyMatchResults": { "$ref": "GoogleCloudAiplatformV1ToolParameterKeyMatchResults", "description": "Results for tool parameter key match metric." }, "trajectoryRecallResults": { "$ref": "GoogleCloudAiplatformV1TrajectoryRecallResults", "description": "Results for trajectory recall metric." }, "questionAnsweringRelevanceResult": { "description": "Result for question answering relevance metric.", "$ref": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceResult" }, "summarizationVerbosityResult": { "description": "Result for summarization verbosity metric.", "$ref": "GoogleCloudAiplatformV1SummarizationVerbosityResult" }, "coherenceResult": { "description": "Result for coherence metric.", "$ref": "GoogleCloudAiplatformV1CoherenceResult" }, "metricResults": { "items": { "$ref": "GoogleCloudAiplatformV1MetricResult" }, "type": "array", "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." }, "trajectoryExactMatchResults": { "$ref": "GoogleCloudAiplatformV1TrajectoryExactMatchResults", "description": "Result for trajectory exact match metric." }, "fulfillmentResult": { "$ref": "GoogleCloudAiplatformV1FulfillmentResult", "description": "Result for fulfillment metric." }, "bleuResults": { "description": "Results for bleu metric.", "$ref": "GoogleCloudAiplatformV1BleuResults" }, "cometResult": { "$ref": "GoogleCloudAiplatformV1CometResult", "description": "Translation metrics. Result for Comet metric." }, "toolNameMatchResults": { "description": "Results for tool name match metric.", "$ref": "GoogleCloudAiplatformV1ToolNameMatchResults" }, "rougeResults": { "$ref": "GoogleCloudAiplatformV1RougeResults", "description": "Results for rouge metric." }, "pairwiseSummarizationQualityResult": { "description": "Result for pairwise summarization quality metric.", "$ref": "GoogleCloudAiplatformV1PairwiseSummarizationQualityResult" }, "questionAnsweringCorrectnessResult": { "description": "Result for question answering correctness metric.", "$ref": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessResult" }, "exactMatchResults": { "description": "Auto metric evaluation results. Results for exact match metric.", "$ref": "GoogleCloudAiplatformV1ExactMatchResults" }, "summarizationQualityResult": { "description": "Summarization only metrics. Result for summarization quality metric.", "$ref": "GoogleCloudAiplatformV1SummarizationQualityResult" }, "toolCallValidResults": { "description": "Tool call metrics. Results for tool call valid metric.", "$ref": "GoogleCloudAiplatformV1ToolCallValidResults" }, "questionAnsweringHelpfulnessResult": { "description": "Result for question answering helpfulness metric.", "$ref": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessResult" }, "trajectoryAnyOrderMatchResults": { "$ref": "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchResults", "description": "Result for trajectory any order match metric." }, "toolParameterKvMatchResults": { "$ref": "GoogleCloudAiplatformV1ToolParameterKVMatchResults", "description": "Results for tool parameter key value match metric." }, "pairwiseQuestionAnsweringQualityResult": { "description": "Result for pairwise question answering quality metric.", "$ref": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityResult" }, "rubricBasedInstructionFollowingResult": { "description": "Result for rubric based instruction following metric.", "$ref": "GoogleCloudAiplatformV1RubricBasedInstructionFollowingResult" } }, "type": "object", "id": "GoogleCloudAiplatformV1EvaluateInstancesResponse" }, "CloudAiLargeModelsVisionGenerateVideoExperimentsLoraConfigAdapter": { "type": "object", "properties": { "id": { "description": "The registered ID of the LoRA adapter (e.g. \"lora_xxx\").", "type": "string" }, "weight": { "format": "float", "description": "The blending scale/weight of the LoRA adapter. Must be in the range (0.0, 1.0]. Default is 1.0.", "type": "number" }, "resolvedPath": { "description": "Internal field populated after validation: resolved TFHub path.", "type": "string" } }, "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsLoraConfigAdapter" }, "GoogleCloudAiplatformV1AsyncQueryReasoningEngineRequest": { "properties": { "outputGcsUri": { "type": "string", "description": "Optional. Output Cloud Storage URI for the Async query. This contains the final response of the query." }, "inputGcsUri": { "type": "string", "description": "Optional. Input Cloud Storage URI for the Async query. If you are not bringing your own container (BYOC), the content of the file should be a JSON object with an `input` field matching the `input` field of `QueryReasoningEngineRequest` (e.g. `{ \"input\": { \"user_id\": \"hello\", \"message\":\"$QUERY\"} }`). For BYOC, the content of the file depends on the the agent application." } }, "description": "Request message for ReasoningEngineExecutionService.AsyncQueryReasoningEngine.", "type": "object", "id": "GoogleCloudAiplatformV1AsyncQueryReasoningEngineRequest" }, "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataInputConfig": { "id": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataInputConfig", "description": "The time series Dataset's data source. The Dataset doesn't store the data directly, but only pointer(s) to its data.", "properties": { "bigquerySource": { "$ref": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataBigQuerySource" }, "gcsSource": { "$ref": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataGcsSource" } }, "type": "object" }, "GenaiVertexV1RetrievalCallStepRetrievalStepArguments": { "type": "object", "id": "GenaiVertexV1RetrievalCallStepRetrievalStepArguments", "description": "The arguments to pass to Retrieval tools.", "properties": { "queries": { "description": "Queries for Retrieval information.", "items": { "type": "string" }, "type": "array" } } }, "GenaiVertexV1AntigravityAgentConfig": { "properties": { "maxTotalTokens": { "description": "Max total tokens for the agent run.", "format": "int64", "type": "string" }, "model": { "description": "The model to use for agent reasoning.", "type": "string" } }, "type": "object", "description": "Configuration for the Antigravity agent runtime. Provides server-side control over the agent's execution environment and tool configuration.", "id": "GenaiVertexV1AntigravityAgentConfig" }, "GoogleCloudAiplatformV1BatchCreateTensorboardRunsRequest": { "description": "Request message for TensorboardService.BatchCreateTensorboardRuns.", "properties": { "requests": { "items": { "$ref": "GoogleCloudAiplatformV1CreateTensorboardRunRequest" }, "description": "Required. The request message specifying the TensorboardRuns to create. A maximum of 1000 TensorboardRuns can be created in a batch.", "type": "array" } }, "type": "object", "id": "GoogleCloudAiplatformV1BatchCreateTensorboardRunsRequest" }, "GoogleCloudAiplatformV1FetchFeatureValuesResponse": { "properties": { "dataKey": { "description": "The data key associated with this response. Will only be populated for FeatureOnlineStoreService.StreamingFetchFeatureValues RPCs.", "$ref": "GoogleCloudAiplatformV1FeatureViewDataKey" }, "protoStruct": { "type": "object", "description": "Feature values in proto Struct format.", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "keyValues": { "description": "Feature values in KeyValue format.", "$ref": "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairList" } }, "type": "object", "description": "Response message for FeatureOnlineStoreService.FetchFeatureValues", "id": "GoogleCloudAiplatformV1FetchFeatureValuesResponse" }, "GoogleCloudAiplatformV1BatchCreateFeaturesOperationMetadata": { "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Operation metadata for Feature." } }, "id": "GoogleCloudAiplatformV1BatchCreateFeaturesOperationMetadata", "description": "Details of operations that perform batch create Features." }, "GoogleCloudAiplatformV1Study": { "type": "object", "id": "GoogleCloudAiplatformV1Study", "description": "A message representing a Study.", "properties": { "name": { "description": "Output only. The name of a study. The study's globally unique identifier. Format: `projects/{project}/locations/{location}/studies/{study}`", "readOnly": true, "type": "string" }, "createTime": { "description": "Output only. Time at which the study was created.", "type": "string", "readOnly": true, "format": "google-datetime" }, "inactiveReason": { "description": "Output only. A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.", "readOnly": true, "type": "string" }, "displayName": { "type": "string", "description": "Required. Describes the Study, default value is empty string." }, "state": { "readOnly": true, "description": "Output only. The detailed state of a Study.", "enumDescriptions": [ "The study state is unspecified.", "The study is active.", "The study is stopped due to an internal error.", "The study is done when the service exhausts the parameter search space or max_trial_count is reached." ], "type": "string", "enum": [ "STATE_UNSPECIFIED", "ACTIVE", "INACTIVE", "COMPLETED" ] }, "studySpec": { "description": "Required. Configuration of the Study.", "$ref": "GoogleCloudAiplatformV1StudySpec" } } }, "GoogleCloudAiplatformV1ToolGoogleSearch": { "description": "GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.", "type": "object", "properties": { "blockingConfidence": { "description": "Optional. Sites with confidence level chosen & above this value will be blocked from the search results.", "type": "string", "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" ], "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." ] }, "excludeDomains": { "description": "Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: [\"amazon.com\", \"facebook.com\"].", "items": { "type": "string" }, "type": "array" }, "searchTypes": { "$ref": "GoogleCloudAiplatformV1ToolGoogleSearchSearchTypes", "description": "Optional. The set of search types to enable. If not set, web search is enabled by default." } }, "id": "GoogleCloudAiplatformV1ToolGoogleSearch" }, "GenaiVertexV1StepStop": { "properties": { "index": { "format": "int32", "type": "integer" }, "usage": { "description": "Cumulative model usage stats from the start of the session.", "$ref": "GenaiVertexV1InteractionUsage" }, "stepUsage": { "$ref": "GenaiVertexV1InteractionUsage", "description": "Model usage stats for this specific step." } }, "type": "object", "id": "GenaiVertexV1StepStop" }, "GoogleCloudAiplatformV1PauseModelDeploymentMonitoringJobRequest": { "id": "GoogleCloudAiplatformV1PauseModelDeploymentMonitoringJobRequest", "description": "Request message for JobService.PauseModelDeploymentMonitoringJob.", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1FeatureMonitoringStatsAnomaly": { "properties": { "featureStatsAnomaly": { "description": "Output only. The stats and anomalies generated at specific timestamp.", "$ref": "GoogleCloudAiplatformV1FeatureStatsAnomaly", "readOnly": true }, "objective": { "enum": [ "OBJECTIVE_UNSPECIFIED", "IMPORT_FEATURE_ANALYSIS", "SNAPSHOT_ANALYSIS" ], "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." ], "description": "Output only. The objective for each stats.", "readOnly": true } }, "type": "object", "description": "A list of historical SnapshotAnalysis or ImportFeaturesAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending.", "id": "GoogleCloudAiplatformV1FeatureMonitoringStatsAnomaly" }, "GoogleCloudAiplatformV1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet": { "id": "GoogleCloudAiplatformV1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet", "type": "object", "properties": { "title": { "description": "The title of the review.", "type": "string" }, "reviewId": { "description": "The ID of the review that is being referenced.", "type": "string" }, "googleMapsUri": { "type": "string", "description": "A link to show the review on Google Maps." } }, "description": "A review snippet that is used to generate the answer." }, "GoogleCloudAiplatformV1SpeculativeDecodingSpecNgramSpeculation": { "id": "GoogleCloudAiplatformV1SpeculativeDecodingSpecNgramSpeculation", "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." } }, "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." }, "GoogleCloudAiplatformV1SandboxEnvironmentTemplateNetworkPort": { "properties": { "port": { "format": "int32", "description": "Optional. Port number to expose. This must be a valid port number, between 1 and 65535.", "type": "integer" }, "protocol": { "description": "Optional. Protocol for port. Defaults to TCP if not specified.", "enum": [ "PROTOCOL_UNSPECIFIED", "TCP", "UDP" ], "enumDescriptions": [ "Unspecified protocol. Defaults to TCP.", "TCP protocol.", "UDP protocol." ], "type": "string" } }, "description": "Represents a network port in a container.", "id": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateNetworkPort", "type": "object" }, "GoogleCloudAiplatformV1AuthConfigOauthConfig": { "type": "object", "description": "Config for user oauth.", "id": "GoogleCloudAiplatformV1AuthConfigOauthConfig", "properties": { "accessToken": { "description": "Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.", "type": "string" }, "serviceAccount": { "type": "string", "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." } } }, "GoogleCloudAiplatformV1FeatureSelector": { "id": "GoogleCloudAiplatformV1FeatureSelector", "type": "object", "description": "Selector for Features of an EntityType.", "properties": { "idMatcher": { "$ref": "GoogleCloudAiplatformV1IdMatcher", "description": "Required. Matches Features based on ID." } } }, "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlModelConfig": { "type": "object", "description": "Config for migrating Model in automl.googleapis.com to Vertex AI's Model.", "id": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlModelConfig", "properties": { "model": { "description": "Required. Full resource name of automl Model. Format: `projects/{project}/locations/{location}/models/{model}`.", "type": "string" }, "modelDisplayName": { "description": "Optional. Display name of the model in Vertex AI. System will pick a display name if unspecified.", "type": "string" } } }, "GoogleCloudAiplatformV1UpdatePersistentResourceOperationMetadata": { "type": "object", "id": "GoogleCloudAiplatformV1UpdatePersistentResourceOperationMetadata", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Operation metadata for PersistentResource." }, "progressMessage": { "description": "Progress Message for Update LRO", "type": "string" } }, "description": "Details of operations that perform update PersistentResource." }, "GoogleCloudAiplatformV1CreateDatasetOperationMetadata": { "description": "Runtime operation information for DatasetService.CreateDataset.", "id": "GoogleCloudAiplatformV1CreateDatasetOperationMetadata", "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The operation generic information." } } }, "GoogleCloudAiplatformV1JiraSourceJiraQueries": { "properties": { "email": { "type": "string", "description": "Required. The Jira email address." }, "apiKeyConfig": { "$ref": "GoogleCloudAiplatformV1ApiAuthApiKeyConfig", "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/)." }, "projects": { "items": { "type": "string" }, "description": "A list of Jira projects to import in their entirety.", "type": "array" }, "customQueries": { "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/", "type": "array", "items": { "type": "string" } }, "serverUri": { "type": "string", "description": "Required. The Jira server URI." } }, "id": "GoogleCloudAiplatformV1JiraSourceJiraQueries", "description": "JiraQueries contains the Jira queries and corresponding authentication.", "type": "object" }, "GoogleCloudAiplatformV1OnlineEvaluatorConfig": { "properties": { "randomSampling": { "description": "Random sampling method.", "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorConfigRandomSampling" }, "maxEvaluatedSamplesPerRun": { "format": "int64", "description": "Optional. The maximum number of evaluations to perform per run. If set to 0, the number is unbounded.", "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1OnlineEvaluatorConfig", "description": "Configuration for sampling behavior of the OnlineEvaluator. The OnlineEvaluator runs at a fixed interval of 10 minutes." }, "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerUserUsageData": { "type": "object", "description": "Per user usage data.", "id": "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerUserUsageData", "properties": { "username": { "description": "User's username", "type": "string" }, "viewCount": { "format": "int64", "description": "Number of times the user has read data within the Tensorboard.", "type": "string" } } }, "GoogleProtobufEmpty": { "id": "GoogleProtobufEmpty", "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); }", "type": "object" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoObjectTrackingMetrics": { "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).", "type": "object", "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoObjectTrackingMetrics", "properties": { "evaluatedBoundingBoxCount": { "description": "UNIMPLEMENTED. The total number of bounding boxes (i.e. summed over all frames) the ground truth used to create this evaluation had.", "type": "integer", "format": "int32" }, "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." }, "boundingBoxMeanAveragePrecision": { "format": "float", "type": "number", "description": "The single metric for bounding boxes evaluation: the `meanAveragePrecision` averaged over all `boundingBoxMetrics`." }, "trackMetrics": { "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTrackMetrics" }, "type": "array", "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." }, "boundingBoxMetrics": { "type": "array", "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.", "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetrics" } }, "trackMeanAveragePrecision": { "type": "number", "description": "UNIMPLEMENTED. The single metric for tracks accuracy evaluation: the `meanAveragePrecision` averaged over all `trackMetrics`.", "format": "float" }, "trackMeanMismatchRate": { "description": "UNIMPLEMENTED. The single metric for tracking consistency evaluation: the `meanMismatchRate` averaged over all `trackMetrics`.", "format": "float", "type": "number" }, "evaluatedFrameCount": { "description": "UNIMPLEMENTED. The number of video frames used to create this evaluation.", "format": "int32", "type": "integer" }, "trackMeanBoundingBoxIou": { "format": "float", "type": "number", "description": "UNIMPLEMENTED. The single metric for tracks bounding box iou evaluation: the `meanBoundingBoxIou` averaged over all `trackMetrics`." } } }, "GenaiVertexV1TextContentAnnotation": { "properties": { "placeCitation": { "description": "A place citation annotation.", "$ref": "GenaiVertexV1PlaceCitation" }, "startIndex": { "description": "Start of segment of the response that is attributed to this source. Index indicates the start of the segment, measured in bytes.", "format": "int32", "type": "integer" }, "wordInfo": { "description": "Word-level ASR annotation with timing and speaker info.", "$ref": "GenaiVertexV1WordInfo" }, "speechMetadata": { "description": "Speech annotation for text content.", "$ref": "GenaiVertexV1SpeechAnnotation" }, "fileCitation": { "description": "A file citation annotation.", "$ref": "GenaiVertexV1FileCitation" }, "urlCitation": { "description": "NOTE: We use these instead of the Citation message for historical reasons. A URL citation annotation.", "$ref": "GenaiVertexV1UrlCitation" }, "endIndex": { "description": "End of the attributed segment, exclusive.", "format": "int32", "type": "integer" } }, "description": "Citation information for model-generated content.", "id": "GenaiVertexV1TextContentAnnotation", "type": "object" }, "GoogleCloudAiplatformV1TrajectoryExactMatchResults": { "type": "object", "description": "Results for TrajectoryExactMatch metric.", "id": "GoogleCloudAiplatformV1TrajectoryExactMatchResults", "properties": { "trajectoryExactMatchMetricValues": { "readOnly": true, "description": "Output only. TrajectoryExactMatch metric values.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1TrajectoryExactMatchMetricValue" } } } }, "GoogleCloudAiplatformV1SafetyInstance": { "description": "Spec for safety instance.", "properties": { "prediction": { "type": "string", "description": "Required. Output of the evaluated model." } }, "type": "object", "id": "GoogleCloudAiplatformV1SafetyInstance" }, "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpec": { "id": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpec", "description": "Represents a parameter spec with condition from its parent parameter.", "type": "object", "properties": { "parameterSpec": { "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpec", "description": "Required. The spec for a conditional parameter." }, "parentIntValues": { "description": "The spec for matching values from a parent parameter of `INTEGER` type.", "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueCondition" }, "parentCategoricalValues": { "description": "The spec for matching values from a parent parameter of `CATEGORICAL` type.", "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition" }, "parentDiscreteValues": { "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition", "description": "The spec for matching values from a parent parameter of `DISCRETE` type." } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetection": { "properties": { "metadata": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata", "description": "The metadata information" }, "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetection", "description": "A TrainingJob that trains and uploads an AutoML Image Object Detection Model.", "type": "object" }, "GoogleCloudAiplatformV1ToolCallValidSpec": { "id": "GoogleCloudAiplatformV1ToolCallValidSpec", "type": "object", "description": "Spec for tool call valid metric.", "properties": {} }, "GoogleCloudAiplatformV1EvaluationRubricConfig": { "id": "GoogleCloudAiplatformV1EvaluationRubricConfig", "description": "Configuration for a rubric group to be generated/saved for evaluation.", "properties": { "rubricGroupKey": { "type": "string", "description": "Required. The key used to save the generated rubrics. If a generation spec is provided, this key will be used for the name of the generated rubric group. Otherwise, this key will be used to look up the existing rubric group on the evaluation item. Note that if a rubric group key is specified on both a rubric config and an evaluation metric, the key from the metric will be used to select the rubrics for evaluation." }, "rubricGenerationSpec": { "$ref": "GoogleCloudAiplatformV1EvaluationRunMetricRubricGenerationSpec", "description": "Dynamically generate rubrics using this specification." }, "predefinedRubricGenerationSpec": { "description": "Dynamically generate rubrics using a predefined spec.", "$ref": "GoogleCloudAiplatformV1EvaluationRunMetricPredefinedMetricSpec" } }, "type": "object" }, "GoogleCloudAiplatformV1StopNotebookRuntimeRequest": { "id": "GoogleCloudAiplatformV1StopNotebookRuntimeRequest", "description": "Request message for NotebookService.StopNotebookRuntime.", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1StreamingPredictRequest": { "id": "GoogleCloudAiplatformV1StreamingPredictRequest", "description": "Request message for PredictionService.StreamingPredict. The first message must contain endpoint field and optionally input. The subsequent messages must contain input.", "type": "object", "properties": { "parameters": { "$ref": "GoogleCloudAiplatformV1Tensor", "description": "The parameters that govern the prediction." }, "inputs": { "items": { "$ref": "GoogleCloudAiplatformV1Tensor" }, "type": "array", "description": "The prediction input." } } }, "GoogleCloudAiplatformV1AskContextsResponse": { "id": "GoogleCloudAiplatformV1AskContextsResponse", "description": "Response message for VertexRagService.AskContexts.", "type": "object", "properties": { "response": { "type": "string", "description": "The Retrieval Response." }, "contexts": { "$ref": "GoogleCloudAiplatformV1RagContexts", "description": "The contexts of the query." } } }, "GoogleCloudAiplatformV1EvaluateDatasetRequest": { "id": "GoogleCloudAiplatformV1EvaluateDatasetRequest", "description": "Request message for EvaluationService.EvaluateDataset.", "properties": { "autoraterConfig": { "description": "Optional. Autorater config used for evaluation. Currently only publisher Gemini models are supported. Format: `projects/{PROJECT}/locations/{LOCATION}/publishers/google/models/{MODEL}.`", "$ref": "GoogleCloudAiplatformV1AutoraterConfig" }, "metrics": { "description": "Required. The metrics used for evaluation.", "items": { "$ref": "GoogleCloudAiplatformV1Metric" }, "type": "array" }, "location": { "type": "string", "description": "Required. The resource name of the Location to evaluate the dataset. Format: `projects/{project}/locations/{location}`" }, "dataset": { "description": "Required. The dataset used for evaluation.", "$ref": "GoogleCloudAiplatformV1EvaluationDataset" }, "outputConfig": { "description": "Required. Config for evaluation output.", "$ref": "GoogleCloudAiplatformV1OutputConfig" } }, "type": "object" }, "GoogleCloudAiplatformV1GenerateMemoriesRequest": { "type": "object", "properties": { "directContentsSource": { "description": "Defines a direct source of content as the source content from which to generate memories.", "$ref": "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectContentsSource" }, "metadata": { "description": "Optional. User-provided metadata for the generated memories. This is not generated by Memory Bank.", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1MemoryMetadataValue" }, "type": "object" }, "vertexSessionSource": { "description": "Defines a Vertex Session as the source content from which to generate memories.", "$ref": "GoogleCloudAiplatformV1GenerateMemoriesRequestVertexSessionSource" }, "revisionTtl": { "format": "google-duration", "description": "Optional. The TTL for the revision. The expiration time is computed: now + TTL.", "type": "string" }, "disableConsolidation": { "description": "Optional. If true, generated memories will not be consolidated with existing memories; all generated memories will be added as new memories regardless of whether they are duplicates of or contradictory to existing memories. By default, memory consolidation is enabled.", "type": "boolean" }, "disableMemoryRevisions": { "description": "Optional. If true, no revisions will be created for this request.", "type": "boolean" }, "metadataMergeStrategy": { "type": "string", "enum": [ "METADATA_MERGE_STRATEGY_UNSPECIFIED", "OVERWRITE", "MERGE", "REQUIRE_EXACT_MATCH" ], "enumDescriptions": [ "Unspecified metadata merge strategy. If unspecified, the default behavior is to overwrite existing metadata (`OVERWRITE`).", "Replace the metadata of the updated memories with the new metadata.", "Append new metadata to the existing metadata. If there are duplicate keys, the existing values will be overwritten.", "Restrict consolidation to memories that have exactly the same metadata as the request. If a memory doesn't have the same metadata, it is not eligible for consolidation." ], "description": "Optional. The strategy to use when applying metadata to existing memories." }, "directMemoriesSource": { "$ref": "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectMemoriesSource", "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." }, "revisionLabels": { "type": "object", "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.", "additionalProperties": { "type": "string" } }, "revisionExpireTime": { "description": "Optional. Timestamp of when the revision is considered expired. If not set, the memory revision will be kept until manually deleted.", "type": "string", "format": "google-datetime" }, "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 '*'." }, "allowedTopics": { "description": "Optional. Restricts memory generation to a subset of memory topics.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1MemoryTopicId" } }, "timeZone": { "description": "Optional. The time zone of the conversation or caller, used as the baseline for resolving relative time expressions (e.g., \"yesterday\") and formatting timestamps. If not set, \"UTC\" is used. Must be a valid IANA Time Zone Database name, e.g. \"America/New_York\".", "type": "string" } }, "description": "Request message for MemoryBankService.GenerateMemories. Maximum size is 8 MB.", "id": "GoogleCloudAiplatformV1GenerateMemoriesRequest" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics": { "description": "Metrics for a single confidence threshold.", "type": "object", "properties": { "f1Score": { "format": "float", "description": "Output only. The harmonic mean of recall and precision.", "type": "number" }, "precision": { "type": "number", "format": "float", "description": "Output only. Precision for the given confidence threshold." }, "confidenceThreshold": { "format": "float", "description": "Output only. The confidence threshold value used to compute the metrics.", "type": "number" }, "recall": { "description": "Output only. Recall for the given confidence threshold.", "format": "float", "type": "number" } }, "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics" }, "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigTtlConfigGranularTtlConfig": { "properties": { "generateCreatedTtl": { "description": "Optional. The TTL duration for memories newly generated via GenerateMemories (GenerateMemoriesResponse.GeneratedMemory.Action.CREATED).", "format": "google-duration", "type": "string" }, "generateUpdatedTtl": { "format": "google-duration", "type": "string", "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)." }, "createTtl": { "type": "string", "description": "Optional. The TTL duration for memories uploaded via CreateMemory.", "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": "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigTtlConfigGranularTtlConfig", "type": "object" }, "GoogleCloudAiplatformV1ContentMap": { "description": "Map of placeholder in metric prompt template to contents of model input.", "properties": { "values": { "description": "Optional. Map of placeholder to contents.", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1ContentMapContents" }, "type": "object" } }, "id": "GoogleCloudAiplatformV1ContentMap", "type": "object" }, "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataRecordError": { "id": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataRecordError", "properties": { "sourceGcsUri": { "type": "string", "description": "Cloud Storage URI pointing to the original file in user's bucket." }, "embeddingId": { "description": "Empty if the embedding id is failed to parse.", "type": "string" }, "errorType": { "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.", "Multiple input records share the same datapoint id. The input conversion pipeline performs non-deterministic last-write-wins de-duplication and emits one error per duplicated id." ], "type": "string", "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", "DUPLICATE_ID" ], "description": "The error type of this record." }, "rawRecord": { "type": "string", "description": "The original content of this record." }, "errorMessage": { "type": "string", "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": "object" }, "GoogleCloudAiplatformV1ExactMatchInput": { "properties": { "instances": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ExactMatchInstance" }, "description": "Required. Repeated exact match instances." }, "metricSpec": { "description": "Required. Spec for exact match metric.", "$ref": "GoogleCloudAiplatformV1ExactMatchSpec" } }, "type": "object", "id": "GoogleCloudAiplatformV1ExactMatchInput", "description": "Input for exact match metric." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity", "description": "A duration of time expressed in time granularity units.", "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.", "type": "string", "format": "int64" }, "unit": { "type": "string", "description": "The time granularity unit of this time period. The supported units are: * \"minute\" * \"hour\" * \"day\" * \"week\" * \"month\" * \"year\"" } }, "type": "object" }, "GoogleCloudAiplatformV1SafetyInput": { "type": "object", "description": "Input for safety metric.", "id": "GoogleCloudAiplatformV1SafetyInput", "properties": { "instance": { "description": "Required. Safety instance.", "$ref": "GoogleCloudAiplatformV1SafetyInstance" }, "metricSpec": { "description": "Required. Spec for safety metric.", "$ref": "GoogleCloudAiplatformV1SafetySpec" } } }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics", "type": "object", "properties": { "falsePositiveRate": { "format": "float", "type": "number", "description": "False Positive Rate for the given confidence threshold." }, "falsePositiveRateAt1": { "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.", "type": "number" }, "confusionMatrix": { "description": "Confusion matrix of the evaluation for this confidence_threshold.", "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix" }, "recallAt1": { "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.", "format": "float", "type": "number" }, "recall": { "type": "number", "format": "float", "description": "Recall (True Positive Rate) for the given confidence threshold." }, "precision": { "description": "Precision for the given confidence threshold.", "format": "float", "type": "number" }, "trueNegativeCount": { "format": "int64", "description": "The number of labels that were not created by the Model, but if they would, they would not match a ground truth label.", "type": "string" }, "f1ScoreAt1": { "format": "float", "type": "number", "description": "The harmonic mean of recallAt1 and precisionAt1." }, "confidenceThreshold": { "type": "number", "description": "Metrics are computed with an assumption that the Model never returns predictions with score lower than this value.", "format": "float" }, "falseNegativeCount": { "description": "The number of ground truth labels that are not matched by a Model created label.", "format": "int64", "type": "string" }, "truePositiveCount": { "format": "int64", "type": "string", "description": "The number of Model created labels that match a ground truth label." }, "f1ScoreMacro": { "description": "Macro-averaged F1 Score.", "format": "float", "type": "number" }, "f1ScoreMicro": { "description": "Micro-averaged F1 Score.", "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" }, "maxPredictions": { "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`.", "type": "integer", "format": "int32" }, "f1Score": { "description": "The harmonic mean of recall and precision. For summary metrics, it computes the micro-averaged F1 score.", "type": "number", "format": "float" }, "falsePositiveCount": { "type": "string", "description": "The number of Model created labels that do not match a ground truth label.", "format": "int64" } } }, "GoogleCloudAiplatformV1EvaluationRunInferenceConfigAgentRunConfig": { "id": "GoogleCloudAiplatformV1EvaluationRunInferenceConfigAgentRunConfig", "type": "object", "description": "Configuration for Agent Run.", "properties": { "sessionInput": { "description": "Optional. The session input to get agent running results.", "$ref": "GoogleCloudAiplatformV1EvaluationRunInferenceConfigSessionInput" }, "geminiAgentConfig": { "description": "Optional. Config for scraping a Gemini Agent via the Interactions API. The scraping service creates interactions against the agent and returns the resulting interaction traces for evaluation.", "$ref": "GoogleCloudAiplatformV1GeminiAgentConfig" }, "agentEngine": { "description": "Optional. The resource name of the Agent Engine. Format: projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine} For example: projects/123/locations/us-central1/reasoningEngines/456", "type": "string" }, "userSimulatorConfig": { "description": "The configuration for a user simulator that uses an LLM to generate messages on behalf of the user.", "$ref": "GoogleCloudAiplatformV1EvaluationRunInferenceConfigAgentRunConfigUserSimulatorConfig" } } }, "GenaiVertexV1FunctionCallStep": { "properties": { "arguments": { "description": "Required. The arguments to pass to the function.", "$ref": "GenaiVertexV1Struct" }, "name": { "type": "string", "description": "Required. The name of the tool to call." } }, "description": "A function tool call step.", "id": "GenaiVertexV1FunctionCallStep", "type": "object" }, "GenaiVertexV1Interaction": { "type": "object", "id": "GenaiVertexV1Interaction", "properties": { "responseFormatSingleton": { "$ref": "GenaiVertexV1ResponseFormat" }, "environmentId": { "readOnly": true, "description": "Output only. The environment ID for the interaction. Only populated if environment config is set in the request.", "type": "string" }, "labels": { "description": "The labels with user-defined metadata for the request. 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" } }, "errors": { "readOnly": true, "items": { "$ref": "GenaiVertexV1Error" }, "type": "array", "description": "Output only. Diagnostic faults / platform errors recorded on the interaction." }, "stepList": { "description": "Input only. The steps for the interaction.", "$ref": "GenaiVertexV1StepList" }, "agentInteraction": { "$ref": "GenaiVertexV1AgentInteraction", "description": "Interaction for generating the completion using agents." }, "modelInteraction": { "$ref": "GenaiVertexV1ModelInteraction", "description": "Interaction for generating the completion using models." }, "id": { "type": "string", "readOnly": true, "description": "Required. Output only. A unique identifier for the interaction completion." }, "tools": { "description": "A list of tool declarations the model may call during interaction.", "type": "array", "items": { "$ref": "GenaiVertexV1Tool" } }, "safetySettings": { "items": { "$ref": "GenaiVertexV1SafetySetting" }, "description": "Safety settings for the interaction.", "type": "array" }, "stringContent": { "type": "string", "description": "A string input for the interaction, it will be processed as a single text input." }, "created": { "description": "Required. Output only. The time at which the response was created in ISO 8601 format (YYYY-MM-DDThh:mm:ssZ).", "readOnly": true, "type": "string" }, "serviceTier": { "description": "The service tier for the interaction.", "enumDescriptions": [ "Default service tier, which is standard.", "Flex service tier.", "Standard service tier.", "Priority service tier.", "Deferred service tier." ], "enum": [ "SERVICE_TIER_UNSPECIFIED", "SERVICE_TIER_FLEX", "SERVICE_TIER_STANDARD", "SERVICE_TIER_PRIORITY", "SERVICE_TIER_DEFERRED" ], "type": "string" }, "envId": { "type": "string", "description": "The environment ID for the interaction. Can be 'remote' for default environment." }, "steps": { "readOnly": true, "type": "array", "description": "Required. Output only. The steps that make up the interaction, when included in the response.", "items": { "$ref": "GenaiVertexV1Step" } }, "content": { "description": "The content for the interaction.", "$ref": "GenaiVertexV1Content" }, "usage": { "$ref": "GenaiVertexV1InteractionUsage", "description": "Output only. Statistics on the interaction request's token usage.", "readOnly": true }, "systemInstruction": { "description": "System instruction for the interaction.", "type": "string" }, "status": { "readOnly": true, "enum": [ "UNSPECIFIED", "IN_PROGRESS", "REQUIRES_ACTION", "COMPLETED", "FAILED", "CANCELLED", "INCOMPLETE", "QUEUED" ], "type": "string", "description": "Required. Output only. The status of the interaction.", "enumDescriptions": [ "Default value. This value is unused.", "The interaction is in progress.", "The interaction requires action/input from the user.", "The interaction is completed.", "The interaction failed.", "The interaction was cancelled.", "The interaction is completed, but contains incomplete results (e.g. hitting max_tokens).", "The interaction is queued, waiting for processing (e.g. waiting for off-peak capacity)." ] }, "updated": { "description": "Required. Output only. The time at which the response was last updated in ISO 8601 format (YYYY-MM-DDThh:mm:ssZ).", "readOnly": true, "type": "string" }, "responseFormatList": { "$ref": "GenaiVertexV1ResponseFormatList" }, "previousInteractionId": { "description": "The ID of the previous interaction, if any.", "type": "string" } }, "description": "Response for InteractionService.CreateInteraction." }, "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpec": { "description": "Specification for deploying from source code.", "properties": { "developerConnectSource": { "description": "Source code is in a Git repository managed by Developer Connect.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecDeveloperConnectSource" }, "inlineSource": { "description": "Source code is provided directly in the request.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecInlineSource" }, "imageSpec": { "description": "Optional. Configuration for building an image with custom config file.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecImageSpec" }, "agentConfigSource": { "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecAgentConfigSource", "description": "Source code is generated from the agent config." }, "pythonSpec": { "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecPythonSpec", "description": "Configuration for a Python application." } }, "type": "object", "id": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpec" }, "GoogleCloudAiplatformV1SyntheticField": { "id": "GoogleCloudAiplatformV1SyntheticField", "type": "object", "description": "Represents a single named field within a synthetic example, consisting of a name and the actual content.", "properties": { "content": { "description": "Required. The actual content or value for this field. This can be text, images, or other types of data.", "$ref": "GoogleCloudAiplatformV1Content" }, "fieldName": { "description": "Optional. The name of the specific field, such as \"product_name\" or \"review_text\".", "type": "string" } } }, "GoogleCloudAiplatformV1RagChunk": { "properties": { "text": { "type": "string", "description": "The content of the chunk." }, "pageSpan": { "description": "If populated, represents where the chunk starts and ends in the document.", "$ref": "GoogleCloudAiplatformV1RagChunkPageSpan" }, "chunkId": { "type": "string", "description": "The ID of the chunk." }, "fileId": { "type": "string", "description": "The ID of the file that the chunk belongs to." } }, "description": "A RagChunk includes the content of a chunk of a RagFile, and associated metadata.", "id": "GoogleCloudAiplatformV1RagChunk", "type": "object" }, "GenaiVertexV1UserInputStep": { "id": "GenaiVertexV1UserInputStep", "properties": { "contentString": { "description": "The content of the step. A single string.", "type": "string" }, "contentList": { "$ref": "GenaiVertexV1ContentList", "description": "The content of the step. An array of Content objects." } }, "description": "Input provided by the user.", "type": "object" }, "GoogleCloudAiplatformV1AudioTranscription": { "type": "object", "id": "GoogleCloudAiplatformV1AudioTranscription", "properties": { "speakerLabel": { "description": "Optional. A label identifying the speaker of this audio segment (e.g. `spk_1`, `spk_2`). Present when `diarization` is set.", "type": "string" }, "words": { "description": "Optional. Detailed word-level transcriptions and timing details. Present when `word_timestamp` is set.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1AudioTranscriptionWordInfo" } }, "text": { "type": "string", "description": "Required. The transcription text of this audio segment." } }, "description": "The transcription of an audio part. For multi-speaker audio, each speaker segment is a separate `Part` with its own `AudioTranscription` carrying the `speaker_label`." }, "GoogleCloudAiplatformV1ToolParameterKeyMatchMetricValue": { "type": "object", "id": "GoogleCloudAiplatformV1ToolParameterKeyMatchMetricValue", "description": "Tool parameter key match metric value for an instance.", "properties": { "score": { "readOnly": true, "type": "number", "description": "Output only. Tool parameter key match score.", "format": "float" } } }, "GenaiVertexV1ComputerUse": { "type": "object", "properties": { "enablePromptInjectionDetection": { "type": "boolean", "description": "Whether enable the prompt injection detection check on computer-use request." }, "disabledSafetyPolicies": { "type": "array", "description": "Optional. Disabled safety policies for computer use.", "items": { "type": "string", "enum": [ "SAFETY_POLICY_UNSPECIFIED", "FINANCIAL_TRANSACTIONS", "SENSITIVE_DATA_MODIFICATION", "COMMUNICATION_TOOL", "ACCOUNT_CREATION", "DATA_MODIFICATION", "USER_CONSENT_MANAGEMENT", "LEGAL_TERMS_AND_AGREEMENTS" ], "enumDescriptions": [ "Unspecified safety policy.", "Safety policy for financial transactions.", "Safety policy for sensitive data modification.", "Safety policy for communication tools (e.g. Gmail, Chat, Meet).", "Safety policy for account creation.", "Safety policy for data modification.", "Safety policy for user consent management.", "Safety policy for legal terms and agreements." ] } }, "excludedPredefinedFunctions": { "description": "The list of predefined functions that are excluded from the model call.", "type": "array", "items": { "type": "string" } }, "environment": { "enum": [ "ENVIRONMENT_UNSPECIFIED", "BROWSER", "MOBILE", "DESKTOP" ], "description": "The environment being operated.", "type": "string", "enumDescriptions": [ "Defaults to browser.", "Operates in a web browser.", "Operates in a mobile environment.", "Operates in a desktop environment." ] } }, "id": "GenaiVertexV1ComputerUse", "description": "A tool that can be used by the model to interact with the computer." }, "GoogleCloudAiplatformV1Transcription": { "id": "GoogleCloudAiplatformV1Transcription", "type": "object", "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." }, "GoogleCloudAiplatformV1CreateFeaturestoreOperationMetadata": { "type": "object", "properties": { "genericMetadata": { "description": "Operation metadata for Featurestore.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "description": "Details of operations that perform create Featurestore.", "id": "GoogleCloudAiplatformV1CreateFeaturestoreOperationMetadata" }, "GoogleCloudAiplatformV1DeployRequestModelConfig": { "id": "GoogleCloudAiplatformV1DeployRequestModelConfig", "properties": { "modelDisplayName": { "type": "string", "description": "Optional. The user-specified display name of the uploaded model. If not set, a default name will be used." }, "acceptEula": { "description": "Optional. Whether the user accepts the End User License Agreement (EULA) for the model.", "type": "boolean" }, "huggingFaceAccessToken": { "description": "Optional. The Hugging Face read access token used to access the model artifacts of gated models.", "type": "string" }, "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" }, "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" }, "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.", "$ref": "GoogleCloudAiplatformV1ModelContainerSpec" } }, "description": "The model config to use for the deployment.", "type": "object" }, "GoogleCloudAiplatformV1ProbeGrpcAction": { "properties": { "service": { "description": "Service is the name of the service to place in the gRPC HealthCheckRequest. See https://github.com/grpc/grpc/blob/master/doc/health-checking.md. If this is not specified, the default behavior is defined by gRPC.", "type": "string" }, "port": { "format": "int32", "type": "integer", "description": "Port number of the gRPC service. Number must be in the range 1 to 65535." } }, "id": "GoogleCloudAiplatformV1ProbeGrpcAction", "type": "object", "description": "GrpcAction checks the health of a container using a gRPC service." }, "GoogleCloudAiplatformV1Tensorboard": { "id": "GoogleCloudAiplatformV1Tensorboard", "properties": { "encryptionSpec": { "description": "Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "displayName": { "description": "Required. User provided name of this Tensorboard.", "type": "string" }, "runCount": { "description": "Output only. The number of Runs stored in this Tensorboard.", "format": "int32", "readOnly": true, "type": "integer" }, "updateTime": { "description": "Output only. Timestamp when this Tensorboard was last updated.", "readOnly": true, "type": "string", "format": "google-datetime" }, "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 '/'.", "type": "string", "readOnly": true }, "description": { "type": "string", "description": "Description of this Tensorboard." }, "labels": { "additionalProperties": { "type": "string" }, "type": "object", "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." }, "satisfiesPzs": { "readOnly": true, "description": "Output only. Reserved for future use.", "type": "boolean" }, "name": { "description": "Output only. Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "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" }, "isDefault": { "type": "boolean", "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." }, "satisfiesPzi": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "createTime": { "readOnly": true, "description": "Output only. Timestamp when this Tensorboard was created.", "format": "google-datetime", "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.", "type": "object" }, "GoogleCloudAiplatformV1ImportEvaluationSetRequestCloudTraceSource": { "description": "Source for loading traces directly from Cloud Trace.", "type": "object", "properties": { "agentResource": { "type": "string", "description": "Optional. Restricts the imported spans to a single agent. Accepts either of two forms, matching `OnlineEvaluator.agent_resource`: * a project-scoped resource name, matched against the `cloud.resource_id` resource attribute that Vertex AI Agent Engine agents are stamped with; * an Agent Registry agent URN, matched against the `gen_ai.main_agent.id` resource attribute that agents on GKE, and any other runtime that stamps it, are identified by. Scopes `session_ids` selection only. Traces named explicitly in `trace_ids` are imported as given and are NOT filtered by this field, because the caller has already identified them. Setting this field with only `trace_ids` therefore has no effect. When unset, spans are selected by session or trace ID alone. That is the pre-existing behavior and it remains the correct one for a session whose agents run in several deployments, because each deployment stamps its own `gen_ai.main_agent.id` and filtering on one of them would silently truncate the trajectory." }, "projectId": { "description": "Required. Project ID for the Cloud Trace.", "type": "string" }, "sessionIds": { "items": { "type": "string" }, "type": "array", "description": "Optional. Session IDs to import traces for. If both trace_ids and session_ids are specified, the union of the two will be imported." }, "traceIds": { "items": { "type": "string" }, "type": "array", "description": "Optional. Trace IDs to import." } }, "id": "GoogleCloudAiplatformV1ImportEvaluationSetRequestCloudTraceSource" }, "GoogleCloudAiplatformV1ToolParallelAiSearch": { "description": "ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding.", "id": "GoogleCloudAiplatformV1ToolParallelAiSearch", "properties": { "enableZeroDataRetention": { "description": "Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is \"false\" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is \"true\", the Parallel Web Search for Grounding - ZDR subscription will be used.", "type": "boolean" }, "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": { "description": "Properties of the object.", "type": "any" } }, "enableDataRetention": { "description": "Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is \"false\" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is \"true\", the Parallel Web Search for Grounding - ZDR subscription will be used.", "type": "boolean", "deprecated": true } }, "type": "object" }, "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlDatasetConfig": { "type": "object", "properties": { "datasetDisplayName": { "description": "Required. Display name of the Dataset in Vertex AI. System will pick a display name if unspecified.", "type": "string" }, "dataset": { "description": "Required. Full resource name of automl Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`.", "type": "string" } }, "description": "Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset.", "id": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateAutomlDatasetConfig" }, "GoogleCloudAiplatformV1SandboxEnvironmentTemplate": { "properties": { "name": { "description": "Identifier. The resource name of the SandboxEnvironmentTemplate. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentTemplates/{sandbox_environment_template}`", "type": "string" }, "egressControlConfig": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateEgressControlConfig", "description": "Optional. The configuration for egress control of this template." }, "createTime": { "readOnly": true, "description": "Output only. The timestamp when this SandboxEnvironmentTemplate was created.", "type": "string", "format": "google-datetime" }, "state": { "type": "string", "enum": [ "UNSPECIFIED", "PROVISIONING", "ACTIVE", "DEPROVISIONING", "DELETED", "FAILED" ], "readOnly": true, "description": "Output only. The state of the sandbox environment template.", "enumDescriptions": [ "The default value. This value is unused.", "Runtime resources are being allocated for the sandbox environment.", "Sandbox runtime is ready for serving.", "Sandbox runtime is halted, performing tear down tasks.", "Sandbox has terminated with underlying runtime failure.", "Sandbox has failed to provision." ] }, "updateTime": { "description": "Output only. The timestamp when this SandboxEnvironmentTemplate was most recently updated.", "format": "google-datetime", "type": "string", "readOnly": true }, "ingressControlConfig": { "description": "Optional. The configuration for private ingress (PSC-E) of this template. When set, the sandbox router is exposed privately via a PSC service attachment so VPC-SC customers can connect from their VPC over a private endpoint instead of the public internet. The resulting service attachment is surfaced on `SandboxEnvironment.connection_info.service_attachment`. Only the PSC-E (service-attachment/ingress) portion of `PrivateServiceConnectConfig` applies here: `enable_private_service_connect` and `project_allowlist` (the consumer projects allowed to connect). The nested `psc_interface_config` (PSC-I / egress) is not used for sandbox ingress; sandbox egress is configured via `egress_control_config` instead.", "$ref": "GoogleCloudAiplatformV1PrivateServiceConnectConfig" }, "displayName": { "type": "string", "description": "Required. The display name of the SandboxEnvironmentTemplate." }, "customContainerEnvironment": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateCustomContainerEnvironment", "description": "The sandbox environment for custom container workloads." }, "defaultContainerEnvironment": { "description": "The sandbox environment for default container workloads.", "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateDefaultContainerEnvironment" } }, "id": "GoogleCloudAiplatformV1SandboxEnvironmentTemplate", "description": "The specification of a SandboxEnvironmentTemplate. A SandboxEnvironmentTemplate defines a template for creating SandboxEnvironments.", "type": "object" }, "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigAgentToAnywhereConfig": { "id": "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigAgentToAnywhereConfig", "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" } }, "type": "object" }, "GoogleCloudAiplatformV1UpdateFeaturestoreOperationMetadata": { "description": "Details of operations that perform update Featurestore.", "type": "object", "properties": { "genericMetadata": { "description": "Operation metadata for Featurestore.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1UpdateFeaturestoreOperationMetadata" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextSentiment": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextSentiment", "type": "object", "properties": { "inputs": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs", "description": "The input parameters of this TrainingJob." } }, "description": "A TrainingJob that trains and uploads an AutoML Text Sentiment Model." }, "GenaiVertexV1GoogleSearchResultStep": { "description": "Google Search result step.", "properties": { "result": { "items": { "$ref": "GenaiVertexV1GoogleSearchResultStepGoogleSearchResultItem" }, "type": "array", "description": "Required. The results of the Google Search." }, "isError": { "description": "Whether the Google Search resulted in an error.", "type": "boolean" } }, "id": "GenaiVertexV1GoogleSearchResultStep", "type": "object" }, "GoogleCloudAiplatformV1CorroborateContentResponse": { "description": "Response message for CorroborateContent.", "type": "object", "id": "GoogleCloudAiplatformV1CorroborateContentResponse", "properties": { "corroborationScore": { "type": "number", "description": "Confidence score of corroborating content. Value is [0,1] with 1 is the most confidence.", "format": "float" }, "claims": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Claim" }, "description": "Claims that are extracted from the input content and facts that support the claims." } } }, "GenaiVertexV1GoogleMapsResultDelta": { "id": "GenaiVertexV1GoogleMapsResultDelta", "properties": { "result": { "description": "The results of the Google Maps.", "type": "array", "items": { "$ref": "GenaiVertexV1GoogleMapsResultContentGoogleMapsResult" } } }, "type": "object" }, "GoogleCloudAiplatformV1PreTunedModel": { "type": "object", "description": "A pre-tuned model for continuous tuning.", "id": "GoogleCloudAiplatformV1PreTunedModel", "properties": { "tunedModelName": { "description": "The resource name of the Model. E.g., a model resource name with a specified version id or alias: `projects/{project}/locations/{location}/models/{model}@{version_id}` `projects/{project}/locations/{location}/models/{model}@{alias}` Or, omit the version id to use the default version: `projects/{project}/locations/{location}/models/{model}`", "type": "string" }, "baseModel": { "type": "string", "description": "Output only. The name of the base model this PreTunedModel was tuned from.", "readOnly": true }, "checkpointId": { "description": "Optional. The source checkpoint id. If not specified, the default checkpoint will be used.", "type": "string" } } }, "GoogleCloudAiplatformV1PipelineTaskDetailArtifactList": { "type": "object", "description": "A list of artifact metadata.", "id": "GoogleCloudAiplatformV1PipelineTaskDetailArtifactList", "properties": { "artifacts": { "description": "Output only. A list of artifact metadata.", "items": { "$ref": "GoogleCloudAiplatformV1Artifact" }, "readOnly": true, "type": "array" } } }, "GoogleCloudAiplatformV1RagFileTransformationConfig": { "description": "Specifies the transformation config for RagFiles.", "id": "GoogleCloudAiplatformV1RagFileTransformationConfig", "properties": { "ragFileChunkingConfig": { "description": "Specifies the chunking config for RagFiles.", "$ref": "GoogleCloudAiplatformV1RagFileChunkingConfig" } }, "type": "object" }, "GoogleCloudAiplatformV1ToolNameMatchResults": { "description": "Results for tool name match metric.", "id": "GoogleCloudAiplatformV1ToolNameMatchResults", "properties": { "toolNameMatchMetricValues": { "type": "array", "description": "Output only. Tool name match metric values.", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1ToolNameMatchMetricValue" } } }, "type": "object" }, "GoogleCloudAiplatformV1NearestNeighborQueryNumericFilter": { "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", "type": "object", "properties": { "op": { "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." ], "type": "string", "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." }, "valueInt": { "type": "string", "description": "int value type.", "format": "int64" }, "name": { "description": "Required. Column name in BigQuery that used as filters.", "type": "string" }, "valueDouble": { "type": "number", "format": "double", "description": "double value type." }, "valueFloat": { "type": "number", "description": "float value type.", "format": "float" } }, "id": "GoogleCloudAiplatformV1NearestNeighborQueryNumericFilter" }, "GoogleCloudAiplatformV1ListNotebookExecutionJobsResponse": { "id": "GoogleCloudAiplatformV1ListNotebookExecutionJobsResponse", "description": "Response message for [NotebookService.CreateNotebookExecutionJob]", "properties": { "nextPageToken": { "type": "string", "description": "A token to retrieve next page of results. Pass to ListNotebookExecutionJobsRequest.page_token to obtain that page." }, "notebookExecutionJobs": { "items": { "$ref": "GoogleCloudAiplatformV1NotebookExecutionJob" }, "description": "List of NotebookExecutionJobs in the requested page.", "type": "array" } }, "type": "object" }, "GenaiVertexV1InteractionUsage": { "type": "object", "id": "GenaiVertexV1InteractionUsage", "description": "Statistics on the interaction request's token usage.", "properties": { "totalInputTokens": { "format": "int32", "description": "Number of tokens in the prompt (context).", "type": "integer" }, "totalCachedTokens": { "description": "Number of tokens in the cached part of the prompt (the cached content).", "format": "int32", "type": "integer" }, "toolUseTokensByModality": { "items": { "$ref": "GenaiVertexV1InteractionUsageModalityTokens" }, "description": "A breakdown of tool-use token usage by modality.", "type": "array" }, "cachedTokensByModality": { "description": "A breakdown of cached token usage by modality.", "type": "array", "items": { "$ref": "GenaiVertexV1InteractionUsageModalityTokens" } }, "totalOutputTokens": { "format": "int32", "description": "Total number of tokens across all the generated responses.", "type": "integer" }, "totalThoughtTokens": { "description": "Number of tokens of thoughts for thinking models.", "format": "int32", "type": "integer" }, "inputTokensByModality": { "items": { "$ref": "GenaiVertexV1InteractionUsageModalityTokens" }, "description": "A breakdown of input token usage by modality.", "type": "array" }, "totalToolUseTokens": { "description": "Number of tokens present in tool-use prompt(s).", "format": "int32", "type": "integer" }, "outputTokensByModality": { "description": "A breakdown of output token usage by modality.", "items": { "$ref": "GenaiVertexV1InteractionUsageModalityTokens" }, "type": "array" }, "totalTokens": { "description": "Total token count for the interaction request (prompt + responses + other internal tokens).", "type": "integer", "format": "int32" }, "groundingToolCount": { "description": "Grounding tool count.", "type": "array", "items": { "$ref": "GenaiVertexV1InteractionUsageGroundingToolCount" } } } }, "GoogleCloudAiplatformV1AggregationResult": { "description": "The aggregation result for a single metric.", "id": "GoogleCloudAiplatformV1AggregationResult", "type": "object", "properties": { "pointwiseMetricResult": { "$ref": "GoogleCloudAiplatformV1PointwiseMetricResult", "description": "Result for pointwise metric." }, "exactMatchMetricValue": { "$ref": "GoogleCloudAiplatformV1ExactMatchMetricValue", "description": "Results for exact match metric." }, "customCodeExecutionResult": { "description": "Result for code execution metric.", "$ref": "GoogleCloudAiplatformV1CustomCodeExecutionResult" }, "pairwiseMetricResult": { "$ref": "GoogleCloudAiplatformV1PairwiseMetricResult", "description": "Result for pairwise metric." }, "rougeMetricValue": { "$ref": "GoogleCloudAiplatformV1RougeMetricValue", "description": "Results for rouge metric." }, "aggregationMetric": { "enumDescriptions": [ "Unspecified aggregation metric.", "Average aggregation metric. Not supported for Pairwise metric.", "Mode aggregation metric.", "Standard deviation aggregation metric. Not supported for pairwise metric.", "Variance aggregation metric. Not supported for pairwise metric.", "Minimum aggregation metric. Not supported for pairwise metric.", "Maximum aggregation metric. Not supported for pairwise metric.", "Median aggregation metric. Not supported for pairwise metric.", "90th percentile aggregation metric. Not supported for pairwise metric.", "95th percentile aggregation metric. Not supported for pairwise metric.", "99th percentile aggregation metric. Not supported for pairwise metric." ], "type": "string", "description": "Aggregation metric.", "enum": [ "AGGREGATION_METRIC_UNSPECIFIED", "AVERAGE", "MODE", "STANDARD_DEVIATION", "VARIANCE", "MINIMUM", "MAXIMUM", "MEDIAN", "PERCENTILE_P90", "PERCENTILE_P95", "PERCENTILE_P99" ] }, "bleuMetricValue": { "$ref": "GoogleCloudAiplatformV1BleuMetricValue", "description": "Results for bleu metric." } } }, "GoogleCloudAiplatformV1SamplingStrategy": { "properties": { "randomSampleConfig": { "description": "Random sample config. Will support more sampling strategies later.", "$ref": "GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfig" } }, "id": "GoogleCloudAiplatformV1SamplingStrategy", "description": "Sampling Strategy for logging, can be for both training and prediction dataset.", "type": "object" }, "GoogleCloudAiplatformV1SchemaTextClassificationAnnotation": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaTextClassificationAnnotation", "description": "Annotation details specific to text classification.", "properties": { "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "annotationSpecId": { "type": "string", "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." } } }, "GoogleCloudAiplatformV1ResumeScheduleRequest": { "properties": { "catchUp": { "type": "boolean", "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": "object", "id": "GoogleCloudAiplatformV1ResumeScheduleRequest", "description": "Request message for ScheduleService.ResumeSchedule." }, "GenaiVertexV1FileSearchResultContentFileSearchResult": { "type": "object", "properties": {}, "id": "GenaiVertexV1FileSearchResultContentFileSearchResult", "description": "The result of the File Search." }, "GoogleCloudAiplatformV1StreamQueryReasoningEngineRequest": { "id": "GoogleCloudAiplatformV1StreamQueryReasoningEngineRequest", "description": "Request message for ReasoningEngineExecutionService.StreamQueryReasoningEngine.", "type": "object", "properties": { "classMethod": { "type": "string", "description": "Optional. Class method to be used for the stream query. It is optional and defaults to \"stream_query\" if unspecified." }, "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": { "description": "Properties of the object.", "type": "any" } } } }, "GoogleCloudAiplatformV1MemoryMetadataValue": { "id": "GoogleCloudAiplatformV1MemoryMetadataValue", "type": "object", "properties": { "boolValue": { "type": "boolean", "description": "Represents a boolean value." }, "doubleValue": { "type": "number", "description": "Represents a double value.", "format": "double" }, "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" } }, "description": "Memory metadata." }, "GoogleCloudAiplatformV1MetricMetadataScoreRange": { "id": "GoogleCloudAiplatformV1MetricMetadataScoreRange", "description": "The range of possible scores for this metric, used for plotting.", "type": "object", "properties": { "description": { "description": "Optional. The description of the score explaining the directionality etc.", "type": "string" }, "max": { "type": "number", "description": "Required. The maximum value of the score range (inclusive).", "format": "double" }, "min": { "description": "Required. The minimum value of the score range (inclusive).", "type": "number", "format": "double" }, "step": { "type": "number", "format": "double", "description": "Optional. The distance between discrete steps in the range. If unset, the range is assumed to be continuous." } } }, "GoogleCloudAiplatformV1CreateTensorboardRunRequest": { "type": "object", "description": "Request message for TensorboardService.CreateTensorboardRun.", "properties": { "tensorboardRun": { "$ref": "GoogleCloudAiplatformV1TensorboardRun", "description": "Required. The TensorboardRun to create." }, "parent": { "type": "string", "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`" }, "tensorboardRunId": { "type": "string", "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-/`." } }, "id": "GoogleCloudAiplatformV1CreateTensorboardRunRequest" }, "CloudAiLargeModelsVisionHumanPose": { "type": "object", "properties": { "bodyLandmarksGcsUri": { "type": "string", "description": "GCS URI of the human pose video to condition video generation.", "deprecated": true }, "faceLandmarksGcsUri": { "description": "GCS URI of the face landmarks video to condition video generation.", "deprecated": true, "type": "string" }, "perfMeshGcsUri": { "type": "string", "description": "GCS URI of the performance mesh to condition video generation." } }, "id": "CloudAiLargeModelsVisionHumanPose" }, "GoogleCloudAiplatformV1RubricContentProperty": { "type": "object", "description": "Defines criteria based on a specific property.", "id": "GoogleCloudAiplatformV1RubricContentProperty", "properties": { "description": { "description": "Description of the property being evaluated. Example: \"The model's response is grammatically correct.\"", "type": "string" } } }, "GoogleCloudAiplatformV1TrajectorySingleToolUseInput": { "type": "object", "id": "GoogleCloudAiplatformV1TrajectorySingleToolUseInput", "properties": { "instances": { "items": { "$ref": "GoogleCloudAiplatformV1TrajectorySingleToolUseInstance" }, "description": "Required. Repeated TrajectorySingleToolUse instance.", "type": "array" }, "metricSpec": { "description": "Required. Spec for TrajectorySingleToolUse metric.", "$ref": "GoogleCloudAiplatformV1TrajectorySingleToolUseSpec" } }, "description": "Instances and metric spec for TrajectorySingleToolUse metric." }, "GenaiVertexV1StepList": { "type": "object", "description": "A list of Steps.", "id": "GenaiVertexV1StepList", "properties": { "steps": { "description": "The steps of the list.", "items": { "$ref": "GenaiVertexV1Step" }, "type": "array" } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsGranularity": { "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": { "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.", "type": "string" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsGranularity" }, "GoogleCloudAiplatformV1RougeSpec": { "type": "object", "id": "GoogleCloudAiplatformV1RougeSpec", "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": { "useStemmer": { "type": "boolean", "description": "Optional. Whether to use stemmer to compute rouge score." }, "rougeType": { "type": "string", "description": "Optional. Supported rouge types are rougen[1-9], rougeL, and rougeLsum." }, "splitSummaries": { "type": "boolean", "description": "Optional. Whether to split summaries while using rougeLsum." } } }, "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataGcsSource": { "properties": { "uri": { "type": "array", "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.", "items": { "type": "string" } } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataGcsSource" }, "GoogleCloudAiplatformV1FindNeighborsRequest": { "description": "The request message for MatchService.FindNeighbors.", "id": "GoogleCloudAiplatformV1FindNeighborsRequest", "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" }, "queries": { "description": "The list of queries.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1FindNeighborsRequestQuery" } }, "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" } }, "type": "object" }, "GoogleCloudAiplatformV1ModelEvaluation": { "id": "GoogleCloudAiplatformV1ModelEvaluation", "properties": { "displayName": { "type": "string", "description": "The display name of the ModelEvaluation." }, "metadata": { "type": "any", "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\"." }, "name": { "readOnly": true, "type": "string", "description": "Output only. The resource name of the ModelEvaluation." }, "createTime": { "description": "Output only. Timestamp when this ModelEvaluation was created.", "readOnly": true, "format": "google-datetime", "type": "string" }, "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" }, "modelExplanation": { "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. ", "$ref": "GoogleCloudAiplatformV1ModelExplanation" }, "explanationSpecs": { "type": "array", "description": "Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.", "items": { "$ref": "GoogleCloudAiplatformV1ModelEvaluationModelEvaluationExplanationSpec" } }, "annotationSchemaUri": { "description": "Points to a YAML file stored on Google Cloud Storage describing EvaluatedDataItemView.predictions, EvaluatedDataItemView.ground_truths, EvaluatedAnnotation.predictions, and EvaluatedAnnotation.ground_truths. 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). This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.", "type": "string" }, "dataItemSchemaUri": { "description": "Points to a YAML file stored on Google Cloud Storage describing EvaluatedDataItemView.data_item_payload and EvaluatedAnnotation.data_item_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). This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.", "type": "string" }, "sliceDimensions": { "items": { "type": "string" }, "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" }, "metrics": { "description": "Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri", "type": "any" } }, "type": "object", "description": "A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data." }, "GoogleCloudAiplatformV1UsageMetadata": { "description": "Usage metadata about the content generation request and response. This message provides a detailed breakdown of token usage and other relevant metrics.", "id": "GoogleCloudAiplatformV1UsageMetadata", "properties": { "cachedContentTokenCount": { "type": "integer", "format": "int32", "description": "Output only. The number of tokens in the cached content that was used for this request.", "readOnly": true }, "candidatesTokenCount": { "format": "int32", "type": "integer", "description": "The total number of tokens in the generated candidates." }, "cacheTokensDetails": { "description": "Output only. A detailed breakdown of the token count for each modality in the cached content.", "items": { "$ref": "GoogleCloudAiplatformV1ModalityTokenCount" }, "readOnly": true, "type": "array" }, "totalTokenCount": { "description": "The total number of tokens for the entire request. This is the sum of `prompt_token_count`, `candidates_token_count`, `tool_use_prompt_token_count`, and `thoughts_token_count`.", "type": "integer", "format": "int32" }, "toolUsePromptTokensDetails": { "description": "Output only. A detailed breakdown by modality of the token counts from the results of tool executions, which are provided back to the model as input.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ModalityTokenCount" }, "readOnly": true }, "trafficType": { "description": "Output only. The traffic type for this request.", "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 Off-Peak Pay-As-You-Go traffic.", "Type for Provisioned Throughput traffic." ], "readOnly": true, "type": "string", "enum": [ "TRAFFIC_TYPE_UNSPECIFIED", "ON_DEMAND", "ON_DEMAND_PRIORITY", "ON_DEMAND_FLEX", "ON_DEMAND_OFFPEAK", "PROVISIONED_THROUGHPUT" ] }, "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" }, "promptTokenCount": { "type": "integer", "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.", "format": "int32" }, "promptTokensDetails": { "type": "array", "readOnly": true, "description": "Output only. A detailed breakdown of the token count for each modality in the prompt.", "items": { "$ref": "GoogleCloudAiplatformV1ModalityTokenCount" } }, "thoughtsTokenCount": { "readOnly": true, "description": "Output only. The number of tokens that were part of the model's generated \"thoughts\" output, if applicable.", "format": "int32", "type": "integer" }, "candidatesTokensDetails": { "description": "Output only. A detailed breakdown of the token count for each modality in the generated candidates.", "type": "array", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1ModalityTokenCount" } } }, "type": "object" }, "GoogleCloudAiplatformV1StringArray": { "description": "A list of string values.", "properties": { "values": { "type": "array", "items": { "type": "string" }, "description": "A list of string values." } }, "id": "GoogleCloudAiplatformV1StringArray", "type": "object" }, "GoogleCloudAiplatformV1ListExecutionsResponse": { "properties": { "executions": { "type": "array", "description": "The Executions retrieved from the MetadataStore.", "items": { "$ref": "GoogleCloudAiplatformV1Execution" } }, "nextPageToken": { "type": "string", "description": "A token, which can be sent as ListExecutionsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages." } }, "id": "GoogleCloudAiplatformV1ListExecutionsResponse", "description": "Response message for MetadataService.ListExecutions.", "type": "object" }, "GoogleCloudAiplatformV1ListFeaturesResponse": { "properties": { "nextPageToken": { "description": "A token, which can be sent as ListFeaturesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" }, "features": { "items": { "$ref": "GoogleCloudAiplatformV1Feature" }, "description": "The Features matching the request.", "type": "array" } }, "description": "Response message for FeaturestoreService.ListFeatures. Response message for FeatureRegistryService.ListFeatures.", "type": "object", "id": "GoogleCloudAiplatformV1ListFeaturesResponse" }, "GoogleCloudAiplatformV1SlackSourceSlackChannelsSlackChannel": { "id": "GoogleCloudAiplatformV1SlackSourceSlackChannelsSlackChannel", "description": "SlackChannel contains the Slack channel ID and the time range to import.", "type": "object", "properties": { "channelId": { "description": "Required. The Slack channel ID.", "type": "string" }, "startTime": { "format": "google-datetime", "type": "string", "description": "Optional. The starting timestamp for messages to import." }, "endTime": { "format": "google-datetime", "description": "Optional. The ending timestamp for messages to import.", "type": "string" } } }, "GenaiVertexV1ModelInteraction": { "id": "GenaiVertexV1ModelInteraction", "description": "Interaction for generating the completion using models.", "properties": { "generationConfig": { "description": "Input only. Configuration parameters for the model interaction.", "$ref": "GenaiVertexV1GenerationConfig" }, "model": { "description": "The name of the `Model` used for generating the completion.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs", "type": "object", "properties": { "sentimentMax": { "format": "int32", "type": "integer", "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)." } } }, "GoogleCloudAiplatformV1NotebookEucConfig": { "description": "The euc configuration of NotebookRuntimeTemplate.", "properties": { "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" }, "bypassActasCheck": { "type": "boolean", "readOnly": true, "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." } }, "type": "object", "id": "GoogleCloudAiplatformV1NotebookEucConfig" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs", "type": "object", "properties": { "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" }, "tunableParameter": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter", "description": "Trainer type for Vision TrainRequest." }, "budgetMilliNodeHours": { "type": "string", "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.", "format": "int64" }, "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" }, "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" ] } } }, "GoogleCloudAiplatformV1Citation": { "type": "object", "properties": { "endIndex": { "format": "int32", "readOnly": true, "description": "Output only. The end index of the citation in the content.", "type": "integer" }, "startIndex": { "type": "integer", "format": "int32", "description": "Output only. The start index of the citation in the content.", "readOnly": true }, "publicationDate": { "description": "Output only. The publication date of the source of the citation.", "readOnly": true, "$ref": "GoogleTypeDate" }, "uri": { "type": "string", "readOnly": true, "description": "Output only. The URI of the source of the citation." }, "license": { "type": "string", "description": "Output only. The license of the source of the citation.", "readOnly": true }, "title": { "description": "Output only. The title of the source of the citation.", "type": "string", "readOnly": true } }, "description": "A citation for a piece of generatedcontent.", "id": "GoogleCloudAiplatformV1Citation" }, "GoogleIamV1TestIamPermissionsResponse": { "type": "object", "id": "GoogleIamV1TestIamPermissionsResponse", "description": "Response message for `TestIamPermissions` method.", "properties": { "permissions": { "description": "A subset of `TestPermissionsRequest.permissions` that the caller is allowed.", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame": { "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": "GoogleCloudAiplatformV1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame", "properties": { "timeOffset": { "format": "google-duration", "type": "string", "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." }, "xMin": { "type": "number", "format": "float", "description": "The leftmost coordinate of the bounding box." }, "yMax": { "description": "The bottommost coordinate of the bounding box.", "type": "number", "format": "float" }, "xMax": { "type": "number", "description": "The rightmost coordinate of the bounding box.", "format": "float" }, "yMin": { "format": "float", "type": "number", "description": "The topmost coordinate of the bounding box." } }, "type": "object" }, "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition": { "properties": { "values": { "type": "array", "items": { "format": "double", "type": "number" }, "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." } }, "type": "object", "description": "Represents the spec to match discrete values from parent parameter.", "id": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition" }, "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroup": { "type": "object", "id": "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroup", "properties": { "featureGroupId": { "description": "Required. Identifier of the feature group.", "type": "string" }, "featureIds": { "items": { "type": "string" }, "type": "array", "description": "Required. Identifiers of features under the feature group." } }, "description": "Features belonging to a single feature group that will be synced to Online Store." }, "GoogleCloudAiplatformV1SchemaPromptSpecMultimodalPrompt": { "id": "GoogleCloudAiplatformV1SchemaPromptSpecMultimodalPrompt", "properties": { "promptMessage": { "description": "The prompt message.", "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecPromptMessage" } }, "type": "object", "description": "Prompt variation that embeds preambles to prompt string." }, "GoogleCloudAiplatformV1SchemaPredictInstanceImageSegmentationPredictionInstance": { "id": "GoogleCloudAiplatformV1SchemaPredictInstanceImageSegmentationPredictionInstance", "description": "Prediction input format for Image Segmentation.", "properties": { "content": { "description": "The image bytes to make the predictions on.", "type": "string" }, "mimeType": { "type": "string", "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": "object" }, "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecValue": { "description": "Single value that supports strings and floats.", "id": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecValue", "properties": { "stringValue": { "description": "String type.", "type": "string" }, "floatValue": { "type": "number", "format": "float", "description": "Float type." } }, "type": "object" }, "GoogleCloudAiplatformV1FeatureValueMetadata": { "type": "object", "description": "Metadata of feature value.", "id": "GoogleCloudAiplatformV1FeatureValueMetadata", "properties": { "generateTime": { "format": "google-datetime", "type": "string", "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." } } }, "GoogleCloudAiplatformV1SupervisedTuningSpec": { "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" }, "evaluationConfig": { "description": "Optional. Evaluation Config for Tuning Job.", "$ref": "GoogleCloudAiplatformV1EvaluationConfig" }, "exportLastCheckpointOnly": { "description": "Optional. If set to true, disable intermediate checkpoints for SFT and only the last checkpoint will be exported. Otherwise, enable intermediate checkpoints for SFT. Default is false.", "type": "boolean" }, "trainingDatasetUri": { "type": "string", "description": "Required. Training dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset." }, "hyperParameters": { "description": "Optional. Hyperparameters for SFT.", "$ref": "GoogleCloudAiplatformV1SupervisedHyperParameters" } }, "type": "object", "id": "GoogleCloudAiplatformV1SupervisedTuningSpec", "description": "Tuning Spec for Supervised Tuning for first party models." }, "GoogleCloudAiplatformV1AgentModelConfig": { "id": "GoogleCloudAiplatformV1AgentModelConfig", "description": "Selects the model configuration for an agent. Starts with just the model id/alias; extensible with further model parameters without a breaking change.", "type": "object", "properties": { "model": { "type": "string", "description": "Optional. Publisher model resource name (an `aiplatform.googleapis.com/PublisherModel`) of the form \"publishers/{publisher}/models/{model}\", e.g. \"publishers/anthropic/models/claude-opus-4-8\" or \"publishers/google/models/gemini-3-flash\". Empty means the agent's default gemini model." }, "temperature": { "format": "float", "description": "Optional. Sampling temperature for the model's generation config (valid range (0.0, 2.0]); a value outside that range leaves the backend default standing.", "type": "number" } } }, "GenaiVertexV1InteractionCompletedSseEvent": { "id": "GenaiVertexV1InteractionCompletedSseEvent", "properties": { "interaction": { "$ref": "GenaiVertexV1Interaction", "description": "Required. Partial completed interaction resource emitted at the end of the stream." } }, "type": "object", "description": "Signals that the Interaction completed. Sent when the Interaction receives Complete/Cancel or naturally terminates. No more input can be sent to the Interaction after this." }, "GoogleCloudAiplatformV1SupervisedTuningDataStats": { "properties": { "truncatedExampleIndices": { "items": { "format": "int64", "type": "string" }, "description": "Output only. A partial sample of the indices (starting from 1) of the dropped examples.", "readOnly": true, "type": "array" }, "tuningStepCount": { "format": "int64", "type": "string", "description": "Output only. Number of tuning steps for this Tuning Job.", "readOnly": true }, "userInputTokenDistribution": { "description": "Output only. Dataset distributions for the user input tokens.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistribution" }, "droppedExampleReasons": { "readOnly": true, "description": "Output only. For each index in `truncated_example_indices`, the user-facing reason why the example was dropped.", "type": "array", "items": { "type": "string" } }, "totalBillableTokenCount": { "format": "int64", "type": "string", "description": "Output only. Number of billable tokens in the tuning dataset.", "readOnly": true }, "totalTuningCharacterCount": { "readOnly": true, "type": "string", "description": "Output only. Number of tuning characters in the tuning dataset.", "format": "int64" }, "userOutputTokenDistribution": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistribution", "description": "Output only. Dataset distributions for the user output tokens." }, "userMessagePerExampleDistribution": { "$ref": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistribution", "readOnly": true, "description": "Output only. Dataset distributions for the messages per example." }, "userDatasetExamples": { "type": "array", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1Content" }, "description": "Output only. Sample user messages in the training dataset uri." }, "totalTruncatedExampleCount": { "readOnly": true, "format": "int64", "type": "string", "description": "Output only. The number of examples in the dataset that have been dropped. An example can be dropped for reasons including: too many tokens, contains an invalid image, contains too many images, etc." }, "tuningDatasetExampleCount": { "format": "int64", "description": "Output only. Number of examples in the tuning dataset.", "type": "string", "readOnly": true }, "totalBillableCharacterCount": { "description": "Output only. Number of billable characters in the tuning dataset.", "format": "int64", "deprecated": true, "type": "string", "readOnly": true } }, "id": "GoogleCloudAiplatformV1SupervisedTuningDataStats", "description": "Tuning data statistics for Supervised Tuning.", "type": "object" }, "GoogleCloudAiplatformV1GeminiPreferenceExample": { "type": "object", "id": "GoogleCloudAiplatformV1GeminiPreferenceExample", "properties": { "contents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Content" }, "description": "Multi-turn contents that represents the Prompt." }, "completions": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1GeminiPreferenceExampleCompletion" }, "description": "List of completions for a given prompt." } }, "description": "Input example for preference optimization." }, "GoogleCloudAiplatformV1DeleteOperationMetadata": { "description": "Details of operations that perform deletes of any entities.", "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1DeleteOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecPythonSpec": { "properties": { "version": { "description": "Optional. The version of Python to use. Supported versions include 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" }, "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": { "type": "string", "description": "Optional. The path to the requirements file, relative to the source root. If not specified, defaults to \"requirements.txt\"." } }, "type": "object", "description": "Specification for running a Python application from source.", "id": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecPythonSpec" }, "GoogleCloudAiplatformV1FeaturestoreMonitoringConfig": { "description": "Configuration of how features in Featurestore are monitored.", "type": "object", "properties": { "categoricalThresholdConfig": { "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).", "$ref": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig" }, "numericalThresholdConfig": { "description": "Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).", "$ref": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig" }, "snapshotAnalysis": { "$ref": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis", "description": "The config for Snapshot Analysis Based Feature Monitoring." }, "importFeaturesAnalysis": { "description": "The config for ImportFeatures Analysis Based Feature Monitoring.", "$ref": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis" } }, "id": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfig" }, "GoogleCloudAiplatformV1TrajectoryPrecisionSpec": { "id": "GoogleCloudAiplatformV1TrajectoryPrecisionSpec", "type": "object", "description": "Spec for TrajectoryPrecision metric - returns a float score based on average precision of individual tool calls.", "properties": {} }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionCustomJobMetadata": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionCustomJobMetadata", "properties": { "backingCustomJob": { "description": "The resource name of the CustomJob that has been created to carry out this custom task.", "type": "string" } } }, "GoogleCloudAiplatformV1ToolParameterKVMatchInstance": { "type": "object", "properties": { "reference": { "type": "string", "description": "Required. Ground truth used to compare against the prediction." }, "prediction": { "type": "string", "description": "Required. Output of the evaluated model." } }, "description": "Spec for tool parameter key value match instance.", "id": "GoogleCloudAiplatformV1ToolParameterKVMatchInstance" }, "GoogleCloudAiplatformV1ReadTensorboardUsageResponse": { "id": "GoogleCloudAiplatformV1ReadTensorboardUsageResponse", "type": "object", "description": "Response message for TensorboardService.ReadTensorboardUsage.", "properties": { "monthlyUsageData": { "type": "object", "description": "Maps year-month (YYYYMM) string to per month usage data.", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerMonthUsageData" } } } }, "GoogleCloudAiplatformV1ExternalApiSimpleSearchParams": { "properties": {}, "description": "The search parameters to use for SIMPLE_SEARCH spec.", "id": "GoogleCloudAiplatformV1ExternalApiSimpleSearchParams", "type": "object" }, "GoogleCloudAiplatformV1EvaluationPromptPromptTemplateData": { "id": "GoogleCloudAiplatformV1EvaluationPromptPromptTemplateData", "description": "Message to hold a prompt template and the values to populate the template.", "type": "object", "properties": { "values": { "description": "The values for fields in the prompt template.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1Content" } } } }, "GoogleCloudAiplatformV1ListReasoningEnginesResponse": { "description": "Response message for ReasoningEngineService.ListReasoningEngines", "properties": { "reasoningEngines": { "type": "array", "description": "List of ReasoningEngines in the requested page.", "items": { "$ref": "GoogleCloudAiplatformV1ReasoningEngine" } }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListReasoningEnginesRequest.page_token to obtain that page.", "type": "string" } }, "id": "GoogleCloudAiplatformV1ListReasoningEnginesResponse", "type": "object" }, "GenaiVertexV1GoogleMapsResultStepGoogleMapsResultItemGoogleMapsResultPlaces": { "properties": { "reviewSnippets": { "items": { "$ref": "GenaiVertexV1ReviewSnippet" }, "type": "array" }, "placeId": { "type": "string" }, "name": { "type": "string" }, "url": { "type": "string" } }, "id": "GenaiVertexV1GoogleMapsResultStepGoogleMapsResultItemGoogleMapsResultPlaces", "type": "object" }, "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityStringPredicate": { "properties": { "values": { "items": { "type": "string" }, "description": "Required. The values to match exactly (case-sensitive). Requires 1 to 20 values, each at most 128 characters long.", "type": "array" } }, "description": "Defines a predicate for filtering based on a string value.", "id": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityStringPredicate", "type": "object" }, "GoogleCloudAiplatformV1FeatureViewIndexConfigBruteForceConfig": { "properties": {}, "description": "Configuration options for using brute force search.", "type": "object", "id": "GoogleCloudAiplatformV1FeatureViewIndexConfigBruteForceConfig" }, "GoogleCloudAiplatformV1ImportFeatureValuesOperationMetadata": { "type": "object", "id": "GoogleCloudAiplatformV1ImportFeatureValuesOperationMetadata", "description": "Details of operations that perform import Feature values.", "properties": { "sourceUris": { "items": { "type": "string" }, "description": "The source URI from where Feature values are imported.", "type": "array" }, "invalidRowCount": { "format": "int64", "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)." }, "blockingOperationIds": { "description": "List of ImportFeatureValues operations running under a single EntityType that are blocking this operation.", "type": "array", "items": { "type": "string", "format": "int64" } }, "timestampOutsideRetentionRowsCount": { "description": "The number rows that weren't ingested due to having timestamps outside the retention boundary.", "format": "int64", "type": "string" }, "importedEntityCount": { "format": "int64", "description": "Number of entities that have been imported by the operation.", "type": "string" }, "importedFeatureValueCount": { "type": "string", "description": "Number of Feature values that have been imported by the operation.", "format": "int64" }, "genericMetadata": { "description": "Operation metadata for Featurestore import Feature values.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } } }, "GenaiVertexV1RagStoreConfigRagRetrievalConfigRanking": { "properties": { "rankService": { "description": "Config for Rank Service.", "$ref": "GenaiVertexV1RagStoreConfigRagRetrievalConfigRankingRankService" } }, "type": "object", "description": "Config for ranking and reranking.", "id": "GenaiVertexV1RagStoreConfigRagRetrievalConfigRanking" }, "GoogleCloudAiplatformV1Dataset": { "type": "object", "properties": { "metadataArtifact": { "readOnly": true, "type": "string", "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}`." }, "description": { "type": "string", "description": "The description of the Dataset." }, "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" }, "savedQueries": { "type": "array", "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.", "items": { "$ref": "GoogleCloudAiplatformV1SavedQuery" } }, "updateTime": { "description": "Output only. Timestamp when this Dataset was last updated.", "format": "google-datetime", "readOnly": true, "type": "string" }, "labels": { "additionalProperties": { "type": "string" }, "description": "The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable. Following system labels exist for each Dataset: * \"aiplatform.googleapis.com/dataset_metadata_schema\": output only, its value is the metadata_schema's title.", "type": "object" }, "displayName": { "type": "string", "description": "Required. The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters." }, "metadata": { "type": "any", "description": "Required. Additional information about the Dataset." }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1EncryptionSpec", "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." }, "name": { "readOnly": true, "type": "string", "description": "Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" }, "createTime": { "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when this Dataset was created.", "readOnly": true }, "dataItemCount": { "format": "int64", "type": "string", "readOnly": true, "description": "Output only. The number of DataItems in this Dataset. Only apply for non-structured Dataset." }, "etag": { "type": "string", "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." }, "satisfiesPzi": { "type": "boolean", "description": "Output only. Reserved for future use.", "readOnly": true } }, "description": "A collection of DataItems and Annotations on them.", "id": "GoogleCloudAiplatformV1Dataset" }, "GoogleCloudAiplatformV1UploadRagFileResponse": { "id": "GoogleCloudAiplatformV1UploadRagFileResponse", "properties": { "ragFile": { "$ref": "GoogleCloudAiplatformV1RagFile", "description": "The RagFile that had been uploaded into the RagCorpus." }, "error": { "description": "The error that occurred while processing the RagFile.", "$ref": "GoogleRpcStatus" } }, "description": "Response message for VertexRagDataService.UploadRagFile.", "type": "object" }, "GoogleCloudAiplatformV1ReadTensorboardTimeSeriesDataResponse": { "description": "Response message for TensorboardService.ReadTensorboardTimeSeriesData.", "properties": { "timeSeriesData": { "description": "The returned time series data.", "$ref": "GoogleCloudAiplatformV1TimeSeriesData" } }, "type": "object", "id": "GoogleCloudAiplatformV1ReadTensorboardTimeSeriesDataResponse" }, "GoogleCloudAiplatformV1SchemaPredictInstanceTextExtractionPredictionInstance": { "properties": { "key": { "description": "This field is only used for batch prediction. If a key is provided, the batch prediction result will by mapped to this key. If omitted, then the batch prediction result will contain the entire input instance. Vertex AI will not check if keys in the request are duplicates, so it is up to the caller to ensure the keys are unique.", "type": "string" }, "mimeType": { "type": "string", "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain" }, "content": { "type": "string", "description": "The text snippet to make the predictions on." } }, "id": "GoogleCloudAiplatformV1SchemaPredictInstanceTextExtractionPredictionInstance", "description": "Prediction input format for Text Extraction.", "type": "object" }, "GenaiVertexV1UrlContextCallContentUrlContextCallArguments": { "id": "GenaiVertexV1UrlContextCallContentUrlContextCallArguments", "properties": { "urls": { "description": "The URLs to fetch.", "items": { "type": "string" }, "type": "array" } }, "type": "object", "description": "The arguments to pass to the URL context." }, "GoogleCloudAiplatformV1WriteTensorboardExperimentDataRequest": { "type": "object", "id": "GoogleCloudAiplatformV1WriteTensorboardExperimentDataRequest", "properties": { "writeRunDataRequests": { "description": "Required. Requests containing per-run TensorboardTimeSeries data to write.", "items": { "$ref": "GoogleCloudAiplatformV1WriteTensorboardRunDataRequest" }, "type": "array" } }, "description": "Request message for TensorboardService.WriteTensorboardExperimentData." }, "GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpec": { "type": "object", "id": "GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpec", "properties": { "values": { "type": "array", "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.", "items": { "format": "double", "type": "number" } }, "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." } }, "description": "Value specification for a parameter in `DISCRETE` type." }, "GoogleCloudAiplatformV1TrajectoryRecallInput": { "id": "GoogleCloudAiplatformV1TrajectoryRecallInput", "properties": { "instances": { "type": "array", "description": "Required. Repeated TrajectoryRecall instance.", "items": { "$ref": "GoogleCloudAiplatformV1TrajectoryRecallInstance" } }, "metricSpec": { "description": "Required. Spec for TrajectoryRecall metric.", "$ref": "GoogleCloudAiplatformV1TrajectoryRecallSpec" } }, "description": "Instances and metric spec for TrajectoryRecall metric.", "type": "object" }, "GoogleCloudAiplatformV1CorroborateContentRequest": { "type": "object", "properties": { "facts": { "type": "array", "description": "Optional. Facts used to generate the text can also be used to corroborate the text.", "items": { "$ref": "GoogleCloudAiplatformV1Fact" } }, "content": { "description": "Optional. Input content to corroborate, only text format is supported for now.", "$ref": "GoogleCloudAiplatformV1Content" }, "parameters": { "description": "Optional. Parameters that can be set to override default settings per request.", "$ref": "GoogleCloudAiplatformV1CorroborateContentRequestParameters" } }, "id": "GoogleCloudAiplatformV1CorroborateContentRequest", "description": "Request message for CorroborateContent." }, "GoogleCloudAiplatformV1FindNeighborsResponse": { "description": "The response message for MatchService.FindNeighbors.", "properties": { "nearestNeighbors": { "description": "The nearest neighbors of the query datapoints.", "items": { "$ref": "GoogleCloudAiplatformV1FindNeighborsResponseNearestNeighbors" }, "type": "array" } }, "type": "object", "id": "GoogleCloudAiplatformV1FindNeighborsResponse" }, "GoogleCloudAiplatformV1NotebookExecutionJobDataformRepositorySource": { "properties": { "dataformRepositoryResourceName": { "type": "string", "description": "The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`" }, "commitSha": { "description": "The commit SHA to read repository with. If unset, the file will be read at HEAD.", "type": "string" } }, "id": "GoogleCloudAiplatformV1NotebookExecutionJobDataformRepositorySource", "description": "The Dataform Repository containing the input notebook.", "type": "object" }, "GoogleCloudAiplatformV1ListNasJobsResponse": { "id": "GoogleCloudAiplatformV1ListNasJobsResponse", "description": "Response message for JobService.ListNasJobs", "properties": { "nextPageToken": { "type": "string", "description": "A token to retrieve the next page of results. Pass to ListNasJobsRequest.page_token to obtain that page." }, "nasJobs": { "items": { "$ref": "GoogleCloudAiplatformV1NasJob" }, "description": "List of NasJobs in the requested page. NasJob.nas_job_output of the jobs will not be returned.", "type": "array" } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataInputConfig": { "properties": { "bigquerySource": { "$ref": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataBigQuerySource" }, "gcsSource": { "$ref": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataGcsSource" } }, "description": "The tables Dataset's data source. The Dataset doesn't store the data directly, but only pointer(s) to its data.", "id": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataInputConfig", "type": "object" }, "GoogleLongrunningOperation": { "type": "object", "id": "GoogleLongrunningOperation", "description": "This resource represents a long-running operation that is the result of a network API call.", "properties": { "metadata": { "type": "object", "additionalProperties": { "description": "Properties of the object. Contains field @type with type URL.", "type": "any" }, "description": "Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any." }, "done": { "type": "boolean", "description": "If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available." }, "response": { "type": "object", "description": "The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.", "additionalProperties": { "description": "Properties of the object. Contains field @type with type URL.", "type": "any" } }, "error": { "description": "The error result of the operation in case of failure or cancellation.", "$ref": "GoogleRpcStatus" }, "name": { "type": "string", "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}`." } } }, "GoogleCloudAiplatformV1AskContextsRequest": { "properties": { "query": { "description": "Required. Single RAG retrieve query.", "$ref": "GoogleCloudAiplatformV1RagQuery" }, "tools": { "items": { "$ref": "GoogleCloudAiplatformV1Tool" }, "type": "array", "description": "Optional. The tools to use for AskContexts." } }, "id": "GoogleCloudAiplatformV1AskContextsRequest", "type": "object", "description": "Agentic Retrieval Ask API for RAG. Request message for VertexRagService.AskContexts." }, "GoogleCloudAiplatformV1RagManagedDbConfigServerless": { "id": "GoogleCloudAiplatformV1RagManagedDbConfigServerless", "type": "object", "description": "Message to configure the serverless mode offered by RAG Engine.", "properties": {} }, "GoogleCloudAiplatformV1XraiAttribution": { "properties": { "blurBaselineConfig": { "$ref": "GoogleCloudAiplatformV1BlurBaselineConfig", "description": "Config for XRAI with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383" }, "smoothGradConfig": { "$ref": "GoogleCloudAiplatformV1SmoothGradConfig", "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" }, "stepCount": { "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.", "type": "integer", "format": "int32" } }, "id": "GoogleCloudAiplatformV1XraiAttribution", "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.", "type": "object" }, "GoogleCloudAiplatformV1ListServingProfilesResponse": { "id": "GoogleCloudAiplatformV1ListServingProfilesResponse", "description": "Response message for ServingProfileService.ListServingProfiles.", "properties": { "servingProfiles": { "type": "array", "description": "Output only. A list of ServingProfiles.", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1ServingProfile" } }, "nextPageToken": { "type": "string", "description": "Output only. A token to retrieve the next page of results.", "readOnly": true } }, "type": "object" }, "GenaiVertexV1FileSearchResultDelta": { "type": "object", "id": "GenaiVertexV1FileSearchResultDelta", "properties": { "result": { "type": "array", "items": { "$ref": "GenaiVertexV1FileSearchResultContentFileSearchResult" } } } }, "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectTimeRangeAndFeature": { "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": "GoogleCloudAiplatformV1FeatureSelector", "description": "Required. Selectors choosing which feature values to be deleted from the EntityType." }, "skipOnlineStorageDelete": { "type": "boolean", "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": "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.", "id": "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectTimeRangeAndFeature" }, "GoogleCloudAiplatformV1BigQueryRequestSet": { "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" }, "uri": { "description": "Required. The URI of a BigQuery table. e.g. bq://projectId.bqDatasetId.bqTableId", "type": "string" }, "candidateResponseColumns": { "additionalProperties": { "type": "string" }, "type": "object", "description": "Optional. Map of candidate name to candidate response column name. The column will be in evaluation_item.CandidateResponse format." }, "samplingConfig": { "description": "Optional. The sampling config for the bigquery resource.", "$ref": "GoogleCloudAiplatformV1BigQueryRequestSetSamplingConfig" } }, "description": "The request set for the evaluation run.", "type": "object", "id": "GoogleCloudAiplatformV1BigQueryRequestSet" }, "GoogleCloudAiplatformV1GroundednessSpec": { "id": "GoogleCloudAiplatformV1GroundednessSpec", "type": "object", "properties": { "version": { "format": "int32", "type": "integer", "description": "Optional. Which version to use for evaluation." } }, "description": "Spec for groundedness metric." }, "GoogleCloudAiplatformV1SpeechMetadata": { "description": "Structured Metadata Sub-Message for Part", "id": "GoogleCloudAiplatformV1SpeechMetadata", "properties": { "speaker": { "description": "Optional. Identifies which speaker is speaking this turn.", "type": "string" }, "style": { "type": "string", "description": "Optional. Natural language description of the vocal style (e.g., \"cheerful\")." } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaTextDataItem": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaTextDataItem", "properties": { "gcsUri": { "type": "string", "readOnly": true, "description": "Output only. Google Cloud Storage URI points to a copy of the original text in the Vertex-managed bucket in the user's project. The text file is up to 10MB in size." } }, "description": "Payload of Text DataItem." }, "GenaiVertexV1FunctionResultDelta": { "properties": { "isError": { "type": "boolean" }, "name": { "type": "string" }, "result": { "$ref": "GenaiVertexV1Value" } }, "type": "object", "id": "GenaiVertexV1FunctionResultDelta" }, "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInstance": { "description": "Spec for pairwise question answering quality instance.", "properties": { "prediction": { "description": "Required. Output of the candidate model.", "type": "string" }, "baselinePrediction": { "description": "Required. Output of the baseline model.", "type": "string" }, "context": { "type": "string", "description": "Required. Text to answer the question." }, "instruction": { "description": "Required. Question Answering prompt for LLM.", "type": "string" }, "reference": { "type": "string", "description": "Optional. Ground truth used to compare against the prediction." } }, "type": "object", "id": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInstance" }, "GoogleCloudAiplatformV1MetricxInput": { "description": "Input for MetricX metric.", "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1MetricxInstance", "description": "Required. Metricx instance." }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1MetricxSpec", "description": "Required. Spec for Metricx metric." } }, "type": "object", "id": "GoogleCloudAiplatformV1MetricxInput" }, "GoogleCloudAiplatformV1BatchImportModelEvaluationSlicesResponse": { "type": "object", "id": "GoogleCloudAiplatformV1BatchImportModelEvaluationSlicesResponse", "description": "Response message for ModelService.BatchImportModelEvaluationSlices", "properties": { "importedModelEvaluationSlices": { "readOnly": true, "items": { "type": "string" }, "type": "array", "description": "Output only. List of imported ModelEvaluationSlice.name." } } }, "GoogleCloudAiplatformV1DestinationFeatureSetting": { "type": "object", "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": "GoogleCloudAiplatformV1DestinationFeatureSetting" }, "GoogleCloudAiplatformV1UpdateFeatureOnlineStoreOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Operation metadata for FeatureOnlineStore." } }, "id": "GoogleCloudAiplatformV1UpdateFeatureOnlineStoreOperationMetadata", "description": "Details of operations that perform update FeatureOnlineStore.", "type": "object" }, "GoogleCloudAiplatformV1ListSemanticGovernancePoliciesResponse": { "type": "object", "properties": { "semanticGovernancePolicies": { "type": "array", "description": "The list of SemanticGovernancePolicies.", "items": { "$ref": "GoogleCloudAiplatformV1SemanticGovernancePolicy" } }, "nextPageToken": { "type": "string", "description": "A token to retrieve the next page of results. Pass to ListSemanticGovernancePoliciesRequest.page_token to obtain that page." } }, "id": "GoogleCloudAiplatformV1ListSemanticGovernancePoliciesResponse", "description": "Response message for SemanticGovernancePolicyService.ListSemanticGovernancePolicies." }, "GoogleCloudAiplatformV1Artifact": { "description": "Instance of a general artifact.", "id": "GoogleCloudAiplatformV1Artifact", "properties": { "schemaVersion": { "type": "string", "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." }, "state": { "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." ], "enum": [ "STATE_UNSPECIFIED", "PENDING", "LIVE" ], "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.", "type": "string" }, "displayName": { "type": "string", "description": "User provided display name of the Artifact. May be up to 128 Unicode characters." }, "createTime": { "format": "google-datetime", "readOnly": true, "type": "string", "description": "Output only. Timestamp when this Artifact was created." }, "schemaTitle": { "type": "string", "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." }, "updateTime": { "readOnly": true, "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when this Artifact was last updated." }, "uri": { "description": "The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.", "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." } }, "description": { "type": "string", "description": "Description of the Artifact" }, "etag": { "type": "string", "description": "An eTag used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." }, "name": { "type": "string", "readOnly": true, "description": "Output only. The resource name of the Artifact." }, "labels": { "additionalProperties": { "type": "string" }, "type": "object", "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" }, "GenaiVertexV1CodeExecutionCallStep": { "id": "GenaiVertexV1CodeExecutionCallStep", "type": "object", "description": "Code execution call step.", "properties": { "arguments": { "$ref": "GenaiVertexV1CodeExecutionCallStepCodeExecutionCallStepArguments", "description": "Required. The arguments to pass to the code execution." } } }, "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig": { "description": "The config for Featurestore Monitoring threshold.", "properties": { "value": { "type": "number", "format": "double", "description": "Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature." } }, "id": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig", "type": "object" }, "GoogleCloudAiplatformV1SchemaVisualInspectionMaskSavedQueryMetadata": { "id": "GoogleCloudAiplatformV1SchemaVisualInspectionMaskSavedQueryMetadata", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1CandidateResult": { "id": "GoogleCloudAiplatformV1CandidateResult", "properties": { "rubricVerdicts": { "items": { "$ref": "GoogleCloudAiplatformV1RubricVerdict" }, "description": "Optional. The rubric verdicts for the metric.", "type": "array" }, "explanation": { "type": "string", "description": "Optional. The explanation for the metric." }, "metric": { "description": "Required. The metric that was evaluated.", "type": "string" }, "score": { "format": "float", "type": "number", "description": "Optional. The score for the metric." }, "additionalResults": { "description": "Optional. Additional results for the metric.", "type": "any" }, "candidate": { "type": "string", "description": "Required. The candidate that is being evaluated. The value is the same as the candidate name in the EvaluationRequest." }, "error": { "description": "Output only. Error while evaluating the candidate for the metric.", "$ref": "GoogleRpcStatus", "readOnly": true } }, "type": "object", "description": "Result for a single candidate." }, "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataResponse": { "type": "object", "id": "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataResponse", "properties": { "nextPageToken": { "description": "A token, which can be sent as page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" }, "timeSeriesDataPoints": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1TimeSeriesDataPoint" }, "description": "The returned time series data points." } }, "description": "Response message for TensorboardService.ExportTensorboardTimeSeriesData." }, "GenaiVertexV1UrlContextResultStepUrlContextResultItem": { "type": "object", "description": "The result of the URL context.", "id": "GenaiVertexV1UrlContextResultStepUrlContextResultItem", "properties": { "url": { "type": "string", "description": "The URL that was fetched." }, "status": { "type": "string", "enum": [ "STATUS_UNSPECIFIED", "SUCCESS", "ERROR", "PAYWALL", "UNSAFE" ], "enumDescriptions": [ "", "", "", "", "" ], "description": "The status of the URL retrieval." } } }, "GoogleCloudAiplatformV1EmbedContentResponse": { "properties": { "embedding": { "description": "The embedding generated from the input content.", "$ref": "GoogleCloudAiplatformV1EmbedContentResponseEmbedding" }, "usageMetadata": { "description": "Usage metadata about the response(s).", "$ref": "GoogleCloudAiplatformV1UsageMetadata" }, "truncated": { "description": "Whether the input content was truncated before generating the embedding.", "type": "boolean" } }, "description": "Response message for PredictionService.EmbedContent.", "type": "object", "id": "GoogleCloudAiplatformV1EmbedContentResponse" }, "GoogleCloudAiplatformV1ListEvaluationSetsResponse": { "description": "Response message for EvaluationManagementService.ListEvaluationSets.", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results.", "type": "string" }, "evaluationSets": { "items": { "$ref": "GoogleCloudAiplatformV1EvaluationSet" }, "type": "array", "description": "List of EvaluationSets in the requested page." } }, "type": "object", "id": "GoogleCloudAiplatformV1ListEvaluationSetsResponse" }, "GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatus": { "description": "A single record of the task status.", "properties": { "state": { "readOnly": true, "type": "string", "enum": [ "STATE_UNSPECIFIED", "PENDING", "RUNNING", "SUCCEEDED", "CANCEL_PENDING", "CANCELLING", "CANCELLED", "FAILED", "SKIPPED", "NOT_TRIGGERED" ], "enumDescriptions": [ "Unspecified.", "Specifies pending state for the task.", "Specifies task is being executed.", "Specifies task completed successfully.", "Specifies Task cancel is in pending state.", "Specifies task is being cancelled.", "Specifies task was cancelled.", "Specifies task failed.", "Specifies task was skipped due to cache hit.", "Specifies that the task was not triggered because the task's trigger policy is not satisfied. The trigger policy is specified in the `condition` field of PipelineJob.pipeline_spec." ], "description": "Output only. The state of the task." }, "error": { "description": "Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "updateTime": { "description": "Output only. Update time of this status.", "type": "string", "readOnly": true, "format": "google-datetime" } }, "id": "GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatus", "type": "object" }, "GoogleCloudAiplatformV1TensorboardTensor": { "description": "One point viewable on a tensor metric plot.", "id": "GoogleCloudAiplatformV1TensorboardTensor", "type": "object", "properties": { "versionNumber": { "format": "int32", "description": "Optional. Version number of TensorProto used to serialize value.", "type": "integer" }, "value": { "format": "byte", "type": "string", "description": "Required. Serialized form of https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor.proto" } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecasting": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecasting", "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model.", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputs" }, "metadata": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingMetadata", "description": "The metadata information." } } }, "GoogleCloudAiplatformV1WorkerPoolSpec": { "type": "object", "description": "Represents the spec of a worker pool in a job.", "properties": { "containerSpec": { "$ref": "GoogleCloudAiplatformV1ContainerSpec", "description": "The custom container task." }, "nfsMounts": { "items": { "$ref": "GoogleCloudAiplatformV1NfsMount" }, "description": "Optional. List of NFS mount spec.", "type": "array" }, "machineSpec": { "description": "Optional. Immutable. The specification of a single machine.", "$ref": "GoogleCloudAiplatformV1MachineSpec" }, "diskSpec": { "description": "Disk spec.", "$ref": "GoogleCloudAiplatformV1DiskSpec" }, "pythonPackageSpec": { "$ref": "GoogleCloudAiplatformV1PythonPackageSpec", "description": "The Python packaged task." }, "replicaCount": { "type": "string", "format": "int64", "description": "Optional. The number of worker replicas to use for this worker pool." }, "lustreMounts": { "description": "Optional. List of Lustre mounts.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1LustreMount" } } }, "id": "GoogleCloudAiplatformV1WorkerPoolSpec" }, "GoogleCloudAiplatformV1PublisherModelCallToAction": { "id": "GoogleCloudAiplatformV1PublisherModelCallToAction", "type": "object", "properties": { "openFineTuningPipelines": { "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionOpenFineTuningPipelines", "description": "Optional. Open fine-tuning pipelines of the PublisherModel." }, "multiDeployVertex": { "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionDeployVertex", "description": "Optional. Multiple setups to deploy the PublisherModel to Vertex Endpoint." }, "openGenie": { "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences", "description": "Optional. Open Genie / Playground." }, "createApplication": { "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences", "description": "Optional. Create application using the PublisherModel." }, "deploy": { "description": "Optional. Deploy the PublisherModel to Vertex Endpoint.", "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionDeploy" }, "deployGke": { "description": "Optional. Deploy PublisherModel to Google Kubernetes Engine.", "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionDeployGke" }, "openEvaluationPipeline": { "description": "Optional. Open evaluation pipeline of the PublisherModel.", "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" }, "openFineTuningPipeline": { "description": "Optional. Open fine-tuning pipeline of the PublisherModel.", "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" }, "openNotebooks": { "description": "Optional. Open notebooks of the PublisherModel.", "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionOpenNotebooks" }, "viewRestApi": { "description": "Optional. To view Rest API docs.", "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionViewRestApi" }, "openGenerationAiStudio": { "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences", "description": "Optional. Open in Generation AI Studio." }, "openNotebook": { "description": "Optional. Open notebook of the PublisherModel.", "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" }, "openPromptTuningPipeline": { "description": "Optional. Open prompt-tuning pipeline of the PublisherModel.", "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" }, "requestAccess": { "description": "Optional. Request for access.", "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" } }, "description": "Actions could take on this Publisher Model." }, "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesRequest": { "properties": { "requests": { "items": { "$ref": "GoogleCloudAiplatformV1CreateTensorboardTimeSeriesRequest" }, "type": "array", "description": "Required. The request message specifying the TensorboardTimeSeries to create. A maximum of 1000 TensorboardTimeSeries can be created in a batch." } }, "description": "Request message for TensorboardService.BatchCreateTensorboardTimeSeries.", "type": "object", "id": "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesRequest" }, "GoogleCloudAiplatformV1SpeakerVoiceConfig": { "id": "GoogleCloudAiplatformV1SpeakerVoiceConfig", "properties": { "speaker": { "description": "Required. The name of the speaker. This should be the same as the speaker name used in the prompt.", "type": "string" }, "voiceConfig": { "$ref": "GoogleCloudAiplatformV1VoiceConfig", "description": "Required. The configuration for the voice of this speaker." } }, "description": "Configuration for a single speaker in a multi-speaker setup.", "type": "object" }, "GenaiVertexV1RagStoreConfigRagRetrievalConfigFilter": { "properties": { "vectorSimilarityThreshold": { "type": "number", "format": "double", "description": "Optional. Only returns contexts with vector similarity larger than the threshold." }, "metadataFilter": { "type": "string", "description": "Optional. String for metadata filtering." }, "vectorDistanceThreshold": { "type": "number", "format": "double", "description": "Optional. Only returns contexts with vector distance smaller than the threshold." } }, "description": "Config for filters.", "type": "object", "id": "GenaiVertexV1RagStoreConfigRagRetrievalConfigFilter" }, "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsResponse": { "description": "Response message for ModelService.BatchImportEvaluatedAnnotations", "id": "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsResponse", "properties": { "importedEvaluatedAnnotationsCount": { "description": "Output only. Number of EvaluatedAnnotations imported.", "format": "int32", "readOnly": true, "type": "integer" } }, "type": "object" }, "GoogleCloudAiplatformV1DirectPredictResponse": { "description": "Response message for PredictionService.DirectPredict.", "properties": { "parameters": { "description": "The parameters that govern the prediction.", "$ref": "GoogleCloudAiplatformV1Tensor" }, "outputs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Tensor" }, "description": "The prediction output." } }, "type": "object", "id": "GoogleCloudAiplatformV1DirectPredictResponse" }, "GoogleCloudAiplatformV1DeployRequestDeployConfig": { "properties": { "dedicatedResources": { "$ref": "GoogleCloudAiplatformV1DedicatedResources", "description": "Optional. The dedicated resources to use for the endpoint. If not set, the default resources will be used." }, "systemLabels": { "additionalProperties": { "type": "string" }, "type": "object", "description": "Optional. System labels for Model Garden deployments. These labels are managed by Google and for tracking purposes only." }, "fastTryoutEnabled": { "description": "Optional. If true, enable the QMT fast tryout feature for this model if possible.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1DeployRequestDeployConfig", "type": "object", "description": "The deploy config to use for the deployment." }, "GoogleCloudAiplatformV1UploadModelRequest": { "description": "Request message for ModelService.UploadModel.", "properties": { "model": { "description": "Required. The Model to create.", "$ref": "GoogleCloudAiplatformV1Model" }, "modelId": { "type": "string", "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." }, "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": { "type": "string", "description": "Optional. The resource name of the model into which to upload the version. Only specify this field when uploading a new version." } }, "type": "object", "id": "GoogleCloudAiplatformV1UploadModelRequest" }, "GoogleCloudAiplatformV1BatchMigrateResourcesResponse": { "type": "object", "properties": { "migrateResourceResponses": { "description": "Successfully migrated resources.", "items": { "$ref": "GoogleCloudAiplatformV1MigrateResourceResponse" }, "type": "array" } }, "id": "GoogleCloudAiplatformV1BatchMigrateResourcesResponse", "description": "Response message for MigrationService.BatchMigrateResources." }, "GoogleCloudAiplatformV1FindNeighborsRequestQuery": { "id": "GoogleCloudAiplatformV1FindNeighborsRequestQuery", "type": "object", "description": "A query to find a number of the nearest neighbors (most similar vectors) of a vector.", "properties": { "perCrowdingAttributeNeighborCount": { "format": "int32", "type": "integer", "description": "Crowding is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute. It's used for improving result diversity. This field is the maximum number of matches with the same crowding tag." }, "datapoint": { "$ref": "GoogleCloudAiplatformV1IndexDatapoint", "description": "Required. The datapoint/vector whose nearest neighbors should be searched for." }, "fractionLeafNodesToSearchOverride": { "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.", "type": "number", "format": "double" }, "rrf": { "$ref": "GoogleCloudAiplatformV1FindNeighborsRequestQueryRRF", "description": "Optional. Represents RRF algorithm that combines search results." }, "neighborCount": { "description": "The number of nearest neighbors to be retrieved from database for each query. If not set, will use the default from the service configuration (https://cloud.google.com/vertex-ai/docs/matching-engine/configuring-indexes#nearest-neighbor-search-config).", "format": "int32", "type": "integer" }, "approximateNeighborCount": { "description": "The number of neighbors to find via approximate search before exact reordering is performed. If not set, the default value from scam config is used; if set, this value must be \u003e 0.", "type": "integer", "format": "int32" } } }, "GoogleCloudAiplatformV1FileStatus": { "type": "object", "description": "RagFile status.", "properties": { "errorStatus": { "type": "string", "readOnly": true, "description": "Output only. Only when the `state` field is ERROR." }, "state": { "description": "Output only. RagFile state.", "readOnly": true, "enumDescriptions": [ "RagFile state is unspecified.", "RagFile resource has been created and indexed successfully.", "RagFile resource is in a problematic state. See `error_message` field for details." ], "type": "string", "enum": [ "STATE_UNSPECIFIED", "ACTIVE", "ERROR" ] } }, "id": "GoogleCloudAiplatformV1FileStatus" }, "GenaiVertexV1UrlContextCallStepUrlContextCallStepArguments": { "id": "GenaiVertexV1UrlContextCallStepUrlContextCallStepArguments", "properties": { "urls": { "items": { "type": "string" }, "description": "The URLs to fetch.", "type": "array" } }, "type": "object", "description": "The arguments to pass to the URL context." }, "GoogleCloudAiplatformV1ContentMapContents": { "description": "Repeated Content type.", "type": "object", "id": "GoogleCloudAiplatformV1ContentMapContents", "properties": { "contents": { "items": { "$ref": "GoogleCloudAiplatformV1Content" }, "type": "array", "description": "Optional. Repeated contents." } } }, "GoogleCloudAiplatformV1SchemaPredictPredictionTimeSeriesForecastingPredictionResult": { "type": "object", "properties": { "tftFeatureImportance": { "description": "Only use these if TFt is enabled.", "$ref": "GoogleCloudAiplatformV1SchemaPredictPredictionTftFeatureImportance" }, "value": { "description": "The regression value.", "type": "number", "format": "float" }, "quantileValues": { "type": "array", "description": "Quantile values.", "items": { "type": "number", "format": "float" } }, "quantilePredictions": { "items": { "type": "number", "format": "float" }, "type": "array", "description": "Quantile predictions, in 1-1 correspondence with quantile_values." } }, "id": "GoogleCloudAiplatformV1SchemaPredictPredictionTimeSeriesForecastingPredictionResult", "description": "Prediction output format for Time Series Forecasting." }, "GoogleCloudAiplatformV1ToolCall": { "description": "Spec for tool call.", "type": "object", "id": "GoogleCloudAiplatformV1ToolCall", "properties": { "toolInput": { "type": "string", "description": "Optional. Spec for tool input" }, "toolName": { "description": "Required. Spec for tool name", "type": "string" } } }, "GoogleCloudAiplatformV1CancelCustomJobRequest": { "description": "Request message for JobService.CancelCustomJob.", "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1CancelCustomJobRequest" }, "GoogleCloudAiplatformV1SchemaTextSegment": { "type": "object", "properties": { "endOffset": { "format": "uint64", "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.", "type": "string" }, "startOffset": { "format": "uint64", "type": "string", "description": "Zero-based character index of the first character of the text segment (counting characters from the beginning of the text)." }, "content": { "type": "string", "description": "The text content in the segment for output only." } }, "id": "GoogleCloudAiplatformV1SchemaTextSegment", "description": "The text segment inside of DataItem." }, "GoogleCloudAiplatformV1ModelArmorConfig": { "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.", "id": "GoogleCloudAiplatformV1ModelArmorConfig", "type": "object", "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": { "type": "string", "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}`." } } }, "GoogleCloudAiplatformV1AgentConfig": { "description": "Represents configuration for an Agent.", "type": "object", "id": "GoogleCloudAiplatformV1AgentConfig", "properties": { "description": { "type": "string", "description": "Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly." }, "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" }, "agentType": { "type": "string", "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." }, "subAgents": { "type": "array", "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.", "items": { "type": "string" } }, "tools": { "items": { "$ref": "GoogleCloudAiplatformV1Tool" }, "description": "Optional. The list of tools available to this agent.", "type": "array" }, "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" } } }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsRegressionEvaluationMetrics": { "description": "Metrics for regression evaluation results.", "properties": { "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", "type": "number", "description": "Mean Absolute Error (MAE)." }, "rootMeanSquaredError": { "type": "number", "format": "float", "description": "Root Mean Squared Error (RMSE)." }, "rootMeanSquaredLogError": { "format": "float", "description": "Root mean squared log error. Undefined when there are negative ground truth values or predictions.", "type": "number" }, "meanAbsolutePercentageError": { "type": "number", "description": "Mean absolute percentage error. Infinity when there are zeros in the ground truth.", "format": "float" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsRegressionEvaluationMetrics" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsSummarizationEvaluationMetrics": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsSummarizationEvaluationMetrics", "properties": { "rougeLSum": { "type": "number", "description": "ROUGE-L (Longest Common Subsequence) scoring at summary level.", "format": "float" } }, "type": "object" }, "GoogleCloudAiplatformV1RagFileParsingConfigLlmParser": { "properties": { "maxParsingRequestsPerMin": { "type": "integer", "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" }, "modelName": { "description": "The name of a LLM model used for parsing. Format: * `projects/{project_id}/locations/{location}/publishers/{publisher}/models/{model}`", "type": "string" }, "customParsingPrompt": { "description": "The prompt to use for parsing. If not specified, a default prompt will be used.", "type": "string" } }, "id": "GoogleCloudAiplatformV1RagFileParsingConfigLlmParser", "description": "Specifies the LLM parsing for RagFiles.", "type": "object" }, "GoogleCloudAiplatformV1ExactMatchInstance": { "description": "Spec for exact match instance.", "id": "GoogleCloudAiplatformV1ExactMatchInstance", "properties": { "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "reference": { "type": "string", "description": "Required. Ground truth used to compare against the prediction." } }, "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(''); }; // ...", "id": "GoogleTypeColor", "properties": { "blue": { "type": "number", "description": "The amount of blue in the color as a value in the interval [0, 1].", "format": "float" }, "red": { "description": "The amount of red in the color as a value in the interval [0, 1].", "type": "number", "format": "float" }, "alpha": { "type": "number", "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)." }, "green": { "format": "float", "description": "The amount of green in the color as a value in the interval [0, 1].", "type": "number" } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaPredictPredictionTabularClassificationPredictionResult": { "description": "Prediction output format for Tabular Classification.", "properties": { "classes": { "description": "The name of the classes being classified, contains all possible values of the target column.", "items": { "type": "string" }, "type": "array" }, "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": "GoogleCloudAiplatformV1SchemaPredictPredictionTabularClassificationPredictionResult", "type": "object" }, "GoogleCloudAiplatformV1UpsertDatapointsResponse": { "description": "Response message for IndexService.UpsertDatapoints", "id": "GoogleCloudAiplatformV1UpsertDatapointsResponse", "properties": {}, "type": "object" }, "GoogleCloudAiplatformV1MachineSpec": { "id": "GoogleCloudAiplatformV1MachineSpec", "description": "Specification of a single machine.", "properties": { "acceleratorCount": { "type": "integer", "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, Agent Platform co-schedules 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, Agent Platform co-schedules 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." }, "tpuTopology": { "type": "string", "description": "Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: \"2x2x1\")." }, "gpuPartitionSize": { "type": "string", "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." }, "machineType": { "description": "Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/gemini-enterprise-agent-platform/machine-learning/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/gemini-enterprise-agent-platform/machine-learning/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": { "description": "Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.", "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" ], "type": "string", "enumDeprecated": [ false, true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ], "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." ] }, "reservationAffinity": { "$ref": "GoogleCloudAiplatformV1ReservationAffinity", "description": "Optional. Immutable. Configuration controlling how this resource pool consumes reservation." } }, "type": "object" }, "GoogleCloudAiplatformV1CreateFeatureGroupOperationMetadata": { "id": "GoogleCloudAiplatformV1CreateFeatureGroupOperationMetadata", "properties": { "genericMetadata": { "description": "Operation metadata for FeatureGroup.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "type": "object", "description": "Details of operations that perform create FeatureGroup." }, "GoogleCloudAiplatformV1CountTokensResponse": { "type": "object", "properties": { "promptTokensDetails": { "description": "Output only. List of modalities that were processed in the request input.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ModalityTokenCount" }, "readOnly": true }, "totalBillableCharacters": { "description": "The total number of billable characters counted across all instances from the request.", "type": "integer", "format": "int32" }, "totalTokens": { "description": "The total number of tokens counted across all instances from the request.", "format": "int32", "type": "integer" } }, "id": "GoogleCloudAiplatformV1CountTokensResponse", "description": "Response message for PredictionService.CountTokens." }, "GoogleCloudAiplatformV1PairwiseMetricSpec": { "properties": { "baselineResponseFieldName": { "type": "string", "description": "Optional. The field name of the baseline response." }, "systemInstruction": { "description": "Optional. System instructions for pairwise metric.", "type": "string" }, "metricPromptTemplate": { "type": "string", "description": "Required. Metric prompt template for pairwise metric." }, "customOutputFormatConfig": { "description": "Optional. CustomOutputFormatConfig allows customization of metric output. When this config is set, the default output is replaced with the raw output string. If a custom format is chosen, the `pairwise_choice` and `explanation` fields in the corresponding metric result will be empty.", "$ref": "GoogleCloudAiplatformV1CustomOutputFormatConfig" }, "candidateResponseFieldName": { "type": "string", "description": "Optional. The field name of the candidate response." } }, "description": "Spec for pairwise metric.", "type": "object", "id": "GoogleCloudAiplatformV1PairwiseMetricSpec" }, "GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpec": { "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.", "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" } }, "id": "GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpec" }, "GoogleCloudAiplatformV1OutputInfo": { "description": "Describes the info for output of EvaluationService.", "type": "object", "properties": { "gcsOutputDirectory": { "description": "Output only. The full path of the Cloud Storage directory created, into which the evaluation results and aggregation results are written.", "readOnly": true, "type": "string" } }, "id": "GoogleCloudAiplatformV1OutputInfo" }, "GoogleCloudAiplatformV1FulfillmentInput": { "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1FulfillmentInstance", "description": "Required. Fulfillment instance." }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1FulfillmentSpec", "description": "Required. Spec for fulfillment score metric." } }, "type": "object", "description": "Input for fulfillment metric.", "id": "GoogleCloudAiplatformV1FulfillmentInput" }, "GoogleCloudAiplatformV1Neighbor": { "description": "Neighbors for example-based explanations.", "properties": { "neighborId": { "description": "Output only. The neighbor id.", "type": "string", "readOnly": true }, "neighborDistance": { "readOnly": true, "format": "double", "type": "number", "description": "Output only. The neighbor distance." } }, "id": "GoogleCloudAiplatformV1Neighbor", "type": "object" }, "GoogleCloudAiplatformV1ClientConnectionConfig": { "type": "object", "properties": { "inferenceTimeout": { "type": "string", "format": "google-duration", "description": "Customizable online prediction request timeout." } }, "id": "GoogleCloudAiplatformV1ClientConnectionConfig", "description": "Configurations (e.g. inference timeout) that are applied on your endpoints." }, "GoogleCloudAiplatformV1VertexMultimodalDatasetDestination": { "id": "GoogleCloudAiplatformV1VertexMultimodalDatasetDestination", "properties": { "bigqueryDestination": { "$ref": "GoogleCloudAiplatformV1BigQueryDestination", "description": "Optional. The destination of the underlying BigQuery table that will be created for the output Multimodal Dataset. If not specified, the BigQuery table will be created in a default BigQuery dataset." }, "displayName": { "description": "Optional. Display name of the output dataset.", "type": "string" } }, "description": "The details for a Vertex Multimodal Dataset output.", "type": "object" }, "GoogleCloudAiplatformV1RubricBasedInstructionFollowingResult": { "description": "Result for RubricBasedInstructionFollowing metric.", "id": "GoogleCloudAiplatformV1RubricBasedInstructionFollowingResult", "type": "object", "properties": { "score": { "type": "number", "description": "Output only. Overall score for the instruction following.", "format": "float", "readOnly": true }, "rubricCritiqueResults": { "description": "Output only. List of per rubric critique results.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1RubricCritiqueResult" }, "readOnly": true } } }, "GoogleCloudAiplatformV1SafetyResult": { "id": "GoogleCloudAiplatformV1SafetyResult", "description": "Spec for safety result.", "type": "object", "properties": { "confidence": { "format": "float", "description": "Output only. Confidence for safety score.", "readOnly": true, "type": "number" }, "explanation": { "readOnly": true, "type": "string", "description": "Output only. Explanation for safety score." }, "score": { "type": "number", "readOnly": true, "description": "Output only. Safety score.", "format": "float" } } }, "GoogleCloudAiplatformV1AutoraterConfig": { "description": "The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset.", "id": "GoogleCloudAiplatformV1AutoraterConfig", "properties": { "autoraterModel": { "type": "string", "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}`" }, "generationConfig": { "$ref": "GoogleCloudAiplatformV1GenerationConfig", "description": "Optional. Configuration options for model generation and outputs." }, "samplingCount": { "type": "integer", "description": "Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.", "format": "int32" }, "flipEnabled": { "type": "boolean", "description": "Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias." } }, "type": "object" }, "GoogleCloudAiplatformV1RubricContent": { "id": "GoogleCloudAiplatformV1RubricContent", "type": "object", "properties": { "property": { "$ref": "GoogleCloudAiplatformV1RubricContentProperty", "description": "Evaluation criteria based on a specific property." } }, "description": "Content of the rubric, defining the testable criteria." }, "GoogleCloudAiplatformV1Agent": { "properties": { "base_environment": { "description": "Optional. The base environment configuration for the agent. Valid types: * A string value for the environment ID, or `remote` for the default. * A struct value for the `environment_config`.", "type": "any" }, "object": { "readOnly": true, "description": "Output only. The object type of the resource. For agents, the value is `agent`.", "type": "string" }, "id": { "description": "Immutable. The user-specified ID for the agent. This ID becomes the final component of the agent resource name. If not provided, Vertex AI will generate a value for this ID. The ID can be up to 63 characters and must match the regular expression `[a-z]([a-z0-9-]{0,61}[a-z0-9])?`.", "type": "string" }, "tools": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1AgentTool" }, "description": "Optional. The tools available to the agent." }, "updated": { "readOnly": true, "format": "google-datetime", "type": "string", "description": "Output only. The time the agent was last updated." }, "base_agent": { "description": "Required. Immutable. The base agent for the agent. Supported values: * `antigravity-preview-05-2026` Immutable: `UpdateAgent` rejects a change, including clearing it. The kind of agent this is gets derived from this field when the agent is created and is recorded then; nothing recomputes it afterwards, so a later change would leave the agent described as one kind and behaving as another. Create a new agent instead.", "type": "string" }, "system_instruction": { "type": "string", "description": "Optional. The instructions for the agent to follow. These instructions are passed to the LLM as a system instruction." }, "modelConfig": { "description": "Optional. Model configuration for the agent. When set, tasks running under this agent default to this model configuration if they do not specify their own.", "$ref": "GoogleCloudAiplatformV1AgentModelConfig" }, "metadata": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The metadata for the agent." }, "observabilityConfig": { "$ref": "GoogleCloudAiplatformV1ObservabilityConfig", "description": "Optional. Observability settings for this agent's sessions." }, "description": { "description": "Optional. The description of the agent.", "type": "string" }, "effectiveIdentity": { "type": "string", "readOnly": true, "description": "Output only. The resolved Agent Identity (SPIFFE principal) of the agent." }, "created": { "readOnly": true, "format": "google-datetime", "type": "string", "description": "Output only. The time the agent was created." }, "name": { "description": "Identifier. The resource name of the agent. Format: `projects/{project}/locations/{location}/agents/{agent}`.", "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1Agent", "description": "A Vertex agent contains instructions and configurations for the LLM to execute a certain task." }, "GenaiVertexV1ParallelAISearchConfig": { "type": "object", "id": "GenaiVertexV1ParallelAISearchConfig", "description": "Used to specify configuration for ParallelAISearch.", "properties": { "apiKey": { "description": "Optional. The API key for ParallelAiSearch.", "type": "string" }, "customConfig": { "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. Custom configs for ParallelAiSearch.", "type": "object" } } }, "GenaiVertexV1InteractionUsageModalityTokens": { "description": "The token count for a single response modality.", "properties": { "modality": { "type": "string", "enum": [ "RESPONSE_MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "AUDIO", "VIDEO", "DOCUMENT" ], "description": "The modality associated with the token count.", "enumDescriptions": [ "Default value. This value is unused.", "Indicates the model should return text.", "Indicates the model should return images.", "Indicates the model should return audio.", "Indicates the model should return video.", "Indicates the model should return documents." ] }, "tokens": { "description": "Number of tokens for the modality.", "format": "int32", "type": "integer" } }, "type": "object", "id": "GenaiVertexV1InteractionUsageModalityTokens" }, "GoogleCloudAiplatformV1QueryDeployedModelsResponse": { "type": "object", "id": "GoogleCloudAiplatformV1QueryDeployedModelsResponse", "description": "Response message for QueryDeployedModels method.", "properties": { "totalDeployedModelCount": { "type": "integer", "description": "The total number of DeployedModels on this DeploymentResourcePool.", "format": "int32" }, "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": "GoogleCloudAiplatformV1DeployedModelRef" } }, "deployedModels": { "items": { "$ref": "GoogleCloudAiplatformV1DeployedModel" }, "deprecated": true, "description": "DEPRECATED Use deployed_model_refs instead.", "type": "array" }, "totalEndpointCount": { "type": "integer", "format": "int32", "description": "The total number of Endpoints that have DeployedModels on this DeploymentResourcePool." } } }, "GoogleCloudAiplatformV1CreateDatasetVersionOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The common part of the operation metadata." } }, "type": "object", "id": "GoogleCloudAiplatformV1CreateDatasetVersionOperationMetadata", "description": "Runtime operation information for DatasetService.CreateDatasetVersion." }, "GenaiVertexV1UrlContextResultStep": { "properties": { "isError": { "description": "Whether the URL context resulted in an error.", "type": "boolean" }, "result": { "items": { "$ref": "GenaiVertexV1UrlContextResultStepUrlContextResultItem" }, "description": "Required. The results of the URL context.", "type": "array" } }, "type": "object", "description": "URL context result step.", "id": "GenaiVertexV1UrlContextResultStep" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsQuestionAnsweringEvaluationMetrics": { "properties": { "exactMatch": { "format": "float", "type": "number", "description": "The rate at which the input predicted strings exactly match their references." } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsQuestionAnsweringEvaluationMetrics" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingMetadata": { "type": "object", "description": "Model metadata specific to AutoML Forecasting.", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingMetadata", "properties": { "trainCostMilliNodeHours": { "type": "string", "format": "int64", "description": "Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget." }, "evaluatedDataItemsBigqueryUri": { "description": "BigQuery destination uri for exported evaluated examples.", "type": "string" } } }, "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfig": { "description": "The configuration for grounding checking.", "properties": { "disableAttribution": { "type": "boolean", "deprecated": true, "description": "If set, skip finding claim attributions (i.e not generate grounding citation)." }, "sources": { "items": { "$ref": "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfigSourceEntry" }, "description": "The sources for the grounding checking.", "type": "array" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaPredictParamsGroundingConfig" }, "GoogleCloudAiplatformV1GenerateVideoResponseVideo": { "description": "A generated video.", "id": "GoogleCloudAiplatformV1GenerateVideoResponseVideo", "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" } } }, "GoogleCloudAiplatformV1GenerateSyntheticDataResponse": { "id": "GoogleCloudAiplatformV1GenerateSyntheticDataResponse", "properties": { "syntheticExamples": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SyntheticExample" }, "description": "A list of generated synthetic examples, each containing a complete synthetic data instance generated based on your request." } }, "description": "The response message for the `GenerateSyntheticData` method, containing the synthetic examples generated by the Gen AI evaluation service.", "type": "object" }, "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInput": { "type": "object", "description": "Input for pairwise question answering quality metric.", "id": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInput", "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInstance", "description": "Required. Pairwise question answering quality instance." }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualitySpec", "description": "Required. Spec for pairwise question answering quality score metric." } } }, "GoogleCloudAiplatformV1UpdateSpecialistPoolOperationMetadata": { "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" }, "specialistPool": { "readOnly": true, "type": "string", "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}`" } }, "id": "GoogleCloudAiplatformV1UpdateSpecialistPoolOperationMetadata", "type": "object", "description": "Runtime operation metadata for SpecialistPoolService.UpdateSpecialistPool." }, "GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScaling": { "properties": { "cpuUtilizationTarget": { "type": "integer", "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%.", "format": "int32" }, "maxNodeCount": { "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", "format": "int32" }, "minNodeCount": { "type": "integer", "description": "Required. The minimum number of nodes to scale down to. Must be greater than or equal to 1.", "format": "int32" } }, "id": "GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScaling", "type": "object" }, "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox": { "type": "object", "properties": { "y2": { "format": "int32", "type": "integer", "description": "The Y coordinate of the bottom-right corner, in pixels." }, "x1": { "description": "The X coordinate of the top-left corner, in pixels.", "type": "integer", "format": "int32" }, "y1": { "description": "The Y coordinate of the top-left corner, in pixels.", "type": "integer", "format": "int32" }, "x2": { "format": "int32", "type": "integer", "description": "The X coordinate of the bottom-right corner, in pixels." } }, "description": "An integer bounding box of original pixels of the image for the detected labels.", "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox" }, "GoogleCloudAiplatformV1SuggestTrialsRequest": { "type": "object", "properties": { "clientId": { "type": "string", "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." }, "suggestionCount": { "format": "int32", "type": "integer", "description": "Required. The number of suggestions requested. It must be positive." }, "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": "GoogleCloudAiplatformV1TrialContext" } } }, "description": "Request message for VizierService.SuggestTrials.", "id": "GoogleCloudAiplatformV1SuggestTrialsRequest" }, "GenaiVertexV1ExaAISearchConfig": { "properties": { "customConfig": { "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. This field can be used to pass any parameter from the Exa.ai Search API.", "type": "object" }, "apiKey": { "description": "Required. The API key for ExaAiSearch.", "type": "string" } }, "description": "Used to specify configuration for ExaAISearch.", "id": "GenaiVertexV1ExaAISearchConfig", "type": "object" }, "GoogleCloudAiplatformV1EvaluationRun": { "id": "GoogleCloudAiplatformV1EvaluationRun", "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.", "type": "object", "properties": { "name": { "type": "string", "description": "Identifier. The resource name of the EvaluationRun. This is a unique identifier. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}`" }, "completionTime": { "readOnly": true, "format": "google-datetime", "description": "Output only. Time when the evaluation run was completed.", "type": "string" }, "evaluationConfig": { "description": "Optional. The configuration used for the evaluation. Optional when analysis_configs is provided.", "$ref": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfig" }, "inferenceConfigs": { "description": "Optional. The candidate to inference config map for the evaluation run. The candidate can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1EvaluationRunInferenceConfig" } }, "error": { "description": "Output only. Only populated when the evaluation run's state is FAILED or CANCELLED.", "$ref": "GoogleRpcStatus", "readOnly": true }, "dataSource": { "$ref": "GoogleCloudAiplatformV1EvaluationRunDataSource", "description": "Required. The data source for the evaluation run." }, "displayName": { "type": "string", "description": "Required. The display name of the Evaluation Run." }, "encryptionSpec": { "description": "Optional. Customer-managed encryption key spec for this EvaluationRun. If set, this EvaluationRun will be secured by this key.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "evaluationResults": { "description": "Output only. The results of the evaluation run. Only populated when the evaluation run's state is SUCCEEDED.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1EvaluationResults" }, "metadata": { "type": "any", "description": "Optional. Metadata about the evaluation run, can be used by the caller to store additional tracking information about the evaluation run." }, "createTime": { "description": "Output only. Time when the evaluation run was created.", "format": "google-datetime", "readOnly": true, "type": "string" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. Labels for the evaluation run." }, "state": { "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." ], "description": "Output only. The state of the evaluation run.", "enum": [ "STATE_UNSPECIFIED", "PENDING", "RUNNING", "SUCCEEDED", "FAILED", "CANCELLED", "INFERENCE", "GENERATING_RUBRICS", "GENERATING_LOSS_CLUSTERS" ], "type": "string", "readOnly": true }, "evaluationSetSnapshot": { "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.", "type": "string" } } }, "GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpec": { "properties": { "useElapsedDuration": { "type": "boolean", "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." } }, "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.", "id": "GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpec", "type": "object" }, "GoogleCloudAiplatformV1FeatureValueList": { "type": "object", "id": "GoogleCloudAiplatformV1FeatureValueList", "description": "Container for list of values.", "properties": { "values": { "items": { "$ref": "GoogleCloudAiplatformV1FeatureValue" }, "type": "array", "description": "A list of feature values. All of them should be the same data type." } } }, "GoogleCloudAiplatformV1EmbedContentRequestEmbedContentConfig": { "id": "GoogleCloudAiplatformV1EmbedContentRequestEmbedContentConfig", "properties": { "outputDimensionality": { "description": "Optional. Reduced dimension for the output embedding. If set, excessive values in the output embedding are truncated from the end.", "type": "integer", "format": "int32" }, "documentOcr": { "description": "Optional. Whether to enable OCR for document content.", "type": "boolean" }, "title": { "type": "string", "description": "Optional. The title for the text. Only applicable to text-only embedding models." }, "audioTrackExtraction": { "type": "boolean", "description": "Optional. Whether to extract audio from video content." }, "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" }, "taskType": { "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." ], "enum": [ "UNSPECIFIED", "RETRIEVAL_QUERY", "RETRIEVAL_DOCUMENT", "SEMANTIC_SIMILARITY", "CLASSIFICATION", "CLUSTERING", "QUESTION_ANSWERING", "FACT_VERIFICATION", "CODE_RETRIEVAL_QUERY" ] } }, "description": "Configurations for the EmbedContent API.", "type": "object" }, "GoogleCloudAiplatformV1SmoothGradConfig": { "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": { "noisySampleCount": { "type": "integer", "format": "int32", "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." }, "noiseSigma": { "format": "float", "type": "number", "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." }, "featureNoiseSigma": { "$ref": "GoogleCloudAiplatformV1FeatureNoiseSigma", "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." } }, "type": "object", "id": "GoogleCloudAiplatformV1SmoothGradConfig" }, "GoogleCloudAiplatformV1GroundingChunkMapsRoute": { "type": "object", "properties": { "distanceMeters": { "description": "The total distance of the route, in meters.", "type": "integer", "format": "int32" }, "duration": { "type": "string", "description": "The total duration of the route.", "format": "google-duration" }, "encodedPolyline": { "type": "string", "description": "An encoded polyline of the route. See https://developers.google.com/maps/documentation/utilities/polylinealgorithm" } }, "description": "Route information from Google Maps.", "id": "GoogleCloudAiplatformV1GroundingChunkMapsRoute" }, "GenaiVertexV1UrlContextResultDelta": { "type": "object", "id": "GenaiVertexV1UrlContextResultDelta", "properties": { "result": { "items": { "$ref": "GenaiVertexV1UrlContextResultContentUrlContextResult" }, "type": "array" }, "isError": { "type": "boolean" } } }, "GoogleCloudAiplatformV1PrivateEndpoints": { "id": "GoogleCloudAiplatformV1PrivateEndpoints", "description": "PrivateEndpoints proto is used to provide paths for users to send requests privately. To send request via private service access, use predict_http_uri, explain_http_uri or health_http_uri. To send request via private service connect, use service_attachment.", "properties": { "healthHttpUri": { "description": "Output only. Http(s) path to send health check requests.", "readOnly": true, "type": "string" }, "explainHttpUri": { "type": "string", "description": "Output only. Http(s) path to send explain requests.", "readOnly": true }, "serviceAttachment": { "type": "string", "readOnly": true, "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled." }, "predictHttpUri": { "description": "Output only. Http(s) path to send prediction requests.", "type": "string", "readOnly": true } }, "type": "object" }, "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadata": { "properties": { "dataBytesCount": { "type": "string", "format": "int64", "description": "The ingested data size in bytes." }, "contentValidationStats": { "description": "The validation stats of the content (per file) to be inserted or updated on the Matching Engine Index resource. Populated if contentsDeltaUri is provided as part of Index.metadata. Please note that, currently for those files that are broken or has unsupported file format, we will not have the stats for those files.", "items": { "$ref": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataContentValidationStats" }, "type": "array" } }, "description": "Runtime operation metadata with regard to Matching Engine Index.", "type": "object", "id": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadata" }, "GoogleCloudAiplatformV1SlackSourceSlackChannels": { "description": "SlackChannels contains the Slack channels and corresponding access token.", "properties": { "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.", "$ref": "GoogleCloudAiplatformV1ApiAuthApiKeyConfig" }, "channels": { "items": { "$ref": "GoogleCloudAiplatformV1SlackSourceSlackChannelsSlackChannel" }, "description": "Required. The Slack channel IDs.", "type": "array" } }, "type": "object", "id": "GoogleCloudAiplatformV1SlackSourceSlackChannels" }, "GoogleCloudAiplatformV1ReadIndexDatapointsResponse": { "type": "object", "id": "GoogleCloudAiplatformV1ReadIndexDatapointsResponse", "properties": { "datapoints": { "type": "array", "description": "The result list of datapoints.", "items": { "$ref": "GoogleCloudAiplatformV1IndexDatapoint" } } }, "description": "The response message for MatchService.ReadIndexDatapoints." }, "GoogleCloudAiplatformV1DeployOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The operation generic information." }, "destination": { "description": "Output only. The resource name of the Location to deploy the model in. Format: `projects/{project}/locations/{location}`", "readOnly": true, "type": "string" }, "projectNumber": { "format": "int64", "readOnly": true, "type": "string", "description": "Output only. The project number where the deploy model request is sent." }, "modelId": { "description": "Output only. The model id to be used at query time.", "readOnly": true, "type": "string" }, "publisherModel": { "readOnly": true, "description": "Output only. The name of the model resource.", "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1DeployOperationMetadata", "description": "Runtime operation information for ModelGardenService.Deploy." }, "GoogleCloudAiplatformV1IndexDatapointSparseEmbedding": { "description": "Feature embedding vector for sparse index. An array of numbers whose values are located in the specified dimensions.", "properties": { "values": { "description": "Required. The list of embedding values of the sparse vector.", "type": "array", "items": { "format": "float", "type": "number" } }, "dimensions": { "type": "array", "description": "Required. The list of indexes for the embedding values of the sparse vector.", "items": { "format": "int64", "type": "string" } } }, "id": "GoogleCloudAiplatformV1IndexDatapointSparseEmbedding", "type": "object" }, "GoogleCloudAiplatformV1RollbackMemoryRequest": { "type": "object", "id": "GoogleCloudAiplatformV1RollbackMemoryRequest", "description": "Request message for MemoryBankService.RollbackMemory.", "properties": { "targetRevisionId": { "type": "string", "description": "Required. The ID of the revision to rollback to.", "format": "int64" } } }, "GoogleCloudAiplatformV1RagChunkPageSpan": { "id": "GoogleCloudAiplatformV1RagChunkPageSpan", "description": "Represents where the chunk starts and ends in the document.", "properties": { "firstPage": { "type": "integer", "description": "Page where chunk starts in the document. Inclusive. 1-indexed.", "format": "int32" }, "lastPage": { "description": "Page where chunk ends in the document. Inclusive. 1-indexed.", "type": "integer", "format": "int32" } }, "type": "object" }, "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences": { "type": "object", "properties": { "title": { "type": "string", "description": "Required. " }, "references": { "type": "object", "description": "Required.", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1PublisherModelResourceReference" } }, "resourceDescription": { "description": "Optional. Description of the resource.", "type": "string" }, "supportsWorkbench": { "description": "Optional. For notebook resource, whether the notebook supports Workbench.", "type": "boolean" }, "resourceTitle": { "description": "Optional. Title of the resource.", "type": "string" }, "resourceUseCase": { "description": "Optional. Use case (CUJ) of the resource.", "type": "string" }, "colabNotebookDisabled": { "type": "boolean", "description": "Optional. For notebook resource. When set to true, the Colab Enterprise link will be disabled in the \"open notebook\" dialog in UI." } }, "description": "The regional resource name or the URI. Key is region, e.g., us-central1, europe-west2, global, etc..", "id": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences" }, "GoogleCloudAiplatformV1NearestNeighborQuery": { "id": "GoogleCloudAiplatformV1NearestNeighborQuery", "description": "A query to find a number of similar entities.", "properties": { "embedding": { "description": "Optional. The embedding vector that be used for similar search.", "$ref": "GoogleCloudAiplatformV1NearestNeighborQueryEmbedding" }, "neighborCount": { "type": "integer", "format": "int32", "description": "Optional. The number of similar entities to be retrieved from feature view for each query." }, "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" }, "numericFilters": { "description": "Optional. The list of numeric filters.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1NearestNeighborQueryNumericFilter" } }, "perCrowdingAttributeNeighborCount": { "description": "Optional. Crowding is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than sper_crowding_attribute_neighbor_count of the k neighbors returned have the same value of crowding_attribute. It's used for improving result diversity.", "format": "int32", "type": "integer" }, "stringFilters": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1NearestNeighborQueryStringFilter" }, "description": "Optional. The list of string filters." }, "parameters": { "description": "Optional. Parameters that can be set to tune query on the fly.", "$ref": "GoogleCloudAiplatformV1NearestNeighborQueryParameters" } }, "type": "object" }, "GoogleCloudAiplatformV1CoherenceSpec": { "id": "GoogleCloudAiplatformV1CoherenceSpec", "type": "object", "properties": { "version": { "format": "int32", "description": "Optional. Which version to use for evaluation.", "type": "integer" } }, "description": "Spec for coherence score metric." }, "GoogleCloudAiplatformV1SchemaPredictionResultError": { "properties": { "status": { "type": "string", "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" ], "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" ] }, "message": { "description": "Error message with additional details.", "type": "string" } }, "id": "GoogleCloudAiplatformV1SchemaPredictionResultError", "type": "object" }, "CloudAiLargeModelsVisionGenerateVideoExperimentsOutpaintConfigFrameSource": { "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsOutpaintConfigFrameSource", "type": "object", "properties": { "globPattern": { "type": "string" }, "horizontalOffset": { "type": "integer", "description": "Horizontal offset in pixels of the frame's left edge from the canvas's left edge. Values outside the canvas crop the frame. Optional. Default is 0 (frame flush with the canvas's left edge).", "format": "int32" }, "verticalOffset": { "description": "Vertical offset in pixels of the frame's top edge from the canvas's top edge. Values outside the canvas crop the frame. Optional. Default is 0 (frame flush with the canvas's top edge).", "format": "int32", "type": "integer" } }, "description": "The input frame(s). It can be a full path or a glob pattern to images. The proto can be extended in the future for alternative ways to specify source of frames." }, "GoogleCloudAiplatformV1AuthConfig": { "type": "object", "properties": { "oidcConfig": { "$ref": "GoogleCloudAiplatformV1AuthConfigOidcConfig", "description": "Config for user OIDC auth." }, "apiKeyConfig": { "description": "Config for API key auth.", "$ref": "GoogleCloudAiplatformV1AuthConfigApiKeyConfig" }, "googleServiceAccountConfig": { "description": "Config for Google Service Account auth.", "$ref": "GoogleCloudAiplatformV1AuthConfigGoogleServiceAccountConfig" }, "httpBasicAuthConfig": { "description": "Config for HTTP Basic auth.", "$ref": "GoogleCloudAiplatformV1AuthConfigHttpBasicAuthConfig" }, "oauthConfig": { "description": "Config for user oauth.", "$ref": "GoogleCloudAiplatformV1AuthConfigOauthConfig" }, "authType": { "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.", "type": "string" } }, "description": "Auth configuration to run the extension.", "id": "GoogleCloudAiplatformV1AuthConfig" }, "GoogleCloudAiplatformV1QuestionAnsweringQualitySpec": { "type": "object", "description": "Spec for question answering quality score metric.", "properties": { "useReference": { "type": "boolean", "description": "Optional. Whether to use instance.reference to compute question answering quality." }, "version": { "description": "Optional. Which version to use for evaluation.", "format": "int32", "type": "integer" } }, "id": "GoogleCloudAiplatformV1QuestionAnsweringQualitySpec" }, "GoogleCloudAiplatformV1EvaluateDatasetResponse": { "type": "object", "id": "GoogleCloudAiplatformV1EvaluateDatasetResponse", "properties": { "aggregationOutput": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1AggregationOutput", "description": "Output only. Aggregation statistics derived from results of EvaluationService." }, "outputInfo": { "readOnly": true, "description": "Output only. Output info for EvaluationService.", "$ref": "GoogleCloudAiplatformV1OutputInfo" } }, "description": "The results from an evaluation run performed by the EvaluationService." }, "GoogleCloudAiplatformV1GenerateContentResponseUsageMetadata": { "id": "GoogleCloudAiplatformV1GenerateContentResponseUsageMetadata", "type": "object", "description": "Usage metadata about the content generation request and response. This message provides a detailed breakdown of token usage and other relevant metrics.", "properties": { "toolUsePromptTokenCount": { "format": "int32", "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.", "type": "integer" }, "candidatesTokensDetails": { "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1ModalityTokenCount" }, "description": "Output only. A detailed breakdown of the token count for each modality in the generated candidates.", "type": "array" }, "totalTokenCount": { "type": "integer", "description": "The total number of tokens for the entire request. This is the sum of `prompt_token_count`, `candidates_token_count`, `tool_use_prompt_token_count`, and `thoughts_token_count`.", "format": "int32" }, "cacheTokensDetails": { "readOnly": true, "description": "Output only. A detailed breakdown of the token count for each modality in the cached content.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ModalityTokenCount" } }, "toolUsePromptTokensDetails": { "items": { "$ref": "GoogleCloudAiplatformV1ModalityTokenCount" }, "readOnly": true, "type": "array", "description": "Output only. A detailed breakdown by modality of the token counts from the results of tool executions, which are provided back to the model as input." }, "trafficType": { "enum": [ "TRAFFIC_TYPE_UNSPECIFIED", "ON_DEMAND", "ON_DEMAND_PRIORITY", "ON_DEMAND_FLEX", "ON_DEMAND_OFFPEAK", "PROVISIONED_THROUGHPUT" ], "type": "string", "enumDescriptions": [ "Unspecified request traffic type.", "The request was processed using Pay-As-You-Go quota.", "Type for Priority Pay-As-You-Go traffic.", "Type for Flex traffic.", "Type for Off-Peak Pay-As-You-Go traffic.", "Type for Provisioned Throughput traffic." ], "readOnly": true, "description": "Output only. The traffic type for this request." }, "promptTokenCount": { "description": "The total number of tokens in the prompt. This includes any text, images, or other media provided in the request. When `cached_content` is set, this also includes the number of tokens in the cached content.", "format": "int32", "type": "integer" }, "thoughtsTokenCount": { "description": "Output only. The number of tokens that were part of the model's generated \"thoughts\" output, if applicable.", "type": "integer", "readOnly": true, "format": "int32" }, "cachedContentTokenCount": { "format": "int32", "readOnly": true, "description": "Output only. The number of tokens in the cached content that was used for this request.", "type": "integer" }, "promptTokensDetails": { "type": "array", "description": "Output only. A detailed breakdown of the token count for each modality in the prompt.", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1ModalityTokenCount" } }, "candidatesTokenCount": { "format": "int32", "description": "The total number of tokens in the generated candidates.", "type": "integer" } } }, "GoogleCloudAiplatformV1ListFeatureViewsResponse": { "type": "object", "id": "GoogleCloudAiplatformV1ListFeatureViewsResponse", "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureViews.", "properties": { "nextPageToken": { "type": "string", "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." }, "featureViews": { "items": { "$ref": "GoogleCloudAiplatformV1FeatureView" }, "description": "The FeatureViews matching the request.", "type": "array" } } }, "GenaiVertexV1TranscriptionConfig": { "type": "object", "description": "Configuration for speech recognition (transcription).", "id": "GenaiVertexV1TranscriptionConfig", "properties": { "adaptationPhrases": { "description": "Optional. A list of phrases to bias the ASR model towards.", "items": { "type": "string" }, "deprecated": true, "type": "array" }, "languageCodes": { "description": "Optional. BCP-47 language codes providing hints about the languages present in the audio. If omitted or empty, defaults to automatic language detection.", "type": "array", "items": { "type": "string" } }, "diarizationMode": { "deprecated": true, "description": "Optional. Configures speaker diarization. Supported values: \"speaker\".", "type": "string" }, "timestampGranularities": { "description": "Optional. The granularity of timestamps to include in the transcription output. Supported values: \"word\". If empty, no timestamps are generated.", "type": "array", "items": { "type": "string" }, "deprecated": true }, "customVocabulary": { "type": "array", "items": { "type": "string" }, "description": "Optional. A list of custom vocabulary phrases to bias the speech recognition model toward recognizing specific terms." } } }, "GoogleCloudAiplatformV1TimestampSplit": { "type": "object", "id": "GoogleCloudAiplatformV1TimestampSplit", "properties": { "key": { "type": "string", "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." }, "testFraction": { "format": "double", "description": "The fraction of the input data that is to be used to evaluate the Model.", "type": "number" }, "validationFraction": { "format": "double", "description": "The fraction of the input data that is to be used to validate the Model.", "type": "number" }, "trainingFraction": { "description": "The fraction of the input data that is to be used to train the Model.", "format": "double", "type": "number" } }, "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." }, "GoogleCloudAiplatformV1MigrateResourceResponse": { "properties": { "dataset": { "type": "string", "description": "Migrated Dataset's resource name." }, "model": { "description": "Migrated Model's resource name.", "type": "string" }, "migratableResource": { "$ref": "GoogleCloudAiplatformV1MigratableResource", "description": "Before migration, the identifier in ml.googleapis.com, automl.googleapis.com or datalabeling.googleapis.com." } }, "description": "Describes a successfully migrated resource.", "type": "object", "id": "GoogleCloudAiplatformV1MigrateResourceResponse" }, "GoogleCloudAiplatformV1ToolParameterKVMatchInput": { "description": "Input for tool parameter key value match metric.", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1ToolParameterKVMatchSpec", "description": "Required. Spec for tool parameter key value match metric." }, "instances": { "type": "array", "description": "Required. Repeated tool parameter key value match instances.", "items": { "$ref": "GoogleCloudAiplatformV1ToolParameterKVMatchInstance" } } }, "type": "object", "id": "GoogleCloudAiplatformV1ToolParameterKVMatchInput" }, "GoogleCloudAiplatformV1ListEvaluationRunsResponse": { "id": "GoogleCloudAiplatformV1ListEvaluationRunsResponse", "type": "object", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results.", "type": "string" }, "evaluationRuns": { "description": "List of EvaluationRuns in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1EvaluationRun" } } }, "description": "Response message for EvaluationManagementService.ListEvaluationRuns." }, "GoogleCloudAiplatformV1BatchDeletePipelineJobsRequest": { "description": "Request message for PipelineService.BatchDeletePipelineJobs.", "id": "GoogleCloudAiplatformV1BatchDeletePipelineJobsRequest", "properties": { "names": { "type": "array", "items": { "type": "string" }, "description": "Required. The names of the PipelineJobs to delete. A maximum of 32 PipelineJobs can be deleted in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}`" } }, "type": "object" }, "GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfig": { "type": "object", "properties": { "userEmails": { "type": "array", "description": "The email addresses to send the alert.", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfig", "description": "The config for email alert." }, "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentData": { "description": "Deprecated: Use `agent_eval_data` instead. Contains data specific to agent evaluations.", "type": "object", "deprecated": true, "id": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentData", "properties": { "tools": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataTools", "description": "List of tools." }, "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).", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentConfig" }, "type": "object" }, "toolsText": { "description": "A JSON string containing a list of tools available to an agent with info such as name, description, parameters and required parameters.", "type": "string", "deprecated": true }, "turns": { "items": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataConversationTurn" }, "type": "array", "description": "Optional. The chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -\u003e Agent Response)." }, "developerInstruction": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1EvaluationInstanceInstanceData", "description": "Optional. Deprecated: Use `agents.developer_instruction` or `turns.events.active_instruction` instead. A field containing instructions from the developer for the agent." }, "events": { "description": "A list of events.", "$ref": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataEvents" }, "agentConfig": { "description": "Optional. Deprecated: Use `agent_eval_data` instead. Agent configuration.", "$ref": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentConfig" } } }, "GoogleCloudAiplatformV1AuthConfigGoogleServiceAccountConfig": { "description": "Config for Google Service Account Authentication.", "properties": { "serviceAccount": { "type": "string", "description": "Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension." } }, "type": "object", "id": "GoogleCloudAiplatformV1AuthConfigGoogleServiceAccountConfig" }, "GoogleCloudAiplatformV1ImportDataResponse": { "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1ImportDataResponse", "description": "Response message for DatasetService.ImportData." }, "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataContentValidationStats": { "id": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataContentValidationStats", "properties": { "invalidSparseRecordCount": { "description": "Number of sparse records in this file we skipped due to validate errors.", "type": "string", "format": "int64" }, "invalidRecordCount": { "format": "int64", "type": "string", "description": "Number of records in this file we skipped due to validate errors." }, "validSparseRecordCount": { "description": "Number of sparse records in this file that were successfully processed.", "format": "int64", "type": "string" }, "partialErrors": { "items": { "$ref": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadataRecordError" }, "type": "array", "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." }, "sourceGcsUri": { "description": "Cloud Storage URI pointing to the original file in user's bucket.", "type": "string" }, "validRecordCount": { "type": "string", "format": "int64", "description": "Number of records in this file that were successfully processed." } }, "type": "object" }, "GoogleCloudAiplatformV1Attribution": { "id": "GoogleCloudAiplatformV1Attribution", "type": "object", "properties": { "approximationError": { "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.", "format": "double", "type": "number", "readOnly": true }, "baselineOutputValue": { "format": "double", "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.", "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": { "type": "integer", "format": "int32" } }, "featureAttributions": { "readOnly": true, "type": "any", "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)." }, "instanceOutputValue": { "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.", "format": "double", "readOnly": true, "type": "number" }, "outputDisplayName": { "readOnly": true, "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" }, "outputName": { "readOnly": true, "description": "Output only. Name of the explain output. Specified as the key in ExplanationMetadata.outputs.", "type": "string" } }, "description": "Attribution that explains a particular prediction output." }, "GoogleCloudAiplatformV1UpdateFeatureOperationMetadata": { "type": "object", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Operation metadata for Feature Update." } }, "description": "Details of operations that perform update Feature.", "id": "GoogleCloudAiplatformV1UpdateFeatureOperationMetadata" }, "GoogleCloudAiplatformV1SchemaVideoObjectTrackingAnnotation": { "properties": { "timeOffset": { "description": "A time (frame) of a video to which this annotation pertains. Represented as the duration since the video's start.", "format": "google-duration", "type": "string" }, "yMin": { "type": "number", "description": "The topmost coordinate of the bounding box.", "format": "double" }, "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "yMax": { "format": "double", "type": "number", "description": "The bottommost coordinate of the bounding box." }, "xMax": { "type": "number", "description": "The rightmost coordinate of the bounding box.", "format": "double" }, "annotationSpecId": { "type": "string", "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." }, "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" }, "xMin": { "format": "double", "description": "The leftmost coordinate of the bounding box.", "type": "number" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaVideoObjectTrackingAnnotation", "description": "Annotation details specific to video object tracking." }, "GenaiVertexV1AudioContent": { "type": "object", "id": "GenaiVertexV1AudioContent", "description": "An audio content block. ", "properties": { "channels": { "format": "int32", "description": "The number of audio channels.", "type": "integer" }, "mimeTypeString": { "description": "Flexible MIME type string of the audio, superseding mime_type = 1. Note: Bespoke logic in the GAOS parser/serializer maps this to the \"mime_type\" JSON key.", "type": "string" }, "data": { "format": "byte", "type": "string", "description": "The audio content." }, "sampleRate": { "description": "The sample rate of the audio.", "format": "int32", "type": "integer" }, "uri": { "type": "string", "description": "The URI of the audio." } } }, "GoogleCloudAiplatformV1VertexAISearchDataStoreSpec": { "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", "type": "object", "properties": { "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" }, "dataStore": { "type": "string", "description": "Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`" } }, "id": "GoogleCloudAiplatformV1VertexAISearchDataStoreSpec" }, "GoogleCloudAiplatformV1RubricVerdict": { "type": "object", "properties": { "verdict": { "type": "boolean", "description": "Required. Outcome of the evaluation against the rubric, represented as a boolean. `true` indicates a \"Pass\", `false` indicates a \"Fail\"." }, "evaluatedRubric": { "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.", "$ref": "GoogleCloudAiplatformV1Rubric" }, "reasoning": { "type": "string", "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." } }, "description": "Represents the verdict of an evaluation against a single rubric.", "id": "GoogleCloudAiplatformV1RubricVerdict" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation": { "properties": { "columnName": { "type": "string" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation", "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.", "type": "object" }, "GoogleCloudAiplatformV1DeployIndexRequest": { "type": "object", "id": "GoogleCloudAiplatformV1DeployIndexRequest", "description": "Request message for IndexEndpointService.DeployIndex.", "properties": { "deployedIndex": { "$ref": "GoogleCloudAiplatformV1DeployedIndex", "description": "Required. The DeployedIndex to be created within the IndexEndpoint." } } }, "GoogleCloudAiplatformV1UpgradeNotebookRuntimeOperationMetadata": { "properties": { "progressMessage": { "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime.", "type": "string" }, "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The operation generic information." } }, "id": "GoogleCloudAiplatformV1UpgradeNotebookRuntimeOperationMetadata", "type": "object", "description": "Metadata information for NotebookService.UpgradeNotebookRuntime." }, "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilitySessionScopeInactivityTrigger": { "description": "Configuration for inactivity based session completion.", "properties": { "threshold": { "type": "string", "description": "Required. The amount of time that must pass with no new traces before a session is considered ready for evaluation. This is a required field if InactivityTrigger is used. The value must be a positive duration no greater than 7 days (604800 seconds).", "format": "google-duration" } }, "type": "object", "id": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilitySessionScopeInactivityTrigger" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter": { "properties": { "studySpec": { "$ref": "GoogleCloudAiplatformV1StudySpec", "description": "Optioinal. StudySpec of hyperparameter tuning job. Required for `model_garden_trainer`." }, "trainerType": { "type": "string", "enum": [ "TRAINER_TYPE_UNSPECIFIED", "AUTOML_TRAINER", "MODEL_GARDEN_TRAINER" ], "enumDescriptions": [ "Default value.", "", "" ] }, "trainerConfig": { "description": "Customizable trainer settings, used in the `model_garden_trainer`.", "type": "object", "additionalProperties": { "type": "string" } }, "checkpointName": { "description": "Optional. An unique name of pretrained model checkpoint provided in model garden, it will be mapped to a GCS location internally.", "type": "string" }, "datasetConfig": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Customizable dataset settings, used in the `model_garden_trainer`." } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter", "description": "A wrapper class which contains the tunable parameters in an AutoML Image training job.", "type": "object" }, "GoogleCloudAiplatformV1FeatureViewDirectWriteResponseWriteResponse": { "type": "object", "id": "GoogleCloudAiplatformV1FeatureViewDirectWriteResponseWriteResponse", "description": "Details about the write for each key.", "properties": { "dataKey": { "description": "What key is this write response associated with.", "$ref": "GoogleCloudAiplatformV1FeatureViewDataKey" }, "onlineStoreWriteTime": { "description": "When the feature values were written to the online store. If FeatureViewDirectWriteResponse.status is not OK, this field is not populated.", "type": "string", "format": "google-datetime" } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation", "description": "Training pipeline will infer the proper transformation based on the statistic of dataset.", "type": "object", "properties": { "columnName": { "type": "string" } } }, "GoogleCloudAiplatformV1BatchPredictionJobInputConfig": { "type": "object", "properties": { "vertexMultimodalDatasetSource": { "$ref": "GoogleCloudAiplatformV1VertexMultimodalDatasetSource", "description": "A Vertex Managed Dataset. Currently, only datasets of type Multimodal are supported." }, "bigquerySource": { "description": "The BigQuery location of the input table. The schema of the table should be in the format described by the given context OpenAPI Schema, if one is provided. The table may contain additional columns that are not described by the schema, and they will be ignored.", "$ref": "GoogleCloudAiplatformV1BigQuerySource" }, "gcsSource": { "description": "The Cloud Storage location for the input instances.", "$ref": "GoogleCloudAiplatformV1GcsSource" }, "instancesFormat": { "type": "string", "description": "Required. The format in which instances are given, must be one of the Model's supported_input_storage_formats." } }, "id": "GoogleCloudAiplatformV1BatchPredictionJobInputConfig", "description": "Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them." }, "CloudAiLargeModelsVisionSeamless": { "type": "object", "id": "CloudAiLargeModelsVisionSeamless", "properties": { "tessellateVertical": { "description": "If true, the generated video will be tessellatable as a vertical tessellation.", "type": "boolean" }, "loop": { "description": "If true, the generated video will be loopable (seamless time looping).", "type": "boolean" }, "tessellateHorizontal": { "description": "If true, the generated video will be tessellatable as a horizontal tessellation.", "type": "boolean" } } }, "GoogleCloudAiplatformV1TrajectoryInOrderMatchMetricValue": { "id": "GoogleCloudAiplatformV1TrajectoryInOrderMatchMetricValue", "description": "TrajectoryInOrderMatch metric value for an instance.", "type": "object", "properties": { "score": { "readOnly": true, "description": "Output only. TrajectoryInOrderMatch score.", "format": "float", "type": "number" } } }, "GoogleCloudAiplatformV1ImportModelEvaluationRequest": { "properties": { "modelEvaluation": { "description": "Required. Model evaluation resource to be imported.", "$ref": "GoogleCloudAiplatformV1ModelEvaluation" } }, "type": "object", "id": "GoogleCloudAiplatformV1ImportModelEvaluationRequest", "description": "Request message for ModelService.ImportModelEvaluation" }, "GoogleCloudAiplatformV1MetricSource": { "description": "The metric source used for evaluation.", "id": "GoogleCloudAiplatformV1MetricSource", "type": "object", "properties": { "metricResourceName": { "description": "Optional. Resource name for registered metric.", "type": "string" }, "metric": { "$ref": "GoogleCloudAiplatformV1Metric", "description": "Inline metric config." } } }, "GoogleCloudAiplatformV1ExplanationMetadataOutputMetadata": { "properties": { "indexDisplayNameMapping": { "description": "Static mapping between the index and display name. Use this if the outputs are a deterministic n-dimensional array, e.g. a list of scores of all the classes in a pre-defined order for a multi-classification Model. It's not feasible if the outputs are non-deterministic, e.g. the Model produces top-k classes or sort the outputs by their values. The shape of the value must be an n-dimensional array of strings. The number of dimensions must match that of the outputs to be explained. The Attribution.output_display_name is populated by locating in the mapping with Attribution.output_index.", "type": "any" }, "outputTensorName": { "type": "string", "description": "Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow." }, "displayNameMappingKey": { "type": "string", "description": "Specify a field name in the prediction to look for the display name. Use this if the prediction contains the display names for the outputs. The display names in the prediction must have the same shape of the outputs, so that it can be located by Attribution.output_index for a specific output." } }, "id": "GoogleCloudAiplatformV1ExplanationMetadataOutputMetadata", "description": "Metadata of the prediction output to be explained.", "type": "object" }, "GoogleCloudAiplatformV1VertexRagStore": { "description": "Retrieve from Vertex RAG Store for grounding.", "type": "object", "properties": { "ragResources": { "items": { "$ref": "GoogleCloudAiplatformV1VertexRagStoreRagResource" }, "type": "array", "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." }, "vectorDistanceThreshold": { "format": "double", "deprecated": true, "description": "Optional. Only return results with vector distance smaller than the threshold.", "type": "number" }, "ragRetrievalConfig": { "description": "Optional. The retrieval config for the Rag query.", "$ref": "GoogleCloudAiplatformV1RagRetrievalConfig" }, "similarityTopK": { "description": "Optional. Number of top k results to return from the selected corpora.", "deprecated": true, "type": "integer", "format": "int32" } }, "id": "GoogleCloudAiplatformV1VertexRagStore" }, "GoogleCloudAiplatformV1ImportFeatureValuesRequestFeatureSpec": { "id": "GoogleCloudAiplatformV1ImportFeatureValuesRequestFeatureSpec", "properties": { "sourceField": { "description": "Source column to get the Feature values from. If not set, uses the column with the same name as the Feature ID.", "type": "string" }, "id": { "type": "string", "description": "Required. ID of the Feature to import values of. This Feature must exist in the target EntityType, or the request will fail." } }, "description": "Defines the Feature value(s) to import.", "type": "object" }, "GoogleCloudAiplatformV1PauseSandboxEnvironmentRequest": { "properties": {}, "type": "object", "id": "GoogleCloudAiplatformV1PauseSandboxEnvironmentRequest", "description": "Request message for SandboxEnvironmentService.PauseSandboxEnvironment." }, "GoogleCloudAiplatformV1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies": { "id": "GoogleCloudAiplatformV1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies", "properties": { "trainingStats": { "description": "Stats calculated for the Training Dataset.", "$ref": "GoogleCloudAiplatformV1FeatureStatsAnomaly" }, "threshold": { "description": "Threshold for anomaly detection.", "$ref": "GoogleCloudAiplatformV1ThresholdConfig" }, "predictionStats": { "items": { "$ref": "GoogleCloudAiplatformV1FeatureStatsAnomaly" }, "description": "A list of historical stats generated by different time window's Prediction Dataset.", "type": "array" }, "featureDisplayName": { "type": "string", "description": "Display Name of the Feature." } }, "type": "object", "description": "Historical Stats (and Anomalies) for a specific Feature." }, "GoogleCloudAiplatformV1ImageConfig": { "properties": { "personGeneration": { "type": "string", "description": "Optional. Controls whether the model can generate people.", "enum": [ "PERSON_GENERATION_UNSPECIFIED", "ALLOW_ALL", "ALLOW_ADULT", "ALLOW_NONE" ], "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." ] }, "prominentPeople": { "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.", "enum": [ "PROMINENT_PEOPLE_UNSPECIFIED", "ALLOW_PROMINENT_PEOPLE", "BLOCK_PROMINENT_PEOPLE" ], "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." ], "type": "string" }, "imageOutputOptions": { "description": "Optional. The image output format for generated images.", "$ref": "GoogleCloudAiplatformV1ImageConfigImageOutputOptions" }, "imageSize": { "type": "string", "description": "Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`." }, "aspectRatio": { "type": "string", "description": "Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: \"1:1\" \"2:3\", \"3:2\" \"3:4\", \"4:3\" \"4:5\", \"5:4\" \"9:16\", \"16:9\" \"21:9\"" } }, "id": "GoogleCloudAiplatformV1ImageConfig", "type": "object", "description": "Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people." }, "GoogleCloudAiplatformV1ConversationTurn": { "description": "Represents a single turn/invocation in the conversation.", "properties": { "turnId": { "description": "Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.", "type": "string" }, "turnIndex": { "description": "Required. The 0-based index of the turn in the conversation sequence.", "type": "integer", "format": "int32" }, "events": { "type": "array", "description": "Optional. The list of events that occurred during this turn.", "items": { "$ref": "GoogleCloudAiplatformV1AgentEvent" } } }, "id": "GoogleCloudAiplatformV1ConversationTurn", "type": "object" }, "GenaiVertexV1ImageContent": { "description": "An image content block. ", "type": "object", "id": "GenaiVertexV1ImageContent", "properties": { "mimeTypeString": { "description": "Flexible MIME type string of the image, superseding mime_type = 1. Note: Bespoke logic in the GAOS parser/serializer maps this to the \"mime_type\" JSON key.", "type": "string" }, "uri": { "type": "string", "description": "The URI of the image." }, "data": { "type": "string", "format": "byte", "description": "The image content." }, "resolution": { "type": "string", "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "LOW", "MEDIUM", "HIGH", "ULTRA_HIGH" ], "description": "The resolution of the media.", "enumDescriptions": [ "Default value. This value is unused.", "Low resolution.", "Medium resolution.", "High resolution.", "Ultra high resolution." ] } } }, "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecAgentConfigSourceAdkConfig": { "description": "Configuration for the Agent Development Kit (ADK).", "type": "object", "properties": { "jsonConfig": { "description": "Required. The value of the ADK config in JSON format.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "id": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecAgentConfigSourceAdkConfig" }, "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecRange": { "type": "object", "description": "A range of values for slice(s). `low` is inclusive, `high` is exclusive.", "id": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecRange", "properties": { "high": { "format": "float", "type": "number", "description": "Exclusive high value for the range." }, "low": { "type": "number", "description": "Inclusive low value for the range.", "format": "float" } } }, "GoogleCloudAiplatformV1IntermediateExtractedMemory": { "description": "An extracted memory that is the intermediate result before consolidation.", "type": "object", "id": "GoogleCloudAiplatformV1IntermediateExtractedMemory", "properties": { "fact": { "readOnly": true, "description": "Output only. Represents the fact of the extracted memory.", "type": "string" }, "context": { "readOnly": true, "type": "string", "description": "Output only. Represents the explanation of why the information was extracted from the source content." }, "structuredData": { "readOnly": true, "type": "object", "description": "Output only. Represents the structured value of the extracted memory.", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "GenaiVertexV1Content": { "type": "object", "id": "GenaiVertexV1Content", "properties": { "document": { "$ref": "GenaiVertexV1DocumentContent" }, "audio": { "$ref": "GenaiVertexV1AudioContent" }, "video": { "$ref": "GenaiVertexV1VideoContent" }, "image": { "$ref": "GenaiVertexV1ImageContent" }, "text": { "$ref": "GenaiVertexV1TextContent" } }, "description": "The content of the response." }, "GenaiVertexV1UrlContextResultContentUrlContextResult": { "properties": { "status": { "description": "The status of the URL retrieval.", "enumDescriptions": [ "Unspecified status. This value should not be used.", "Url retrieval is successful.", "Url retrieval is failed due to error.", "Url retrieval is failed because the content is behind paywall.", "Url retrieval is failed because the content is unsafe." ], "type": "string", "enum": [ "STATUS_UNSPECIFIED", "SUCCESS", "ERROR", "PAYWALL", "UNSAFE" ] }, "url": { "description": "The URL that was fetched.", "type": "string" } }, "description": "The result of the URL context.", "id": "GenaiVertexV1UrlContextResultContentUrlContextResult", "type": "object" }, "GoogleCloudAiplatformV1SearchDataItemsResponse": { "id": "GoogleCloudAiplatformV1SearchDataItemsResponse", "properties": { "dataItemViews": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1DataItemView" }, "description": "The DataItemViews read." }, "nextPageToken": { "type": "string", "description": "A token to retrieve next page of results. Pass to SearchDataItemsRequest.page_token to obtain that page." } }, "description": "Response message for DatasetService.SearchDataItems.", "type": "object" }, "GoogleCloudAiplatformV1GoogleSearchRetrieval": { "description": "Tool to retrieve public web data for grounding, powered by Google.", "properties": { "dynamicRetrievalConfig": { "description": "Specifies the dynamic retrieval configuration for the given source.", "$ref": "GoogleCloudAiplatformV1DynamicRetrievalConfig" } }, "id": "GoogleCloudAiplatformV1GoogleSearchRetrieval", "type": "object" }, "CloudAiLargeModelsVisionGenerateVideoExperimentsOutpaintConfig": { "properties": { "inputFrames": { "items": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsOutpaintConfigFrameSource" }, "type": "array", "description": "The input frames for outpainting. Required." }, "outputSpec": { "enumDescriptions": [ "", "High spec: 1920x1072 resolution, 72 total frames.", "Medium spec: 1280x720 resolution, 192 total frames.", "Low spec: 960x544 resolution, 432 total frames.", "Medium spec at 1280x720, 144 total frames. Shorter than OUTPUT_SPEC_1280X720x192 and higher quality at the same resolution." ], "enum": [ "OUTPUT_SPEC_UNSPECIFIED", "OUTPUT_SPEC_1920X1072x72", "OUTPUT_SPEC_1280X720x192", "OUTPUT_SPEC_960X544x432", "OUTPUT_SPEC_1280X720x144" ], "description": "The output specification (defines target resolution and frame count). Required.", "type": "string" } }, "description": "Config for Outpainting task.", "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsOutpaintConfig", "type": "object" }, "GoogleCloudAiplatformV1EventActions": { "type": "object", "id": "GoogleCloudAiplatformV1EventActions", "properties": { "skipSummarization": { "description": "Optional. If true, it won't call model to summarize function response. Only used for function_response event.", "type": "boolean" }, "escalate": { "description": "Optional. The agent is escalating to a higher level agent.", "type": "boolean" }, "requestedAuthConfigs": { "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "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.", "type": "object" }, "transferAgent": { "type": "string", "description": "Optional. If set, the event transfers to the specified agent." }, "artifactDelta": { "type": "object", "additionalProperties": { "type": "integer", "format": "int32" }, "description": "Optional. Indicates that the event is updating an artifact. key is the filename, value is the version." }, "stateDelta": { "additionalProperties": { "type": "any", "description": "Properties of the object." }, "type": "object", "description": "Optional. Indicates that the event is updating the state with the given delta." } }, "description": "Actions are parts of events that are executed by the agent." }, "GoogleCloudAiplatformV1AppendEventResponse": { "properties": {}, "description": "Response message for SessionService.AppendEvent.", "type": "object", "id": "GoogleCloudAiplatformV1AppendEventResponse" }, "GenaiVertexV1ResponseFormat": { "type": "object", "properties": { "text": { "$ref": "GenaiVertexV1TextResponseFormat" }, "image": { "$ref": "GenaiVertexV1ImageResponseFormat" }, "structValue": { "description": "Multi-discriminator values is already enabled in GAOS", "$ref": "GenaiVertexV1Struct" }, "audio": { "$ref": "GenaiVertexV1AudioResponseFormat" }, "video": { "$ref": "GenaiVertexV1VideoResponseFormat" } }, "id": "GenaiVertexV1ResponseFormat" }, "GoogleCloudAiplatformV1EvaluationDataset": { "type": "object", "description": "The dataset used for evaluation.", "id": "GoogleCloudAiplatformV1EvaluationDataset", "properties": { "gcsSource": { "description": "Cloud storage source holds the dataset. Currently only one Cloud Storage file path is supported.", "$ref": "GoogleCloudAiplatformV1GcsSource" }, "bigquerySource": { "description": "BigQuery source holds the dataset.", "$ref": "GoogleCloudAiplatformV1BigQuerySource" } } }, "GoogleCloudAiplatformV1ImportEvaluationSetRequestImportSchemaConfig": { "properties": { "dataFormat": { "description": "Required. The format of the input data.", "type": "string", "enumDescriptions": [ "Unspecified data format.", "OpenTelemetry Protobuf format (e.g. TracesData).", "OpenTelemetry JSON format.", "JSONL format mapping directly to EvaluationItem schema." ], "enum": [ "DATA_FORMAT_UNSPECIFIED", "OTEL_PROTO", "OTEL_JSON", "JSONL" ] }, "dataFormatVersion": { "type": "string", "description": "Optional. Version of the data format." } }, "description": "Configuration for the input data format.", "id": "GoogleCloudAiplatformV1ImportEvaluationSetRequestImportSchemaConfig", "type": "object" }, "GoogleCloudAiplatformV1SecretRef": { "description": "Reference to a secret stored in the Cloud Secret Manager that will provide the value for this environment variable.", "id": "GoogleCloudAiplatformV1SecretRef", "type": "object", "properties": { "secret": { "type": "string", "description": "Required. The name of the secret in Cloud Secret Manager. Format: {secret_name}." }, "version": { "type": "string", "description": "The Cloud Secret Manager secret version. Can be 'latest' for the latest version, an integer for a specific version, or a version alias." } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata": { "type": "object", "properties": { "successfulStopReason": { "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." ], "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" }, "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" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata" }, "GenaiVertexV1GoogleMapsResultContentGoogleMapsResultPlaces": { "id": "GenaiVertexV1GoogleMapsResultContentGoogleMapsResultPlaces", "properties": { "name": { "description": "Title of the place.", "type": "string" }, "reviewSnippets": { "type": "array", "items": { "$ref": "GenaiVertexV1ReviewSnippet" }, "description": "Snippets of reviews that are used to generate answers about the features of a given place in Google Maps." }, "placeId": { "description": "The ID of the place, in `places/{place_id}` format.", "type": "string" }, "url": { "type": "string", "description": "URI reference of the place." } }, "type": "object" }, "GenaiVertexV1TextDelta": { "properties": { "text": { "type": "string" } }, "type": "object", "id": "GenaiVertexV1TextDelta" }, "GoogleCloudAiplatformV1TrajectoryPrecisionInput": { "id": "GoogleCloudAiplatformV1TrajectoryPrecisionInput", "type": "object", "properties": { "metricSpec": { "description": "Required. Spec for TrajectoryPrecision metric.", "$ref": "GoogleCloudAiplatformV1TrajectoryPrecisionSpec" }, "instances": { "items": { "$ref": "GoogleCloudAiplatformV1TrajectoryPrecisionInstance" }, "description": "Required. Repeated TrajectoryPrecision instance.", "type": "array" } }, "description": "Instances and metric spec for TrajectoryPrecision metric." }, "GoogleCloudAiplatformV1MemoryBankCustomizationConfigMemoryTopicManagedMemoryTopic": { "type": "object", "properties": { "managedTopicEnum": { "type": "string", "enum": [ "MANAGED_TOPIC_ENUM_UNSPECIFIED", "USER_PERSONAL_INFO", "USER_PREFERENCES", "KEY_CONVERSATION_DETAILS", "EXPLICIT_INSTRUCTIONS" ], "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": "Required. Represents the managed topic." } }, "description": "A managed memory topic defined by the system.", "id": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigMemoryTopicManagedMemoryTopic" }, "GoogleCloudAiplatformV1GroundednessResult": { "type": "object", "description": "Spec for groundedness result.", "properties": { "score": { "type": "number", "readOnly": true, "description": "Output only. Groundedness score.", "format": "float" }, "explanation": { "description": "Output only. Explanation for groundedness score.", "readOnly": true, "type": "string" }, "confidence": { "readOnly": true, "description": "Output only. Confidence for groundedness score.", "type": "number", "format": "float" } }, "id": "GoogleCloudAiplatformV1GroundednessResult" }, "GoogleCloudAiplatformV1RebootPersistentResourceRequest": { "id": "GoogleCloudAiplatformV1RebootPersistentResourceRequest", "type": "object", "properties": {}, "description": "Request message for PersistentResourceService.RebootPersistentResource." }, "GoogleCloudAiplatformV1ListTensorboardsResponse": { "description": "Response message for TensorboardService.ListTensorboards.", "properties": { "tensorboards": { "items": { "$ref": "GoogleCloudAiplatformV1Tensorboard" }, "description": "The Tensorboards mathching the request.", "type": "array" }, "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": "GoogleCloudAiplatformV1ListTensorboardsResponse", "type": "object" }, "GoogleCloudAiplatformV1Session": { "description": "A session contains a set of actions between users and Vertex agents.", "type": "object", "properties": { "labels": { "type": "object", "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.", "additionalProperties": { "type": "string" } }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when the session was updated." }, "userId": { "type": "string", "description": "Required. Immutable. String id provided by the user" }, "sessionState": { "description": "Optional. Session specific memory which stores key conversation points.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "ttl": { "description": "Optional. Input only. The TTL for this session. The minimum value is 24 hours.", "type": "string", "format": "google-duration" }, "name": { "description": "Identifier. The resource name of the session. Format: 'projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}'.", "type": "string" }, "displayName": { "description": "Optional. The display name of the session.", "type": "string" }, "expireTime": { "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.", "type": "string", "format": "google-datetime" }, "createTime": { "format": "google-datetime", "description": "Output only. Timestamp when the session was created.", "type": "string", "readOnly": true } }, "id": "GoogleCloudAiplatformV1Session" }, "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigAutoraterConfig": { "type": "object", "description": "The autorater config used for the evaluation run.", "id": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigAutoraterConfig", "properties": { "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" }, "generationConfig": { "$ref": "GoogleCloudAiplatformV1GenerationConfig", "description": "Optional. Configuration options for model generation and outputs." }, "sampleCount": { "format": "int32", "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.", "type": "integer" } } }, "GoogleCloudAiplatformV1ExamplesRestrictionsNamespace": { "properties": { "deny": { "type": "array", "description": "The list of deny tags.", "items": { "type": "string" } }, "namespaceName": { "type": "string", "description": "The namespace name." }, "allow": { "description": "The list of allowed tags.", "type": "array", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1ExamplesRestrictionsNamespace", "description": "Restrictions namespace for example-based explanations overrides.", "type": "object" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextExtractionEvaluationMetrics": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextExtractionEvaluationMetrics", "properties": { "confusionMatrix": { "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.", "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix" }, "confidenceMetrics": { "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics" }, "description": "Metrics that have confidence thresholds. Precision-recall curve can be derived from them.", "type": "array" } }, "type": "object", "description": "Metrics for text extraction evaluation results." }, "GoogleCloudAiplatformV1Claim": { "id": "GoogleCloudAiplatformV1Claim", "type": "object", "description": "Claim that is extracted from the input text and facts that support it.", "properties": { "endIndex": { "description": "Index in the input text where the claim ends (exclusive).", "type": "integer", "format": "int32" }, "factIndexes": { "items": { "type": "integer", "format": "int32" }, "description": "Indexes of the facts supporting this claim.", "type": "array" }, "startIndex": { "description": "Index in the input text where the claim starts (inclusive).", "type": "integer", "format": "int32" }, "score": { "description": "Confidence score of this corroboration.", "type": "number", "format": "float" } } }, "GoogleCloudAiplatformV1RetrieveContextsRequestVertexRagStoreRagResource": { "description": "The definition of the Rag resource.", "type": "object", "id": "GoogleCloudAiplatformV1RetrieveContextsRequestVertexRagStoreRagResource", "properties": { "ragFileIds": { "type": "array", "description": "Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.", "items": { "type": "string" } }, "ragCorpus": { "description": "Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "type": "string" } } }, "GoogleCloudAiplatformV1BatchMigrateResourcesRequest": { "description": "Request message for MigrationService.BatchMigrateResources.", "id": "GoogleCloudAiplatformV1BatchMigrateResourcesRequest", "properties": { "migrateResourceRequests": { "items": { "$ref": "GoogleCloudAiplatformV1MigrateResourceRequest" }, "type": "array", "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": "object" }, "GoogleCloudAiplatformV1DataItem": { "description": "A piece of data in a Dataset. Could be an image, a video, a document or plain text.", "id": "GoogleCloudAiplatformV1DataItem", "type": "object", "properties": { "labels": { "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.", "type": "object", "additionalProperties": { "type": "string" } }, "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" }, "updateTime": { "type": "string", "description": "Output only. Timestamp when this DataItem was last updated.", "readOnly": true, "format": "google-datetime" }, "name": { "type": "string", "description": "Output only. The resource name of the DataItem.", "readOnly": true }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "createTime": { "description": "Output only. Timestamp when this DataItem was created.", "format": "google-datetime", "readOnly": true, "type": "string" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true } } }, "GoogleCloudAiplatformV1StreamingPredictResponse": { "id": "GoogleCloudAiplatformV1StreamingPredictResponse", "type": "object", "properties": { "outputs": { "description": "The prediction output.", "items": { "$ref": "GoogleCloudAiplatformV1Tensor" }, "type": "array" }, "parameters": { "description": "The parameters that govern the prediction.", "$ref": "GoogleCloudAiplatformV1Tensor" } }, "description": "Response message for PredictionService.StreamingPredict." }, "GoogleCloudAiplatformV1SharePointSourcesSharePointSource": { "description": "An individual SharePointSource.", "id": "GoogleCloudAiplatformV1SharePointSourcesSharePointSource", "properties": { "clientSecret": { "description": "The application secret for the app registered in Azure.", "$ref": "GoogleCloudAiplatformV1ApiAuthApiKeyConfig" }, "driveName": { "type": "string", "description": "The name of the drive to download from." }, "clientId": { "type": "string", "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." }, "driveId": { "type": "string", "description": "The ID of the drive to download from." }, "sharepointFolderPath": { "description": "The path of the SharePoint folder to download from.", "type": "string" }, "tenantId": { "description": "Unique identifier of the Azure Active Directory Instance.", "type": "string" }, "sharepointFolderId": { "type": "string", "description": "The ID of the SharePoint folder to download from." }, "sharepointSiteName": { "type": "string", "description": "The name of the SharePoint site to download from. This can be the site name or the site id." }, "fileId": { "description": "Output only. The SharePoint file id. Output only.", "readOnly": true, "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1FeatureValue": { "type": "object", "id": "GoogleCloudAiplatformV1FeatureValue", "description": "Value for a feature.", "properties": { "stringArrayValue": { "$ref": "GoogleCloudAiplatformV1StringArray", "description": "A list of string type feature value." }, "doubleValue": { "description": "Double type feature value.", "format": "double", "type": "number" }, "int64ArrayValue": { "description": "A list of int64 type feature value.", "$ref": "GoogleCloudAiplatformV1Int64Array" }, "metadata": { "$ref": "GoogleCloudAiplatformV1FeatureValueMetadata", "description": "Metadata of feature value." }, "stringValue": { "description": "String feature value.", "type": "string" }, "structValue": { "$ref": "GoogleCloudAiplatformV1StructValue", "description": "A struct type feature value." }, "doubleArrayValue": { "$ref": "GoogleCloudAiplatformV1DoubleArray", "description": "A list of double type feature value." }, "boolArrayValue": { "description": "A list of bool type feature value.", "$ref": "GoogleCloudAiplatformV1BoolArray" }, "boolValue": { "description": "Bool type feature value.", "type": "boolean" }, "int64Value": { "type": "string", "description": "Int64 feature value.", "format": "int64" }, "bytesValue": { "format": "byte", "description": "Bytes feature value.", "type": "string" } } }, "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair": { "properties": { "value": { "description": "Feature value.", "$ref": "GoogleCloudAiplatformV1FeatureValue" }, "name": { "type": "string", "description": "Feature short name." } }, "id": "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair", "description": "Feature name & value pair.", "type": "object" }, "GoogleCloudAiplatformV1UndeployModelResponse": { "properties": {}, "type": "object", "description": "Response message for EndpointService.UndeployModel.", "id": "GoogleCloudAiplatformV1UndeployModelResponse" }, "GoogleCloudAiplatformV1ExportDataOperationMetadata": { "description": "Runtime operation information for DatasetService.ExportData.", "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" }, "gcsOutputDirectory": { "description": "A Google Cloud Storage directory which path ends with '/'. The exported data is stored in the directory.", "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1ExportDataOperationMetadata" }, "GoogleCloudAiplatformV1IngestionDirectContentsSource": { "description": "Ingest events directly from the request.", "type": "object", "properties": { "events": { "items": { "$ref": "GoogleCloudAiplatformV1IngestionDirectContentsSourceEvent" }, "description": "Required. The events to ingest.", "type": "array" } }, "id": "GoogleCloudAiplatformV1IngestionDirectContentsSource" }, "GoogleCloudAiplatformV1LargeModelReference": { "description": "Contains information about the Large Model.", "properties": { "name": { "type": "string", "description": "Required. The unique name of the large Foundation or pre-built model. Like \"chat-bison\", \"text-bison\". Or model name with version ID, like \"chat-bison@001\", \"text-bison@005\", etc." } }, "id": "GoogleCloudAiplatformV1LargeModelReference", "type": "object" }, "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessResult": { "properties": { "explanation": { "readOnly": true, "type": "string", "description": "Output only. Explanation for question answering correctness score." }, "score": { "format": "float", "type": "number", "description": "Output only. Question Answering Correctness score.", "readOnly": true }, "confidence": { "readOnly": true, "type": "number", "description": "Output only. Confidence for question answering correctness score.", "format": "float" } }, "id": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessResult", "description": "Spec for question answering correctness result.", "type": "object" }, "GoogleCloudAiplatformV1SummarizationQualityInput": { "description": "Input for summarization quality metric.", "id": "GoogleCloudAiplatformV1SummarizationQualityInput", "type": "object", "properties": { "metricSpec": { "description": "Required. Spec for summarization quality score metric.", "$ref": "GoogleCloudAiplatformV1SummarizationQualitySpec" }, "instance": { "description": "Required. Summarization quality instance.", "$ref": "GoogleCloudAiplatformV1SummarizationQualityInstance" } } }, "GoogleCloudAiplatformV1FasterDeploymentConfig": { "type": "object", "properties": { "fastTryoutEnabled": { "type": "boolean", "description": "If true, enable fast tryout feature for this deployed model." } }, "id": "GoogleCloudAiplatformV1FasterDeploymentConfig", "description": "Configuration for faster model deployment." }, "GoogleCloudAiplatformV1ListTensorboardRunsResponse": { "id": "GoogleCloudAiplatformV1ListTensorboardRunsResponse", "type": "object", "description": "Response message for TensorboardService.ListTensorboardRuns.", "properties": { "tensorboardRuns": { "type": "array", "description": "The TensorboardRuns mathching the request.", "items": { "$ref": "GoogleCloudAiplatformV1TensorboardRun" } }, "nextPageToken": { "type": "string", "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." } } }, "GoogleCloudAiplatformV1BatchReadTensorboardTimeSeriesDataResponse": { "description": "Response message for TensorboardService.BatchReadTensorboardTimeSeriesData.", "id": "GoogleCloudAiplatformV1BatchReadTensorboardTimeSeriesDataResponse", "type": "object", "properties": { "timeSeriesData": { "description": "The returned time series data.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1TimeSeriesData" } } } }, "GoogleCloudAiplatformV1ExportModelResponse": { "description": "Response message of ModelService.ExportModel operation.", "properties": {}, "id": "GoogleCloudAiplatformV1ExportModelResponse", "type": "object" }, "GoogleCloudAiplatformV1CreateNotebookRuntimeTemplateOperationMetadata": { "description": "Metadata information for NotebookService.CreateNotebookRuntimeTemplate.", "type": "object", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1CreateNotebookRuntimeTemplateOperationMetadata" }, "GoogleCloudAiplatformV1Index": { "type": "object", "properties": { "updateTime": { "format": "google-datetime", "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.", "readOnly": true, "type": "string" }, "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" }, "labels": { "type": "object", "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.", "additionalProperties": { "type": "string" } }, "metadataSchemaUri": { "type": "string", "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." }, "metadata": { "description": "An additional information about the Index; the schema of the metadata can be found in metadata_schema.", "type": "any" }, "description": { "type": "string", "description": "The description of the Index." }, "satisfiesPzs": { "readOnly": true, "description": "Output only. Reserved for future use.", "type": "boolean" }, "deployedIndexes": { "readOnly": true, "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.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1DeployedIndexRef" } }, "indexStats": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1IndexStats", "description": "Output only. Stats of the index resource." }, "name": { "description": "Output only. The resource name of the Index.", "readOnly": true, "type": "string" }, "satisfiesPzi": { "readOnly": true, "description": "Output only. Reserved for future use.", "type": "boolean" }, "createTime": { "description": "Output only. Timestamp when this Index was created.", "readOnly": true, "format": "google-datetime", "type": "string" }, "encryptionSpec": { "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.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "etag": { "type": "string", "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." }, "indexUpdateMethod": { "description": "Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default.", "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." ], "enum": [ "INDEX_UPDATE_METHOD_UNSPECIFIED", "BATCH_UPDATE", "STREAM_UPDATE" ], "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": "GoogleCloudAiplatformV1Index" }, "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataRequest": { "id": "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataRequest", "properties": { "filter": { "description": "Exports the TensorboardTimeSeries' data that match the filter expression.", "type": "string" }, "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" }, "orderBy": { "description": "Field to use to sort the TensorboardTimeSeries' data. By default, TensorboardTimeSeries' data is returned in a pseudo random order.", "type": "string" }, "pageSize": { "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.", "format": "int32", "type": "integer" } }, "description": "Request message for TensorboardService.ExportTensorboardTimeSeriesData.", "type": "object" }, "GoogleCloudAiplatformV1UrlContext": { "id": "GoogleCloudAiplatformV1UrlContext", "description": "Tool to support URL context.", "properties": {}, "type": "object" }, "GoogleCloudAiplatformV1TrajectorySingleToolUseSpec": { "id": "GoogleCloudAiplatformV1TrajectorySingleToolUseSpec", "properties": { "toolName": { "type": "string", "description": "Required. Spec for tool name to be checked for in the predicted trajectory." } }, "description": "Spec for TrajectorySingleToolUse metric - returns 1 if tool is present in the predicted trajectory, else 0.", "type": "object" }, "GoogleCloudAiplatformV1SchemaVideoClassificationAnnotation": { "type": "object", "properties": { "timeSegment": { "description": "This Annotation applies to the time period represented by the TimeSegment. If it's not set, the Annotation applies to the whole video.", "$ref": "GoogleCloudAiplatformV1SchemaTimeSegment" }, "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" } }, "description": "Annotation details specific to video classification.", "id": "GoogleCloudAiplatformV1SchemaVideoClassificationAnnotation" }, "GoogleCloudAiplatformV1EvaluationResult": { "properties": { "metadata": { "description": "Optional. Metadata about the evaluation result.", "type": "any" }, "metric": { "type": "string", "description": "Required. The metric that was evaluated." }, "candidateResults": { "items": { "$ref": "GoogleCloudAiplatformV1CandidateResult" }, "description": "Optional. The results for the metric.", "type": "array" }, "evaluationRun": { "type": "string", "description": "Required. The evaluation run that was used to generate the result. Format: projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}" }, "evaluationRequest": { "type": "string", "description": "Required. The request item that was evaluated. Format: projects/{project}/locations/{location}/evaluationItems/{evaluation_item}" }, "request": { "description": "Required. The request that was evaluated.", "$ref": "GoogleCloudAiplatformV1EvaluationRequest" } }, "id": "GoogleCloudAiplatformV1EvaluationResult", "description": "Evaluation result.", "type": "object" }, "GoogleCloudAiplatformV1FeatureOnlineStoreDedicatedServingEndpoint": { "properties": { "privateServiceConnectConfig": { "$ref": "GoogleCloudAiplatformV1PrivateServiceConnectConfig", "description": "Optional. Private service connect config. The private service connection is available only for Optimized storage type, not for embedding management now. If PrivateServiceConnectConfig.enable_private_service_connect set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint." }, "publicEndpointDomainName": { "type": "string", "readOnly": true, "description": "Output only. This field will be populated with the domain name to use for this FeatureOnlineStore" }, "serviceAttachment": { "description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled and after FeatureViewSync is created.", "readOnly": true, "type": "string" } }, "type": "object", "description": "The dedicated serving endpoint for this FeatureOnlineStore. Only need to set when you choose Optimized storage type. Public endpoint is provisioned by default.", "id": "GoogleCloudAiplatformV1FeatureOnlineStoreDedicatedServingEndpoint" }, "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline": { "description": "Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores.", "properties": { "gcs": { "description": "Cloud Storage location for BatchExplain output.", "$ref": "GoogleCloudAiplatformV1GcsDestination" }, "predictionFormat": { "enum": [ "PREDICTION_FORMAT_UNSPECIFIED", "JSONL", "BIGQUERY" ], "type": "string", "enumDescriptions": [ "Should not be set.", "Predictions are in JSONL files.", "Predictions are in BigQuery." ], "description": "The storage format of the predictions generated BatchPrediction job." }, "bigquery": { "$ref": "GoogleCloudAiplatformV1BigQueryDestination", "description": "BigQuery location for BatchExplain output." } }, "type": "object", "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline" }, "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpec": { "properties": { "configs": { "description": "Mapping configuration for this SliceSpec. The key is the name of the feature. By default, the key will be prefixed by \"instance\" as a dictionary prefix for Vertex Batch Predictions output format.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpecSliceConfig" } } }, "description": "Specification for how the data should be sliced.", "type": "object", "id": "GoogleCloudAiplatformV1ModelEvaluationSliceSliceSliceSpec" }, "GoogleCloudAiplatformV1AddContextChildrenRequest": { "type": "object", "description": "Request message for MetadataService.AddContextChildren.", "properties": { "childContexts": { "type": "array", "items": { "type": "string" }, "description": "The resource names of the child Contexts." } }, "id": "GoogleCloudAiplatformV1AddContextChildrenRequest" }, "GenaiVertexV1RetrievalResultStep": { "properties": { "isError": { "type": "boolean", "description": "Whether the retrieval resulted in an error." } }, "description": "Vertex Retrieval result step. Used by Vertex Retrieval tools such as Parallel AI, Exa AI, Vertex AI Search, etc.", "id": "GenaiVertexV1RetrievalResultStep", "type": "object" }, "GoogleCloudAiplatformV1EvaluationRequest": { "properties": { "rubrics": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1RubricGroup" }, "description": "Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group." }, "prompt": { "$ref": "GoogleCloudAiplatformV1EvaluationPrompt", "description": "Optional. The request/prompt to evaluate." }, "goldenResponse": { "description": "Optional. The Ideal response or ground truth.", "$ref": "GoogleCloudAiplatformV1CandidateResponse" }, "candidateResponses": { "items": { "$ref": "GoogleCloudAiplatformV1CandidateResponse" }, "description": "Optional. Responses from model under test and other baseline models for comparison.", "type": "array" } }, "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`. Metrics receive each candidate as an `EvaluationInstance`, whose fields are the names metrics can reference: `prompt` -\u003e `prompt`, the candidate -\u003e `response` (or `agent_eval_data` for `agent_data`), `golden_response` -\u003e `reference`, `rubrics` -\u003e `rubric_groups`, and `prompt.prompt_template_data.values` and `extra_context` -\u003e `other_data`.", "type": "object", "id": "GoogleCloudAiplatformV1EvaluationRequest" }, "GoogleCloudAiplatformV1ImageResponseFormat": { "properties": { "aspectRatio": { "enumDescriptions": [ "Default value. This value is unused.", "1:1 aspect ratio.", "2:3 aspect ratio.", "3:2 aspect ratio.", "3:4 aspect ratio.", "4:3 aspect ratio.", "4:5 aspect ratio.", "5:4 aspect ratio.", "9:16 aspect ratio.", "16:9 aspect ratio.", "21:9 aspect ratio.", "1:8 aspect ratio.", "8:1 aspect ratio.", "1:4 aspect ratio.", "4:1 aspect ratio." ], "type": "string", "description": "Optional. The aspect ratio for the image output.", "enum": [ "ASPECT_RATIO_UNSPECIFIED", "ASPECT_RATIO_ONE_BY_ONE", "ASPECT_RATIO_TWO_BY_THREE", "ASPECT_RATIO_THREE_BY_TWO", "ASPECT_RATIO_THREE_BY_FOUR", "ASPECT_RATIO_FOUR_BY_THREE", "ASPECT_RATIO_FOUR_BY_FIVE", "ASPECT_RATIO_FIVE_BY_FOUR", "ASPECT_RATIO_NINE_BY_SIXTEEN", "ASPECT_RATIO_SIXTEEN_BY_NINE", "ASPECT_RATIO_TWENTY_ONE_BY_NINE", "ASPECT_RATIO_ONE_BY_EIGHT", "ASPECT_RATIO_EIGHT_BY_ONE", "ASPECT_RATIO_ONE_BY_FOUR", "ASPECT_RATIO_FOUR_BY_ONE" ] }, "delivery": { "enumDescriptions": [ "Default value. This value is unused.", "Generated bytes are returned inline in the response.", "Generated content is stored and a URI is returned." ], "type": "string", "enum": [ "DELIVERY_UNSPECIFIED", "INLINE", "URI" ], "description": "Optional. Delivery mode for the generated content." }, "imageSize": { "description": "Optional. The size of the image output.", "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "512px image size.", "1K image size.", "2K image size.", "4K image size." ], "enum": [ "IMAGE_SIZE_UNSPECIFIED", "IMAGE_SIZE_FIVE_TWELVE", "IMAGE_SIZE_ONE_K", "IMAGE_SIZE_TWO_K", "IMAGE_SIZE_FOUR_K" ] }, "mimeType": { "enum": [ "MIME_TYPE_UNSPECIFIED", "IMAGE_JPEG" ], "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "JPEG image format." ], "description": "Optional. The MIME type of the image output." } }, "description": "Configuration for image-specific output formatting.", "id": "GoogleCloudAiplatformV1ImageResponseFormat", "type": "object" }, "GenaiVertexV1VideoResponseFormat": { "type": "object", "id": "GenaiVertexV1VideoResponseFormat", "properties": { "delivery": { "enum": [ "DELIVERY_UNSPECIFIED", "INLINE", "URI" ], "enumDescriptions": [ "Default value. This value is unused.", "Video data is returned inline in the response.", "Video data is returned as a URI." ], "type": "string", "description": "The delivery mode for the video output." }, "aspectRatio": { "description": "The aspect ratio for the video output.", "enum": [ "ASPECT_RATIO_UNSPECIFIED", "ASPECT_RATIO_SIXTEEN_BY_NINE", "ASPECT_RATIO_NINE_BY_SIXTEEN" ], "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "16:9 aspect ratio.", "9:16 aspect ratio." ] }, "gcsUri": { "description": "The Cloud Storage URI to store the video output. Required for Vertex if delivery mode is URI.", "type": "string" }, "resolution": { "enumDescriptions": [ "Default value. This value is unused.", "360p resolution.", "720p resolution.", "1080p resolution.", "4K resolution." ], "enum": [ "RESOLUTION_UNSPECIFIED", "RESOLUTION_THREE_SIXTY_P", "RESOLUTION_SEVEN_TWENTY_P", "RESOLUTION_TEN_EIGHTY_P", "RESOLUTION_FOUR_K" ], "description": "The video output resolution. Defaults to 720p.", "type": "string" }, "duration": { "description": "The duration for the video output.", "type": "string", "format": "google-duration" } }, "description": "Configuration for video output format." }, "GoogleCloudAiplatformV1PointwiseMetricInput": { "description": "Input for pointwise metric.", "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1PointwiseMetricInstance", "description": "Required. Pointwise metric instance." }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1PointwiseMetricSpec", "description": "Required. Spec for pointwise metric." } }, "type": "object", "id": "GoogleCloudAiplatformV1PointwiseMetricInput" }, "GenaiVertexV1UrlCitation": { "id": "GenaiVertexV1UrlCitation", "description": "A URL citation annotation.", "properties": { "url": { "description": "The URL.", "type": "string" }, "title": { "type": "string", "description": "The title of the URL." } }, "type": "object" }, "GoogleCloudAiplatformV1NotebookExecutionJobWorkbenchRuntimeVmImage": { "description": "The definition of a Compute Engine VM image to run the notebook execution on. Mirrors `google.cloud.notebooks.v2.VmImage`.", "type": "object", "properties": { "family": { "type": "string", "description": "Use this VM image family to find the image; the newest image in this family is used." }, "name": { "description": "Use this VM image name to find the image.", "type": "string" }, "project": { "description": "Required. The name of the Google Cloud project that this VM image belongs to. Format: `{project_id}`.", "type": "string" } }, "id": "GoogleCloudAiplatformV1NotebookExecutionJobWorkbenchRuntimeVmImage" }, "GenaiVertexV1CodeExecution": { "description": "A tool that can be used by the model to execute code.", "id": "GenaiVertexV1CodeExecution", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1ImportRagFilesConfig": { "description": "Config for importing RagFiles.", "properties": { "jiraSource": { "description": "Jira queries with their corresponding authentication.", "$ref": "GoogleCloudAiplatformV1JiraSource" }, "rebuildAnnIndex": { "type": "boolean", "description": "Rebuilds the ANN index to optimize for recall on the imported data. Only applicable for RagCorpora running on RagManagedDb with `retrieval_strategy` set to `ANN`. The rebuild will be performed using the existing ANN config set on the RagCorpus. To change the ANN config, please use the UpdateRagCorpus API. Default is false, i.e., index is not rebuilt." }, "importResultGcsSink": { "$ref": "GoogleCloudAiplatformV1GcsDestination", "description": "The Cloud Storage path to write import result to." }, "importResultBigquerySink": { "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.", "$ref": "GoogleCloudAiplatformV1BigQueryDestination" }, "gcsSource": { "$ref": "GoogleCloudAiplatformV1GcsSource", "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`" }, "slackSource": { "$ref": "GoogleCloudAiplatformV1SlackSource", "description": "Slack channels with their corresponding access tokens." }, "sharePointSources": { "description": "SharePoint sources.", "$ref": "GoogleCloudAiplatformV1SharePointSources" }, "partialFailureBigquerySink": { "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`.", "$ref": "GoogleCloudAiplatformV1BigQueryDestination", "deprecated": true }, "ragFileTransformationConfig": { "description": "Specifies the transformation config for RagFiles.", "$ref": "GoogleCloudAiplatformV1RagFileTransformationConfig" }, "googleDriveSource": { "$ref": "GoogleCloudAiplatformV1GoogleDriveSource", "description": "Google Drive location. Supports importing individual files as well as Google Drive folders." }, "partialFailureGcsSink": { "description": "The Cloud Storage path to write partial failures to. Deprecated. Prefer to use `import_result_gcs_sink`.", "$ref": "GoogleCloudAiplatformV1GcsDestination", "deprecated": true }, "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." }, "ragFileParsingConfig": { "description": "Optional. Specifies the parsing config for RagFiles. RAG will use the default parser if this field is not set.", "$ref": "GoogleCloudAiplatformV1RagFileParsingConfig" } }, "id": "GoogleCloudAiplatformV1ImportRagFilesConfig", "type": "object" }, "GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutput": { "id": "GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutput", "description": "The output of a multi-trial Neural Architecture Search (NAS) jobs.", "properties": { "trainTrials": { "description": "Output only. List of NasTrials that were started as part of train stage.", "items": { "$ref": "GoogleCloudAiplatformV1NasTrial" }, "type": "array", "readOnly": true }, "searchTrials": { "items": { "$ref": "GoogleCloudAiplatformV1NasTrial" }, "readOnly": true, "description": "Output only. List of NasTrials that were started as part of search stage.", "type": "array" } }, "type": "object" }, "GoogleCloudAiplatformV1ListSandboxEnvironmentSnapshotsResponse": { "description": "Response message for SandboxEnvironmentService.ListSandboxEnvironmentSnapshots.", "type": "object", "id": "GoogleCloudAiplatformV1ListSandboxEnvironmentSnapshotsResponse", "properties": { "sandboxEnvironmentSnapshots": { "description": "The SandboxEnvironmentSnapshots matching the request.", "items": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentSnapshot" }, "type": "array" }, "nextPageToken": { "type": "string", "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." } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation", "properties": { "columnName": { "type": "string" } }, "type": "object", "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." }, "GoogleCloudAiplatformV1ListCustomJobsResponse": { "type": "object", "properties": { "customJobs": { "description": "List of CustomJobs in the requested page.", "items": { "$ref": "GoogleCloudAiplatformV1CustomJob" }, "type": "array" }, "nextPageToken": { "type": "string", "description": "A token to retrieve the next page of results. Pass to ListCustomJobsRequest.page_token to obtain that page." } }, "description": "Response message for JobService.ListCustomJobs", "id": "GoogleCloudAiplatformV1ListCustomJobsResponse" }, "GoogleCloudAiplatformV1ListSchedulesResponse": { "type": "object", "description": "Response message for ScheduleService.ListSchedules", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListSchedulesRequest.page_token to obtain that page.", "type": "string" }, "schedules": { "items": { "$ref": "GoogleCloudAiplatformV1Schedule" }, "description": "List of Schedules in the requested page.", "type": "array" } }, "id": "GoogleCloudAiplatformV1ListSchedulesResponse" }, "GoogleCloudAiplatformV1BlurBaselineConfig": { "id": "GoogleCloudAiplatformV1BlurBaselineConfig", "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", "properties": { "maxBlurSigma": { "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", "format": "float" } }, "type": "object" }, "GoogleCloudAiplatformV1ResourcesConsumed": { "id": "GoogleCloudAiplatformV1ResourcesConsumed", "properties": { "replicaHours": { "type": "number", "format": "double", "readOnly": true, "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." } }, "description": "Statistics information about resource consumption.", "type": "object" }, "GoogleCloudAiplatformV1CoherenceInput": { "type": "object", "description": "Input for coherence metric.", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1CoherenceSpec", "description": "Required. Spec for coherence score metric." }, "instance": { "description": "Required. Coherence instance.", "$ref": "GoogleCloudAiplatformV1CoherenceInstance" } }, "id": "GoogleCloudAiplatformV1CoherenceInput" }, "GoogleCloudAiplatformV1EvaluatedAnnotation": { "description": "True positive, false positive, or false negative. EvaluatedAnnotation is only available under ModelEvaluationSlice with slice of `annotationSpec` dimension.", "id": "GoogleCloudAiplatformV1EvaluatedAnnotation", "type": "object", "properties": { "predictions": { "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", "readOnly": true }, "dataItemPayload": { "readOnly": true, "description": "Output only. The data item payload that the Model predicted this EvaluatedAnnotation on.", "type": "any" }, "type": { "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." ], "description": "Output only. Type of the EvaluatedAnnotation.", "type": "string", "enum": [ "EVALUATED_ANNOTATION_TYPE_UNSPECIFIED", "TRUE_POSITIVE", "FALSE_POSITIVE", "FALSE_NEGATIVE" ], "readOnly": true }, "errorAnalysisAnnotations": { "description": "Annotations of model error analysis results.", "items": { "$ref": "GoogleCloudAiplatformV1ErrorAnalysisAnnotation" }, "type": "array" }, "groundTruths": { "type": "array", "readOnly": true, "description": "Output only. The ground truth Annotations, i.e. the Annotations that exist in the test data the Model is evaluated on. For true positive, there is one and only one ground truth annotation, which matches the only prediction in predictions. For false positive, there are zero or more ground truth annotations that are similar to the only prediction in predictions, but not enough for a match. For false negative, there is one and only one ground truth annotation, which doesn't match any predictions created by the model. The schema of the ground truth is stored in ModelEvaluation.annotation_schema_uri", "items": { "type": "any" } }, "evaluatedDataItemViewId": { "readOnly": true, "type": "string", "description": "Output only. ID of the EvaluatedDataItemView under the same ancestor ModelEvaluation. The EvaluatedDataItemView consists of all ground truths and predictions on data_item_payload." }, "explanations": { "description": "Explanations of predictions. Each element of the explanations indicates the explanation for one explanation Method. The attributions list in the EvaluatedAnnotationExplanation.explanation object corresponds to the predictions list. For example, the second element in the attributions list explains the second element in the predictions list.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1EvaluatedAnnotationExplanation" } } } }, "GoogleCloudAiplatformV1ExportFeatureValuesOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Operation metadata for Featurestore export Feature values." } }, "type": "object", "description": "Details of operations that exports Features values.", "id": "GoogleCloudAiplatformV1ExportFeatureValuesOperationMetadata" }, "GenaiVertexV1Function": { "description": "A tool that can be used by the model.", "type": "object", "id": "GenaiVertexV1Function", "properties": { "description": { "description": "A description of the function.", "type": "string" }, "parameters": { "description": "The JSON Schema for the function's parameters.", "$ref": "GenaiVertexV1Value" }, "name": { "description": "The name of the function.", "type": "string" } } }, "GoogleCloudAiplatformV1ListTrainingPipelinesResponse": { "id": "GoogleCloudAiplatformV1ListTrainingPipelinesResponse", "description": "Response message for PipelineService.ListTrainingPipelines", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListTrainingPipelinesRequest.page_token to obtain that page.", "type": "string" }, "trainingPipelines": { "items": { "$ref": "GoogleCloudAiplatformV1TrainingPipeline" }, "description": "List of TrainingPipelines in the requested page.", "type": "array" } }, "type": "object" }, "GoogleCloudAiplatformV1FeatureViewDirectWriteRequest": { "id": "GoogleCloudAiplatformV1FeatureViewDirectWriteRequest", "description": "Request message for FeatureOnlineStoreService.FeatureViewDirectWrite.", "properties": { "dataKeyAndFeatureValues": { "description": "Required. The data keys and associated feature values.", "items": { "$ref": "GoogleCloudAiplatformV1FeatureViewDirectWriteRequestDataKeyAndFeatureValues" }, "type": "array" } }, "type": "object" }, "GoogleCloudAiplatformV1JiraSource": { "id": "GoogleCloudAiplatformV1JiraSource", "properties": { "jiraQueries": { "items": { "$ref": "GoogleCloudAiplatformV1JiraSourceJiraQueries" }, "description": "Required. The Jira queries.", "type": "array" } }, "description": "The Jira source for the ImportRagFilesRequest.", "type": "object" }, "GoogleCloudAiplatformV1DeployedIndexRef": { "type": "object", "properties": { "indexEndpoint": { "description": "Immutable. A resource name of the IndexEndpoint.", "type": "string" }, "displayName": { "type": "string", "readOnly": true, "description": "Output only. The display name of the DeployedIndex." }, "deployedIndexId": { "description": "Immutable. The ID of the DeployedIndex in the above IndexEndpoint.", "type": "string" } }, "id": "GoogleCloudAiplatformV1DeployedIndexRef", "description": "Points to a DeployedIndex." }, "GoogleCloudAiplatformV1BleuMetricValue": { "properties": { "score": { "type": "number", "description": "Output only. Bleu score.", "readOnly": true, "format": "float" } }, "description": "Bleu metric value for an instance.", "type": "object", "id": "GoogleCloudAiplatformV1BleuMetricValue" }, "GenaiVertexV1DocumentDelta": { "id": "GenaiVertexV1DocumentDelta", "properties": { "data": { "format": "byte", "type": "string" }, "mimeType": { "type": "string", "enum": [ "TYPE_UNSPECIFIED", "TYPE_PDF", "TYPE_CSV" ], "enumDescriptions": [ "", "PDF document format", "CSV document format" ] }, "uri": { "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1CompactionConfigEventEditingConfig": { "id": "GoogleCloudAiplatformV1CompactionConfigEventEditingConfig", "description": "Configuration for event-history editing-based compaction. When set, the event history is rewritten in place using deterministic rules (e.g. truncating/masking oversized tool responses, stripping model thoughts).", "type": "object", "properties": { "mode": { "enumDescriptions": [ "Unspecified. Requests must set an explicit mode.", "Platform-managed editing with server-side defaults (e.g. 5KB tool-response truncation threshold)." ], "type": "string", "description": "Required. The event-editing mode. Only `AUTO` is supported for MVP.", "enum": [ "MODE_UNSPECIFIED", "AUTO" ] } } }, "GoogleCloudAiplatformV1CreateFeatureOnlineStoreOperationMetadata": { "properties": { "genericMetadata": { "description": "Operation metadata for FeatureOnlineStore.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1CreateFeatureOnlineStoreOperationMetadata", "description": "Details of operations that perform create FeatureOnlineStore.", "type": "object" }, "GoogleCloudAiplatformV1TimeSeriesDataPoint": { "type": "object", "description": "A TensorboardTimeSeries data point.", "id": "GoogleCloudAiplatformV1TimeSeriesDataPoint", "properties": { "blobs": { "description": "A blob sequence value.", "$ref": "GoogleCloudAiplatformV1TensorboardBlobSequence" }, "tensor": { "description": "A tensor value.", "$ref": "GoogleCloudAiplatformV1TensorboardTensor" }, "scalar": { "description": "A scalar value.", "$ref": "GoogleCloudAiplatformV1Scalar" }, "step": { "type": "string", "format": "int64", "description": "Step index of this data point within the run." }, "wallTime": { "description": "Wall clock timestamp when this data point is generated by the end user.", "type": "string", "format": "google-datetime" } } }, "CloudAiLargeModelsVisionExperimentsResponseProEditResult": { "description": "Result metadata from a Pro Edit operation.", "properties": { "structuredPrompt": { "description": "The output structured prompt (JSON string) produced by this edit.", "type": "string" } }, "id": "CloudAiLargeModelsVisionExperimentsResponseProEditResult", "type": "object" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetrics", "type": "object", "properties": { "meanAbsolutePercentageError": { "description": "Mean absolute percentage error. Infinity when there are zeros in the ground truth.", "type": "number", "format": "float" }, "weightedAbsolutePercentageError": { "format": "float", "description": "Weighted Absolute Percentage Error. Does not use weights, this is just what the metric is called. Undefined if actual values sum to zero. Will be very large if actual values sum to a very small number.", "type": "number" }, "rootMeanSquaredPercentageError": { "description": "Root Mean Square Percentage Error. Square root of MSPE. Undefined/imaginary when MSPE is negative.", "type": "number", "format": "float" }, "rSquared": { "format": "float", "description": "Coefficient of determination as Pearson correlation coefficient. Undefined when ground truth or predictions are constant or near constant.", "type": "number" }, "quantileMetrics": { "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry" }, "type": "array", "description": "The quantile metrics entries for each quantile." }, "rootMeanSquaredError": { "format": "float", "description": "Root Mean Squared Error (RMSE).", "type": "number" }, "meanAbsoluteError": { "description": "Mean Absolute Error (MAE).", "type": "number", "format": "float" }, "rootMeanSquaredLogError": { "format": "float", "type": "number", "description": "Root mean squared log error. Undefined when there are negative ground truth values or predictions." } }, "description": "Metrics for forecasting evaluation results." }, "GoogleCloudAiplatformV1GenerationConfigRoutingConfig": { "type": "object", "id": "GoogleCloudAiplatformV1GenerationConfigRoutingConfig", "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": { "$ref": "GoogleCloudAiplatformV1GenerationConfigRoutingConfigManualRoutingMode", "description": "In this mode, the model is specified manually." }, "autoMode": { "description": "In this mode, the model is selected automatically based on the content of the request.", "$ref": "GoogleCloudAiplatformV1GenerationConfigRoutingConfigAutoRoutingMode" } } }, "GoogleCloudAiplatformV1SemanticGovernancePolicyMcpTool": { "properties": { "tools": { "description": "Required. The resource names of the tools used by the Agent that is affected by this policy. Currently, exactly one tool must be specified.", "items": { "type": "string" }, "type": "array" }, "mcpServer": { "description": "Required. The resource name of the McpServer in Agent Registry that is affected by this policy. Format: `projects/{project}/locations/{location}/mcpServers/{mcp_server}`", "type": "string" } }, "description": "Represents a governance policy applied to MCP tools used by an Agent.", "type": "object", "id": "GoogleCloudAiplatformV1SemanticGovernancePolicyMcpTool" }, "CloudAiLargeModelsVisionPromptInputs": { "properties": { "audioPrompt": { "type": "string", "description": "Description of audio content in the video, without speech." }, "negativeAudioPrompt": { "type": "string", "description": "Negative description of audio content in the video." }, "transcript": { "description": "Spoken transcript of the video for characters.", "type": "string" }, "promptChunks": { "type": "array", "description": "2s, 256 tokens per chunk, 4 total chunks. Required.", "items": { "type": "string" } }, "negativePrompt": { "type": "string", "description": "Single negative prompt for what not to generate." } }, "id": "CloudAiLargeModelsVisionPromptInputs", "description": "\"Direct\" prompting for Experimental Video Generation. These will be sent directly to the LDM without being rewritten.", "type": "object" }, "GoogleCloudAiplatformV1SchemaPromptSpecTranslationGcsInputSource": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationGcsInputSource", "properties": { "inputUri": { "type": "string", "description": "Source data URI. For example, `gs://my_bucket/my_object`." } } }, "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsRequest": { "description": "Request message for ModelService.BatchImportEvaluatedAnnotations", "id": "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsRequest", "type": "object", "properties": { "evaluatedAnnotations": { "items": { "$ref": "GoogleCloudAiplatformV1EvaluatedAnnotation" }, "description": "Required. Evaluated annotations resource to be imported.", "type": "array" } } }, "GoogleCloudAiplatformV1IndexDatapointNumericRestriction": { "type": "object", "description": "This field allows restricts to be based on numeric comparisons rather than categorical tokens.", "properties": { "valueDouble": { "description": "Represents 64 bit float.", "type": "number", "format": "double" }, "valueInt": { "format": "int64", "type": "string", "description": "Represents 64 bit integer." }, "valueFloat": { "description": "Represents 32 bit float.", "format": "float", "type": "number" }, "namespace": { "type": "string", "description": "The namespace of this restriction. e.g.: cost." }, "op": { "description": "This MUST be specified for queries and must NOT be specified for datapoints.", "type": "string", "enum": [ "OPERATOR_UNSPECIFIED", "LESS", "LESS_EQUAL", "EQUAL", "GREATER_EQUAL", "GREATER", "NOT_EQUAL" ], "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." ] } }, "id": "GoogleCloudAiplatformV1IndexDatapointNumericRestriction" }, "GoogleCloudAiplatformV1IndexEndpoint": { "properties": { "updateTime": { "type": "string", "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, "format": "google-datetime" }, "publicEndpointDomainName": { "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.", "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.", "type": "boolean", "deprecated": true }, "encryptionSpec": { "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.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "labels": { "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.", "type": "object", "additionalProperties": { "type": "string" } }, "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" }, "satisfiesPzi": { "readOnly": true, "description": "Output only. Reserved for future use.", "type": "boolean" }, "description": { "description": "The description of the IndexEndpoint.", "type": "string" }, "createTime": { "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when this IndexEndpoint was created.", "readOnly": true }, "deployedIndexes": { "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1DeployedIndex" }, "type": "array", "description": "Output only. The indexes deployed in this endpoint." }, "name": { "type": "string", "readOnly": true, "description": "Output only. The resource name of the IndexEndpoint." }, "publicEndpointEnabled": { "description": "Optional. If true, the deployed index will be accessible through public endpoint.", "type": "boolean" }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "displayName": { "description": "Required. The display name of the IndexEndpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "privateServiceConnectConfig": { "$ref": "GoogleCloudAiplatformV1PrivateServiceConnectConfig", "description": "Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive." } }, "id": "GoogleCloudAiplatformV1IndexEndpoint", "type": "object", "description": "Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes." }, "GoogleCloudAiplatformV1MemoryTopicId": { "description": "A memory topic identifier. This will be used to label a Memory and to restrict which topics are eligible for generation or retrieval.", "id": "GoogleCloudAiplatformV1MemoryTopicId", "properties": { "managedMemoryTopic": { "description": "Optional. Represents the managed memory topic.", "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." ], "enum": [ "MANAGED_TOPIC_ENUM_UNSPECIFIED", "USER_PERSONAL_INFO", "USER_PREFERENCES", "KEY_CONVERSATION_DETAILS", "EXPLICIT_INSTRUCTIONS" ], "type": "string" }, "customMemoryTopicLabel": { "description": "Optional. Represents the custom memory topic label.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1ModelVersionCheckpoint": { "deprecated": true, "id": "GoogleCloudAiplatformV1ModelVersionCheckpoint", "description": "Describes the machine learning model version checkpoint.", "properties": { "step": { "type": "string", "description": "The step of the checkpoint.", "format": "int64" }, "epoch": { "description": "The epoch of the checkpoint.", "type": "string", "format": "int64" }, "checkpointId": { "type": "string", "description": "The ID of the checkpoint." } }, "type": "object" }, "GenaiVertexV1ThoughtSummaryDelta": { "properties": { "content": { "description": "A new summary item to be added to the thought.", "$ref": "GenaiVertexV1Content" } }, "id": "GenaiVertexV1ThoughtSummaryDelta", "type": "object" }, "GoogleCloudAiplatformV1Part": { "properties": { "executableCode": { "description": "Optional. Code generated by the model that is intended to be executed.", "$ref": "GoogleCloudAiplatformV1ExecutableCode" }, "functionResponse": { "$ref": "GoogleCloudAiplatformV1FunctionResponse", "description": "Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted." }, "inlineData": { "$ref": "GoogleCloudAiplatformV1Blob", "description": "Optional. The inline data content of the part. This can be used to include images, audio, or video in a request." }, "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.", "$ref": "GoogleCloudAiplatformV1FunctionCall" }, "thought": { "description": "Optional. Indicates whether the `part` represents the model's thought process or reasoning.", "type": "boolean" }, "mediaResolution": { "description": "per part media resolution. Media resolution for the input media.", "$ref": "GoogleCloudAiplatformV1PartMediaResolution" }, "text": { "type": "string", "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." }, "audioTranscription": { "description": "Optional. Audio (input or output) transcription. This is only set when this `Part` contains audio data.", "$ref": "GoogleCloudAiplatformV1AudioTranscription" }, "codeExecutionResult": { "description": "Optional. The result of executing the ExecutableCode.", "$ref": "GoogleCloudAiplatformV1CodeExecutionResult" }, "speechMetadata": { "description": "Optional. Turn-level metadata for speech generation (e.g. Daikon speaker/style). May be set alongside `text` to attach speaker and style information to a text part.", "$ref": "GoogleCloudAiplatformV1SpeechMetadata" }, "videoMetadata": { "$ref": "GoogleCloudAiplatformV1VideoMetadata", "description": "Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data." }, "thoughtSignature": { "description": "Optional. An opaque signature for the thought so it can be reused in subsequent requests.", "type": "string", "format": "byte" }, "fileData": { "description": "Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.", "$ref": "GoogleCloudAiplatformV1FileData" } }, "id": "GoogleCloudAiplatformV1Part", "description": "A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` must contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.", "type": "object" }, "GoogleCloudAiplatformV1PairwiseSummarizationQualitySpec": { "type": "object", "id": "GoogleCloudAiplatformV1PairwiseSummarizationQualitySpec", "description": "Spec for pairwise summarization quality score metric.", "properties": { "useReference": { "description": "Optional. Whether to use instance.reference to compute pairwise summarization quality.", "type": "boolean" }, "version": { "format": "int32", "description": "Optional. Which version to use for evaluation.", "type": "integer" } } }, "GenaiVertexV1GoogleMapsCallDelta": { "properties": { "arguments": { "description": "The arguments to pass to the Google Maps tool.", "$ref": "GenaiVertexV1GoogleMapsCallContentGoogleMapsCallArguments" } }, "type": "object", "id": "GenaiVertexV1GoogleMapsCallDelta" }, "GoogleCloudAiplatformV1SchemaPredictPredictionVideoClassificationPredictionResult": { "properties": { "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" }, "displayName": { "description": "The display name of the AnnotationSpec that had been identified.", "type": "string" }, "timeSegmentStart": { "type": "string", "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" }, "timeSegmentEnd": { "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.", "format": "google-duration", "type": "string" }, "confidence": { "description": "The Model's confidence in correction of this prediction, higher value means higher confidence.", "type": "number", "format": "float" }, "id": { "type": "string", "description": "The resource ID of the AnnotationSpec that had been identified." } }, "description": "Prediction output format for Video Classification.", "type": "object", "id": "GoogleCloudAiplatformV1SchemaPredictPredictionVideoClassificationPredictionResult" }, "GoogleCloudAiplatformV1SchemaAnnotationSpecColor": { "type": "object", "properties": { "color": { "description": "The color of the AnnotationSpec in a segmentation mask.", "$ref": "GoogleTypeColor" }, "id": { "type": "string", "description": "The ID of the AnnotationSpec represented by the color in the segmentation mask." }, "displayName": { "type": "string", "description": "The display name of the AnnotationSpec represented by the color in the segmentation mask." } }, "id": "GoogleCloudAiplatformV1SchemaAnnotationSpecColor", "description": "An entry of mapping between color and AnnotationSpec. The mapping is used in segmentation mask." }, "GoogleCloudAiplatformV1FeatureViewDirectWriteResponse": { "id": "GoogleCloudAiplatformV1FeatureViewDirectWriteResponse", "properties": { "writeResponses": { "type": "array", "description": "Details about write for each key. If status is not OK, WriteResponse.data_key will have the key with error, but WriteResponse.online_store_write_time will not be present.", "items": { "$ref": "GoogleCloudAiplatformV1FeatureViewDirectWriteResponseWriteResponse" } }, "status": { "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.", "$ref": "GoogleRpcStatus" } }, "description": "Response message for FeatureOnlineStoreService.FeatureViewDirectWrite.", "type": "object" }, "GoogleCloudAiplatformV1EvaluationRunDataSource": { "properties": { "evaluationSet": { "description": "The EvaluationSet resource name. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`", "type": "string" }, "bigqueryRequestSet": { "description": "Evaluation data in bigquery.", "$ref": "GoogleCloudAiplatformV1BigQueryRequestSet" } }, "type": "object", "description": "The data source for the evaluation run.", "id": "GoogleCloudAiplatformV1EvaluationRunDataSource" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata", "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": { "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.", "type": "string", "enum": [ "SUCCESSFUL_STOP_REASON_UNSPECIFIED", "BUDGET_REACHED", "MODEL_CONVERGED" ] } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation", "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.", "type": "object" }, "GoogleCloudAiplatformV1NasTrial": { "id": "GoogleCloudAiplatformV1NasTrial", "properties": { "finalMeasurement": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1Measurement", "description": "Output only. The final measurement containing the objective value." }, "state": { "enum": [ "STATE_UNSPECIFIED", "REQUESTED", "ACTIVE", "STOPPING", "SUCCEEDED", "INFEASIBLE" ], "type": "string", "readOnly": true, "description": "Output only. The detailed state of the NasTrial.", "enumDescriptions": [ "The NasTrial state is unspecified.", "Indicates that a specific NasTrial has been requested, but it has not yet been suggested by the service.", "Indicates that the NasTrial has been suggested.", "Indicates that the NasTrial should stop according to the service.", "Indicates that the NasTrial is completed successfully.", "Indicates that the NasTrial should not be attempted again. The service will set a NasTrial to INFEASIBLE when it's done but missing the final_measurement." ] }, "id": { "readOnly": true, "type": "string", "description": "Output only. The identifier of the NasTrial assigned by the service." }, "startTime": { "type": "string", "readOnly": true, "format": "google-datetime", "description": "Output only. Time when the NasTrial was started." }, "endTime": { "format": "google-datetime", "type": "string", "description": "Output only. Time when the NasTrial's status changed to `SUCCEEDED` or `INFEASIBLE`.", "readOnly": true } }, "description": "Represents a uCAIP NasJob trial.", "type": "object" }, "GoogleCloudAiplatformV1SpeculativeDecodingSpec": { "id": "GoogleCloudAiplatformV1SpeculativeDecodingSpec", "description": "Configuration for Speculative Decoding.", "properties": { "speculativeTokenCount": { "format": "int32", "type": "integer", "description": "The number of speculative tokens to generate at each step." }, "ngramSpeculation": { "$ref": "GoogleCloudAiplatformV1SpeculativeDecodingSpecNgramSpeculation", "description": "N-Gram speculation." }, "draftModelSpeculation": { "$ref": "GoogleCloudAiplatformV1SpeculativeDecodingSpecDraftModelSpeculation", "description": "draft model speculation." } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaImageDataItem": { "description": "Payload of Image DataItem.", "properties": { "mimeType": { "readOnly": true, "type": "string", "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" }, "gcsUri": { "type": "string", "description": "Required. Google Cloud Storage URI points to the original image in user's bucket. The image is up to 30MB in size." } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaImageDataItem" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputs": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputs", "type": "object", "properties": { "trainBudgetMilliNodeHours": { "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.", "type": "string" }, "optimizationObjectiveRecallValue": { "format": "float", "description": "Required when optimization_objective is \"maximize-precision-at-recall\". Must be between 0 and 1, inclusive.", "type": "number" }, "additionalExperiments": { "items": { "type": "string" }, "description": "Additional experiment flags for the Tables training pipeline.", "type": "array" }, "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" }, "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" }, "transformations": { "type": "array", "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.", "items": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation" } }, "optimizationObjectivePrecisionValue": { "format": "float", "type": "number", "description": "Required when optimization_objective is \"maximize-recall-at-precision\". Must be between 0 and 1, inclusive." }, "optimizationObjective": { "type": "string", "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)." }, "exportEvaluatedDataItemsConfig": { "description": "Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig" }, "targetColumn": { "description": "The column name of the target column that the model is to predict.", "type": "string" }, "predictionType": { "type": "string", "description": "The type of prediction the Model is to produce. \"classification\" - Predict one out of multiple target values is picked for each row. \"regression\" - Predict a value based on its relation to other values. This type is available only to columns that contain semantically numeric values, i.e. integers or floating point number, even if stored as e.g. strings." } } }, "GoogleCloudAiplatformV1MemoryBankCustomizationConfigMemoryTopic": { "description": "A topic of information that should be extracted from conversations and stored as memories.", "id": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigMemoryTopic", "properties": { "customMemoryTopic": { "$ref": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigMemoryTopicCustomMemoryTopic", "description": "A custom memory topic defined by the developer." }, "managedMemoryTopic": { "$ref": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigMemoryTopicManagedMemoryTopic", "description": "A managed memory topic defined by Memory Bank." } }, "type": "object" }, "GoogleCloudAiplatformV1CustomJob": { "id": "GoogleCloudAiplatformV1CustomJob", "description": "Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded).", "type": "object", "properties": { "name": { "description": "Output only. Resource name of a CustomJob.", "type": "string", "readOnly": true }, "displayName": { "type": "string", "description": "Required. The display name of the CustomJob. The name can be up to 128 characters long and can consist of any UTF-8 characters." }, "encryptionSpec": { "description": "Customer-managed encryption key options for a CustomJob. If this is set, then all resources created by the CustomJob will be encrypted with the provided encryption key.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "webAccessUris": { "readOnly": true, "additionalProperties": { "type": "string" }, "type": "object", "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." }, "createTime": { "type": "string", "description": "Output only. Time when the CustomJob was created.", "format": "google-datetime", "readOnly": true }, "state": { "readOnly": true, "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.", "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." ] }, "startTime": { "type": "string", "readOnly": true, "format": "google-datetime", "description": "Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state." }, "satisfiesPzi": { "readOnly": true, "description": "Output only. Reserved for future use.", "type": "boolean" }, "updateTime": { "format": "google-datetime", "description": "Output only. Time when the CustomJob was most recently updated.", "readOnly": true, "type": "string" }, "satisfiesPzs": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "jobSpec": { "$ref": "GoogleCloudAiplatformV1CustomJobSpec", "description": "Required. Job spec." }, "endTime": { "type": "string", "description": "Output only. Time when the CustomJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.", "readOnly": true, "format": "google-datetime" }, "error": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`." }, "labels": { "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.", "type": "object" } } }, "GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata": { "type": "object", "id": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata", "description": "All metadata of most recent monitoring pipelines.", "properties": { "runTime": { "format": "google-datetime", "type": "string", "description": "The time that most recent monitoring pipelines that is related to this run." }, "status": { "description": "The status of the most recent monitoring pipeline.", "$ref": "GoogleRpcStatus" } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation": { "properties": { "columnName": { "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation", "description": "Training pipeline will infer the proper transformation based on the statistic of dataset." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecasting": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecasting", "type": "object", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs" }, "metadata": { "description": "The metadata information.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata" } }, "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformation": { "properties": { "auto": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation" }, "categorical": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation" }, "text": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation" }, "timestamp": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation" }, "numeric": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformation", "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs", "type": "object", "properties": { "modelType": { "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." ], "enum": [ "MODEL_TYPE_UNSPECIFIED", "CLOUD", "MOBILE_VERSATILE_1", "MOBILE_JETSON_VERSATILE_1", "MOBILE_CORAL_VERSATILE_1" ] } } }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry", "description": "Entry for the Quantiles loss type optimization objective.", "type": "object", "properties": { "quantile": { "format": "double", "description": "The quantile for this entry.", "type": "number" }, "observedQuantile": { "format": "double", "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.", "type": "number" }, "scaledPinballLoss": { "type": "number", "description": "The scaled pinball loss of this quantile.", "format": "float" } } }, "GoogleCloudAiplatformV1DeployModelRequest": { "type": "object", "description": "Request message for EndpointService.DeployModel.", "properties": { "trafficSplit": { "type": "object", "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.", "additionalProperties": { "type": "integer", "format": "int32" } }, "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.", "$ref": "GoogleCloudAiplatformV1DeployedModel" } }, "id": "GoogleCloudAiplatformV1DeployModelRequest" }, "GoogleCloudAiplatformV1PairwiseMetricResult": { "id": "GoogleCloudAiplatformV1PairwiseMetricResult", "properties": { "customOutput": { "description": "Output only. Spec for custom output.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1CustomOutput" }, "pairwiseChoice": { "readOnly": true, "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" ] }, "explanation": { "description": "Output only. Explanation for pairwise metric score.", "type": "string", "readOnly": true } }, "type": "object", "description": "Spec for pairwise metric result." }, "GoogleCloudAiplatformV1RagContexts": { "type": "object", "properties": { "contexts": { "items": { "$ref": "GoogleCloudAiplatformV1RagContextsContext" }, "type": "array", "description": "All its contexts." } }, "description": "Relevant contexts for one query.", "id": "GoogleCloudAiplatformV1RagContexts" }, "GoogleCloudAiplatformV1EvaluateDatasetRun": { "type": "object", "description": "Evaluate Dataset Run Result for Tuning Job.", "properties": { "error": { "readOnly": true, "description": "Output only. The error of the evaluation run if any.", "$ref": "GoogleRpcStatus" }, "evaluationRun": { "readOnly": true, "type": "string", "description": "Output only. The resource name of the evaluation run. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run_id}`." }, "operationName": { "readOnly": true, "deprecated": true, "description": "Output only. Deprecated: The updated architecture uses evaluation_run instead.", "type": "string" }, "evaluateDatasetResponse": { "$ref": "GoogleCloudAiplatformV1EvaluateDatasetResponse", "description": "Output only. Results for EvaluationService.", "readOnly": true }, "checkpointId": { "description": "Output only. The checkpoint id used in the evaluation run. Only populated when evaluating checkpoints.", "type": "string", "readOnly": true } }, "id": "GoogleCloudAiplatformV1EvaluateDatasetRun" }, "GoogleCloudAiplatformV1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeature": { "properties": { "name": { "description": "Feature short name.", "type": "string" }, "value": { "$ref": "GoogleCloudAiplatformV1FeatureValue", "description": "Feature value. A user provided timestamp may be set in the `FeatureValue.metadata.generate_time` field." } }, "description": "Feature name & value pair.", "type": "object", "id": "GoogleCloudAiplatformV1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeature" }, "GoogleCloudAiplatformV1UploadRagFileConfig": { "type": "object", "properties": { "ragFileTransformationConfig": { "description": "Specifies the transformation config for RagFiles.", "$ref": "GoogleCloudAiplatformV1RagFileTransformationConfig" } }, "id": "GoogleCloudAiplatformV1UploadRagFileConfig", "description": "Config for uploading RagFile." }, "GoogleCloudAiplatformV1PersistentDiskSpec": { "description": "Represents the spec of persistent disk and hyperdisk options.", "type": "object", "id": "GoogleCloudAiplatformV1PersistentDiskSpec", "properties": { "diskType": { "type": "string", "description": "Type of the disk (default is \"pd-standard\"). Valid values: \"pd-ssd\" (Persistent Disk Solid State Drive) \"pd-standard\" (Persistent Disk Hard Disk Drive) \"pd-balanced\" (Balanced Persistent Disk) \"pd-extreme\" (Extreme Persistent Disk) \"hyperdisk-balanced\" (Hyperdisk Balanced) \"hyperdisk-extreme\" (Hyperdisk Extreme) \"hyperdisk-balanced-high-availability\" (Hyperdisk Balanced High Availability) \"hyperdisk-ml\" (Hyperdisk ML) \"hyperdisk-throughput\" (Hyperdisk Throughput)" }, "diskSizeGb": { "type": "string", "format": "int64", "description": "Size in GB of the disk (default is 100GB)." } } }, "GoogleCloudAiplatformV1ListBatchPredictionJobsResponse": { "id": "GoogleCloudAiplatformV1ListBatchPredictionJobsResponse", "description": "Response message for JobService.ListBatchPredictionJobs", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListBatchPredictionJobsRequest.page_token to obtain that page.", "type": "string" }, "batchPredictionJobs": { "items": { "$ref": "GoogleCloudAiplatformV1BatchPredictionJob" }, "type": "array", "description": "List of BatchPredictionJobs in the requested page." } }, "type": "object" }, "GenaiVertexV1StepDelta": { "properties": { "index": { "format": "int32", "type": "integer" }, "delta": { "$ref": "GenaiVertexV1StepDeltaData" } }, "id": "GenaiVertexV1StepDelta", "type": "object" }, "GoogleCloudAiplatformV1SampledShapleyAttribution": { "id": "GoogleCloudAiplatformV1SampledShapleyAttribution", "type": "object", "properties": { "pathCount": { "format": "int32", "type": "integer", "description": "Required. The number of feature permutations to consider when approximating the Shapley values. Valid range of its value is [1, 50], inclusively." } }, "description": "An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features." }, "GoogleCloudAiplatformV1RebootPersistentResourceOperationMetadata": { "properties": { "progressMessage": { "description": "Progress Message for Reboot LRO", "type": "string" }, "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Operation metadata for PersistentResource." } }, "description": "Details of operations that perform reboot PersistentResource.", "id": "GoogleCloudAiplatformV1RebootPersistentResourceOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1CometInput": { "type": "object", "description": "Input for Comet metric.", "properties": { "instance": { "description": "Required. Comet instance.", "$ref": "GoogleCloudAiplatformV1CometInstance" }, "metricSpec": { "description": "Required. Spec for comet metric.", "$ref": "GoogleCloudAiplatformV1CometSpec" } }, "id": "GoogleCloudAiplatformV1CometInput" }, "GoogleCloudAiplatformV1EmbedContentResponseEmbedding": { "type": "object", "id": "GoogleCloudAiplatformV1EmbedContentResponseEmbedding", "properties": { "values": { "type": "array", "description": "Embedding vector values.", "items": { "type": "number", "format": "float" } } }, "description": "A list of floats representing an embedding." }, "GoogleCloudAiplatformV1ExportFeatureValuesRequestSnapshotExport": { "properties": { "startTime": { "format": "google-datetime", "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.", "type": "string" }, "snapshotTime": { "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", "format": "google-datetime" } }, "type": "object", "description": "Describes exporting the latest Feature values of all entities of the EntityType between [start_time, snapshot_time].", "id": "GoogleCloudAiplatformV1ExportFeatureValuesRequestSnapshotExport" }, "GoogleCloudAiplatformV1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset": { "id": "GoogleCloudAiplatformV1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset", "description": "Represents one AnnotatedDataset in datalabeling.googleapis.com.", "properties": { "annotatedDatasetDisplayName": { "type": "string", "description": "The AnnotatedDataset's display name in datalabeling.googleapis.com." }, "annotatedDataset": { "type": "string", "description": "Full resource name of data labeling AnnotatedDataset. Format: `projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}`." } }, "type": "object" }, "GoogleCloudAiplatformV1RetrieveMemoriesResponse": { "type": "object", "description": "Response message for MemoryBankService.RetrieveMemories.", "properties": { "nextPageToken": { "type": "string", "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." }, "retrievedMemories": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1RetrieveMemoriesResponseRetrievedMemory" }, "description": "The retrieved memories." } }, "id": "GoogleCloudAiplatformV1RetrieveMemoriesResponse" }, "GoogleCloudAiplatformV1ExecuteCodeResponse": { "id": "GoogleCloudAiplatformV1ExecuteCodeResponse", "type": "object", "description": "Response message for SandboxEnvironmentExecutionService.ExecuteCode.", "properties": { "outputs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Chunk" }, "description": "The outputs from the sandbox environment." } } }, "GenaiVertexV1ListValue": { "type": "object", "properties": { "values": { "items": { "$ref": "GenaiVertexV1Value" }, "description": "Repeated field of dynamically typed values.", "type": "array" } }, "description": "`ListValue` is a wrapper around a repeated field of values.", "id": "GenaiVertexV1ListValue" }, "GoogleCloudAiplatformV1ListNasTrialDetailsResponse": { "description": "Response message for JobService.ListNasTrialDetails", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListNasTrialDetailsRequest.page_token to obtain that page.", "type": "string" }, "nasTrialDetails": { "description": "List of top NasTrials in the requested page.", "items": { "$ref": "GoogleCloudAiplatformV1NasTrialDetail" }, "type": "array" } }, "type": "object", "id": "GoogleCloudAiplatformV1ListNasTrialDetailsResponse" }, "GoogleCloudAiplatformV1SchemaPromptSpecTranslationFileInputSource": { "type": "object", "properties": { "mimeType": { "description": "The file's mime type.", "type": "string" }, "displayName": { "type": "string", "description": "The file's display name." }, "content": { "type": "string", "description": "The file's contents." } }, "id": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationFileInputSource" }, "GoogleCloudAiplatformV1BleuSpec": { "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.", "properties": { "useEffectiveOrder": { "description": "Optional. Whether to use_effective_order to compute bleu score.", "type": "boolean" } }, "type": "object", "id": "GoogleCloudAiplatformV1BleuSpec" }, "GoogleCloudAiplatformV1Trial": { "type": "object", "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": "GoogleCloudAiplatformV1Trial", "properties": { "state": { "type": "string", "enum": [ "STATE_UNSPECIFIED", "REQUESTED", "ACTIVE", "STOPPING", "SUCCEEDED", "INFEASIBLE" ], "description": "Output only. The detailed state of the Trial.", "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." ], "readOnly": true }, "webAccessUris": { "additionalProperties": { "type": "string" }, "type": "object", "readOnly": true, "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." }, "infeasibleReason": { "type": "string", "description": "Output only. A human readable string describing why the Trial is infeasible. This is set only if Trial state is `INFEASIBLE`.", "readOnly": true }, "customJob": { "description": "Output only. The CustomJob name linked to the Trial. It's set for a HyperparameterTuningJob's Trial.", "readOnly": true, "type": "string" }, "name": { "description": "Output only. Resource name of the Trial assigned by the service.", "readOnly": true, "type": "string" }, "finalMeasurement": { "description": "Output only. The final measurement containing the objective value.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1Measurement" }, "id": { "type": "string", "description": "Output only. The identifier of the Trial assigned by the service.", "readOnly": true }, "endTime": { "format": "google-datetime", "type": "string", "description": "Output only. Time when the Trial's status changed to `SUCCEEDED` or `INFEASIBLE`.", "readOnly": true }, "clientId": { "readOnly": true, "description": "Output only. The identifier of the client that originally requested this Trial. Each client is identified by a unique client_id. When a client asks for a suggestion, Vertex AI Vizier will assign it a Trial. The client should evaluate the Trial, complete it, and report back to Vertex AI Vizier. If suggestion is asked again by same client_id before the Trial is completed, the same Trial will be returned. Multiple clients with different client_ids can ask for suggestions simultaneously, each of them will get their own Trial.", "type": "string" }, "measurements": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Measurement" }, "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.", "readOnly": true }, "parameters": { "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1TrialParameter" }, "description": "Output only. The parameters of the Trial." }, "startTime": { "format": "google-datetime", "readOnly": true, "type": "string", "description": "Output only. Time when the Trial was started." } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1CachedContent": { "description": "A resource used in LLM queries for users to explicitly specify what to cache and how to cache.", "type": "object", "properties": { "tools": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Tool" }, "description": "Optional. Input only. Immutable. A list of `Tools` the model may use to generate the next response" }, "updateTime": { "description": "Output only. When the cache entry was last updated in UTC time.", "format": "google-datetime", "readOnly": true, "type": "string" }, "contents": { "description": "Optional. Input only. Immutable. The content to cache", "items": { "$ref": "GoogleCloudAiplatformV1Content" }, "type": "array" }, "toolConfig": { "$ref": "GoogleCloudAiplatformV1ToolConfig", "description": "Optional. Input only. Immutable. Tool config. This config is shared for all tools" }, "expireTime": { "type": "string", "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." }, "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.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "systemInstruction": { "$ref": "GoogleCloudAiplatformV1Content", "description": "Optional. Input only. Immutable. Developer set system instruction. Currently, text only" }, "ttl": { "type": "string", "format": "google-duration", "description": "Input only. The TTL for this resource. The expiration time is computed: now + TTL." }, "name": { "type": "string", "description": "Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}" }, "createTime": { "format": "google-datetime", "description": "Output only. Creation time of the cache entry.", "readOnly": true, "type": "string" }, "usageMetadata": { "description": "Output only. Metadata on the usage of the cached content.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1CachedContentUsageMetadata" }, "displayName": { "description": "Optional. Immutable. The user-generated meaningful display name of the cached content.", "type": "string" }, "model": { "type": "string", "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}" } }, "id": "GoogleCloudAiplatformV1CachedContent" }, "GenaiVertexV1SpeechAnnotation": { "description": "Speech annotation for text content.", "properties": { "style": { "description": "Style instruction for the speech synthesis.", "type": "string" }, "speaker": { "description": "The speaker to associate with this turn.", "type": "string" } }, "type": "object", "id": "GenaiVertexV1SpeechAnnotation" }, "GoogleCloudAiplatformV1OutputFieldSpec": { "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.", "id": "GoogleCloudAiplatformV1OutputFieldSpec", "properties": { "fieldName": { "type": "string", "description": "Required. The name of this field in the generated synthetic data, such as \"email_subject\" or \"customer_review\"." }, "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", "description": "Optional. The data type of the field. Defaults to CONTENT if not set.", "enum": [ "FIELD_TYPE_UNSPECIFIED", "CONTENT", "TEXT", "IMAGE", "AUDIO" ], "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." ] } }, "type": "object" }, "GoogleCloudAiplatformV1FeatureView": { "properties": { "satisfiesPzi": { "type": "boolean", "description": "Output only. Reserved for future use.", "readOnly": true }, "bigtableMetadata": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1FeatureViewBigtableMetadata", "description": "Output only. Metadata containing information about the Cloud Bigtable." }, "optimizedConfig": { "$ref": "GoogleCloudAiplatformV1FeatureViewOptimizedConfig", "description": "Optional. Configuration for FeatureView created under Optimized FeatureOnlineStore." }, "labels": { "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.", "type": "object", "additionalProperties": { "type": "string" } }, "satisfiesPzs": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "serviceAgentType": { "enum": [ "SERVICE_AGENT_TYPE_UNSPECIFIED", "SERVICE_AGENT_TYPE_PROJECT", "SERVICE_AGENT_TYPE_FEATURE_VIEW" ], "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." ], "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.", "type": "string" }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "bigQuerySource": { "description": "Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.", "$ref": "GoogleCloudAiplatformV1FeatureViewBigQuerySource" }, "updateTime": { "readOnly": true, "description": "Output only. Timestamp when this FeatureView was last updated.", "type": "string", "format": "google-datetime" }, "name": { "type": "string", "description": "Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`" }, "createTime": { "type": "string", "description": "Output only. Timestamp when this FeatureView was created.", "readOnly": true, "format": "google-datetime" }, "vertexRagSource": { "$ref": "GoogleCloudAiplatformV1FeatureViewVertexRagSource", "description": "Optional. The Vertex RAG Source that the FeatureView is linked to." }, "syncConfig": { "description": "Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving.", "$ref": "GoogleCloudAiplatformV1FeatureViewSyncConfig" }, "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.", "$ref": "GoogleCloudAiplatformV1FeatureViewIndexConfig" }, "serviceAccountEmail": { "description": "Output only. A Service Account unique to this FeatureView. The role bigquery.dataViewer should be granted to this service account to allow Vertex AI Feature Store to sync data to the online store.", "readOnly": true, "type": "string" }, "featureRegistrySource": { "$ref": "GoogleCloudAiplatformV1FeatureViewFeatureRegistrySource", "description": "Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore." } }, "type": "object", "description": "FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.", "id": "GoogleCloudAiplatformV1FeatureView" }, "GoogleCloudAiplatformV1PairwiseSummarizationQualityResult": { "id": "GoogleCloudAiplatformV1PairwiseSummarizationQualityResult", "properties": { "pairwiseChoice": { "readOnly": true, "description": "Output only. Pairwise summarization prediction choice.", "enumDescriptions": [ "Unspecified prediction choice.", "Baseline prediction wins", "Candidate prediction wins", "Winner cannot be determined" ], "type": "string", "enum": [ "PAIRWISE_CHOICE_UNSPECIFIED", "BASELINE", "CANDIDATE", "TIE" ] }, "confidence": { "type": "number", "description": "Output only. Confidence for summarization quality score.", "readOnly": true, "format": "float" }, "explanation": { "description": "Output only. Explanation for summarization quality score.", "type": "string", "readOnly": true } }, "description": "Spec for pairwise summarization quality result.", "type": "object" }, "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInput": { "type": "object", "properties": { "metricSpec": { "description": "Required. Spec for question answering relevance score metric.", "$ref": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceSpec" }, "instance": { "$ref": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInstance", "description": "Required. Question answering relevance instance." } }, "id": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInput", "description": "Input for question answering relevance metric." }, "GoogleCloudAiplatformV1MergeVersionAliasesRequest": { "id": "GoogleCloudAiplatformV1MergeVersionAliasesRequest", "type": "object", "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." } }, "description": "Request message for ModelService.MergeVersionAliases." }, "GoogleCloudAiplatformV1ExportFeatureValuesResponse": { "type": "object", "properties": {}, "description": "Response message for FeaturestoreService.ExportFeatureValues.", "id": "GoogleCloudAiplatformV1ExportFeatureValuesResponse" }, "GoogleCloudAiplatformV1SummarizationHelpfulnessResult": { "description": "Spec for summarization helpfulness result.", "id": "GoogleCloudAiplatformV1SummarizationHelpfulnessResult", "type": "object", "properties": { "score": { "format": "float", "description": "Output only. Summarization Helpfulness score.", "type": "number", "readOnly": true }, "explanation": { "description": "Output only. Explanation for summarization helpfulness score.", "type": "string", "readOnly": true }, "confidence": { "readOnly": true, "description": "Output only. Confidence for summarization helpfulness score.", "format": "float", "type": "number" } } }, "GoogleCloudAiplatformV1SchemaPredictInstanceVideoClassificationPredictionInstance": { "id": "GoogleCloudAiplatformV1SchemaPredictInstanceVideoClassificationPredictionInstance", "description": "Prediction input format for Video Classification.", "type": "object", "properties": { "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": { "type": "string", "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." }, "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" } } }, "GoogleCloudAiplatformV1SecretEnvVar": { "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.", "$ref": "GoogleCloudAiplatformV1SecretRef" } }, "description": "Represents an environment variable where the value is a secret in Cloud Secret Manager.", "id": "GoogleCloudAiplatformV1SecretEnvVar", "type": "object" }, "GoogleIamV1SetIamPolicyRequest": { "description": "Request message for `SetIamPolicy` method.", "properties": { "policy": { "description": "REQUIRED: The complete policy to be applied to the `resource`. The size of the policy is limited to a few 10s of KB. An empty policy is a valid policy but certain Google Cloud services (such as Projects) might reject them.", "$ref": "GoogleIamV1Policy" } }, "type": "object", "id": "GoogleIamV1SetIamPolicyRequest" }, "GoogleCloudAiplatformV1ListSpecialistPoolsResponse": { "type": "object", "description": "Response message for SpecialistPoolService.ListSpecialistPools.", "properties": { "nextPageToken": { "description": "The standard List next-page token.", "type": "string" }, "specialistPools": { "description": "A list of SpecialistPools that matches the specified filter in the request.", "items": { "$ref": "GoogleCloudAiplatformV1SpecialistPool" }, "type": "array" } }, "id": "GoogleCloudAiplatformV1ListSpecialistPoolsResponse" }, "CloudAiLargeModelsVisionGenerateVideoExperimentsAudioControlConfig": { "properties": { "useTargetAudioFromVideo": { "description": "Optional. When true, uses the audio track from the input video as the target audio instead of regenerating it. Mutually exclusive with `target_audio` below. Requires the input to be a video file, not an image sequence.", "type": "boolean" }, "targetAudio": { "description": "Optional. Audio file to use as the target audio input to Omni. Only used when `use_target_audio_from_video` is false. Cannot be set simultaneously with `use_target_audio_from_video = true`.", "$ref": "CloudAiLargeModelsVisionGenerateVideoRequestAudio" } }, "description": "Configuration for audio control.", "type": "object", "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsAudioControlConfig" }, "GoogleCloudAiplatformV1CreateDeploymentResourcePoolOperationMetadata": { "description": "Runtime operation information for CreateDeploymentResourcePool method.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The operation generic information." } }, "type": "object", "id": "GoogleCloudAiplatformV1CreateDeploymentResourcePoolOperationMetadata" }, "GoogleCloudAiplatformV1FeatureViewDataKey": { "type": "object", "id": "GoogleCloudAiplatformV1FeatureViewDataKey", "description": "Lookup key for a feature view.", "properties": { "key": { "description": "String key to use for lookup.", "type": "string" }, "compositeKey": { "$ref": "GoogleCloudAiplatformV1FeatureViewDataKeyCompositeKey", "description": "The actual Entity ID will be composed from this struct. This should match with the way ID is defined in the FeatureView spec." } } }, "GoogleCloudAiplatformV1GroundingChunk": { "id": "GoogleCloudAiplatformV1GroundingChunk", "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.", "type": "object", "properties": { "retrievedContext": { "$ref": "GoogleCloudAiplatformV1GroundingChunkRetrievedContext", "description": "A grounding chunk from a data source retrieved by a retrieval tool, such as Vertex AI Search. See the `RetrievedContext` message for details" }, "web": { "description": "A grounding chunk from a web page, typically from Google Search. See the `Web` message for details.", "$ref": "GoogleCloudAiplatformV1GroundingChunkWeb" }, "image": { "$ref": "GoogleCloudAiplatformV1GroundingChunkImage", "description": "A grounding chunk from an image search result. See the `Image` message for details." }, "maps": { "$ref": "GoogleCloudAiplatformV1GroundingChunkMaps", "description": "A grounding chunk from Google Maps. See the `Maps` message for details." } } }, "GoogleCloudAiplatformV1ModelSourceInfo": { "type": "object", "description": "Detail description of the source information of the model.", "properties": { "sourceType": { "type": "string", "enum": [ "MODEL_SOURCE_TYPE_UNSPECIFIED", "AUTOML", "CUSTOM", "BQML", "MODEL_GARDEN", "GENIE", "CUSTOM_TEXT_EMBEDDING", "MARKETPLACE" ], "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": "Type of the model source." }, "copy": { "type": "boolean", "description": "If this Model is copy of another Model. If true then source_type pertains to the original." } }, "id": "GoogleCloudAiplatformV1ModelSourceInfo" }, "GenaiVertexV1UrlContextCallStep": { "id": "GenaiVertexV1UrlContextCallStep", "type": "object", "properties": { "arguments": { "description": "Required. The arguments to pass to the URL context.", "$ref": "GenaiVertexV1UrlContextCallStepUrlContextCallStepArguments" } }, "description": "URL context call step." }, "GoogleCloudAiplatformV1EvaluationRunMetric": { "properties": { "metricConfig": { "description": "The metric config.", "$ref": "GoogleCloudAiplatformV1Metric" }, "llmBasedMetricSpec": { "$ref": "GoogleCloudAiplatformV1EvaluationRunMetricLLMBasedMetricSpec", "description": "Spec for an LLM based metric." }, "metricResourceName": { "description": "Optional. The resource name of the metric definition.", "type": "string" }, "metric": { "type": "string", "description": "Required. The name of the metric." }, "predefinedMetricSpec": { "description": "Spec for a pre-defined metric.", "$ref": "GoogleCloudAiplatformV1EvaluationRunMetricPredefinedMetricSpec" }, "rubricBasedMetricSpec": { "description": "Spec for rubric based metric.", "$ref": "GoogleCloudAiplatformV1EvaluationRunMetricRubricBasedMetricSpec" }, "computationBasedMetricSpec": { "$ref": "GoogleCloudAiplatformV1EvaluationRunMetricComputationBasedMetricSpec", "description": "Spec for a computation based metric." } }, "id": "GoogleCloudAiplatformV1EvaluationRunMetric", "description": "The metric used for evaluation runs.", "type": "object" }, "GenaiVertexV1Struct": { "description": "`Struct` represents a structured data value, consisting of fields which map to dynamically typed values.", "properties": { "fields": { "items": { "$ref": "GenaiVertexV1Field" }, "type": "array", "description": "Dynamically typed fields. List instead of map because LLMs are sensitive to ordering, and we want to give users full control." } }, "type": "object", "id": "GenaiVertexV1Struct" }, "GenaiVertexV1CodeExecutionCallStepCodeExecutionCallStepArguments": { "type": "object", "description": "The arguments to pass to the code execution.", "properties": { "language": { "enum": [ "LANGUAGE_UNSPECIFIED", "PYTHON" ], "description": "Programming language of the `code`.", "type": "string", "enumDescriptions": [ "Unspecified language. This value should not be used.", "Python \u003e= 3.10, with numpy and simpy available." ] }, "code": { "type": "string", "description": "The code to be executed." } }, "id": "GenaiVertexV1CodeExecutionCallStepCodeExecutionCallStepArguments" }, "GoogleCloudAiplatformV1ServiceAccountSpec": { "description": "Configuration for the use of custom service account to run the workloads.", "type": "object", "id": "GoogleCloudAiplatformV1ServiceAccountSpec", "properties": { "enableCustomServiceAccount": { "type": "boolean", "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)." }, "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" } } }, "GoogleCloudAiplatformV1TaskDescriptionStrategy": { "type": "object", "id": "GoogleCloudAiplatformV1TaskDescriptionStrategy", "properties": { "taskDescription": { "type": "string", "description": "Required. A general description of the type of synthetic data you want to generate. For example, \"Generate customer reviews for a new smartphone.\"" } }, "description": "Defines a generation strategy based on a general task description." }, "GoogleCloudAiplatformV1Retrieval": { "id": "GoogleCloudAiplatformV1Retrieval", "description": "Defines a retrieval tool that model can call to access external knowledge.", "properties": { "disableAttribution": { "type": "boolean", "deprecated": true, "description": "Optional. Deprecated. This option is no longer supported." }, "vertexAiSearch": { "$ref": "GoogleCloudAiplatformV1VertexAISearch", "description": "Set to use data source powered by Vertex AI Search." }, "vertexRagStore": { "description": "Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.", "$ref": "GoogleCloudAiplatformV1VertexRagStore" }, "externalApi": { "$ref": "GoogleCloudAiplatformV1ExternalApi", "description": "Use data source powered by external API for grounding." } }, "type": "object" }, "GoogleCloudAiplatformV1MutateDeployedModelOperationMetadata": { "id": "GoogleCloudAiplatformV1MutateDeployedModelOperationMetadata", "description": "Runtime operation information for EndpointService.MutateDeployedModel.", "type": "object", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1NotebookExecutionJobWorkbenchRuntimeContainerImage": { "description": "The definition of a user-provided container image to run the notebook execution in. Mirrors `google.cloud.notebooks.v2.ContainerImage`.", "properties": { "repository": { "description": "Required. The path to the container image repository. For example: `gcr.io/{project_id}/{image_name}`.", "type": "string" }, "tag": { "description": "Optional. The tag of the container image. If unset, defaults to `latest`.", "type": "string" } }, "id": "GoogleCloudAiplatformV1NotebookExecutionJobWorkbenchRuntimeContainerImage", "type": "object" }, "GoogleCloudAiplatformV1BatchPredictionJobOutputInfo": { "properties": { "bigqueryOutputDataset": { "readOnly": true, "type": "string", "description": "Output only. The path of the BigQuery dataset created, in `bq://projectId.bqDatasetId` format, into which the prediction output is written." }, "vertexMultimodalDatasetName": { "readOnly": true, "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}`", "type": "string" }, "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.", "readOnly": true, "type": "string" }, "gcsOutputDirectory": { "type": "string", "description": "Output only. The full path of the Cloud Storage directory created, into which the prediction output is written.", "readOnly": true } }, "description": "Further describes this job's output. Supplements output_config.", "type": "object", "id": "GoogleCloudAiplatformV1BatchPredictionJobOutputInfo" }, "GoogleCloudAiplatformV1RagContextsContext": { "id": "GoogleCloudAiplatformV1RagContextsContext", "type": "object", "description": "A context of the query.", "properties": { "sourceUri": { "type": "string", "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." }, "text": { "type": "string", "description": "The text chunk." }, "score": { "format": "double", "type": "number", "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": "GoogleCloudAiplatformV1RagChunk", "description": "Context of the retrieved chunk." }, "sourceDisplayName": { "description": "The file display name.", "type": "string" } } }, "GoogleCloudAiplatformV1AnnotationSpec": { "description": "Identifies a concept with which DataItems may be annotated with.", "id": "GoogleCloudAiplatformV1AnnotationSpec", "properties": { "createTime": { "description": "Output only. Timestamp when this AnnotationSpec was created.", "readOnly": true, "format": "google-datetime", "type": "string" }, "name": { "description": "Output only. Resource name of the AnnotationSpec.", "readOnly": true, "type": "string" }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when AnnotationSpec was last updated.", "type": "string", "readOnly": true }, "displayName": { "type": "string", "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." }, "etag": { "type": "string", "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." } }, "type": "object" }, "GoogleCloudAiplatformV1GenerateLossClustersRequestEvaluationResultList": { "properties": { "evaluationResults": { "description": "Required. The list of evaluation results to analyze.", "items": { "$ref": "GoogleCloudAiplatformV1EvaluationResult" }, "type": "array" } }, "type": "object", "description": "A wrapper to allow providing a list of items inline.", "id": "GoogleCloudAiplatformV1GenerateLossClustersRequestEvaluationResultList" }, "GoogleCloudAiplatformV1FindNeighborsRequestQueryRRF": { "description": "Parameters for RRF algorithm that combines search results.", "id": "GoogleCloudAiplatformV1FindNeighborsRequestQueryRRF", "type": "object", "properties": { "alpha": { "description": "Required. Users can provide an alpha value to give more weight to dense vs sparse results. For example, if the alpha is 0, we only return sparse and if the alpha is 1, we only return dense.", "format": "float", "type": "number" } } }, "GenaiVertexV1ErrorEvent": { "properties": { "error": { "$ref": "GenaiVertexV1Error" } }, "id": "GenaiVertexV1ErrorEvent", "type": "object" }, "GoogleCloudAiplatformV1SchemaTextSentimentSavedQueryMetadata": { "id": "GoogleCloudAiplatformV1SchemaTextSentimentSavedQueryMetadata", "description": "The metadata of SavedQuery contains TextSentiment Annotations.", "properties": { "sentimentMax": { "description": "The maximum sentiment of sentiment Anntoation in this SavedQuery.", "format": "int32", "type": "integer" } }, "type": "object" }, "GoogleCloudAiplatformV1PythonPackageSpec": { "type": "object", "id": "GoogleCloudAiplatformV1PythonPackageSpec", "description": "The spec of a Python packaged code.", "properties": { "env": { "description": "Environment variables to be passed to the python module. Maximum limit is 100.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1EnvVar" } }, "args": { "description": "Command line arguments to be passed to the Python task.", "type": "array", "items": { "type": "string" } }, "pythonModule": { "type": "string", "description": "Required. The Python module name to run after installing the packages." }, "packageUris": { "description": "Required. The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.", "type": "array", "items": { "type": "string" } }, "executorImageUri": { "description": "Required. The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of [pre-built containers for training](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). You must use an image from this list.", "type": "string" } } }, "GoogleCloudAiplatformV1MetricResult": { "description": "Result for a single metric on a single instance.", "id": "GoogleCloudAiplatformV1MetricResult", "properties": { "rubricVerdicts": { "items": { "$ref": "GoogleCloudAiplatformV1RubricVerdict" }, "readOnly": true, "description": "Output only. For rubric-based metrics, the verdicts for each rubric.", "type": "array" }, "error": { "description": "Output only. The error status for the metric result.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "score": { "description": "Output only. The score for the metric. Please refer to each metric's documentation for the meaning of the score.", "format": "float", "readOnly": true, "type": "number" }, "explanation": { "description": "Output only. The explanation for the metric result.", "readOnly": true, "type": "string" } }, "type": "object" }, "GenaiVertexV1FileSearchResultStep": { "properties": {}, "type": "object", "id": "GenaiVertexV1FileSearchResultStep", "description": "File Search result step." }, "GoogleCloudAiplatformV1ListStudiesResponse": { "properties": { "studies": { "description": "The studies associated with the project.", "items": { "$ref": "GoogleCloudAiplatformV1Study" }, "type": "array" }, "nextPageToken": { "type": "string", "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." } }, "id": "GoogleCloudAiplatformV1ListStudiesResponse", "description": "Response message for VizierService.ListStudies.", "type": "object" }, "GoogleCloudAiplatformV1RetrieveMemoriesResponseRetrievedMemory": { "properties": { "memory": { "$ref": "GoogleCloudAiplatformV1Memory", "description": "The retrieved Memory." }, "distance": { "format": "double", "type": "number", "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." } }, "description": "A retrieved memory.", "type": "object", "id": "GoogleCloudAiplatformV1RetrieveMemoriesResponseRetrievedMemory" }, "GenaiVertexV1VertexAISearchConfig": { "id": "GenaiVertexV1VertexAISearchConfig", "description": "Used to specify configuration for VertexAISearch.", "properties": { "engine": { "description": "Optional. Used to specify Vertex AI Search engine.", "type": "string" }, "datastores": { "items": { "type": "string" }, "description": "Optional. Used to specify Vertex AI Search datastores.", "type": "array" } }, "type": "object" }, "GoogleCloudAiplatformV1NetworkSpec": { "id": "GoogleCloudAiplatformV1NetworkSpec", "description": "Network spec.", "type": "object", "properties": { "network": { "description": "The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)", "type": "string" }, "enableInternetAccess": { "type": "boolean", "description": "Whether to enable public internet access. Default false." }, "subnetwork": { "type": "string", "description": "The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`" } } }, "GoogleCloudAiplatformV1TrajectoryRecallSpec": { "properties": {}, "id": "GoogleCloudAiplatformV1TrajectoryRecallSpec", "type": "object", "description": "Spec for TrajectoryRecall metric - returns a float score based on average recall of individual tool calls." }, "GoogleCloudAiplatformV1PscInterfaceConfig": { "type": "object", "description": "Configuration for PSC-I.", "id": "GoogleCloudAiplatformV1PscInterfaceConfig", "properties": { "networkAttachment": { "type": "string", "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." }, "dnsPeeringConfigs": { "items": { "$ref": "GoogleCloudAiplatformV1DnsPeeringConfig" }, "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.", "type": "array" } } }, "GoogleCloudAiplatformV1PublisherModelDocumentation": { "description": "A named piece of documentation.", "id": "GoogleCloudAiplatformV1PublisherModelDocumentation", "properties": { "title": { "type": "string", "description": "Required. E.g., OVERVIEW, USE CASES, DOCUMENTATION, SDK & SAMPLES, JAVA, NODE.JS, etc.." }, "content": { "type": "string", "description": "Required. Content of this piece of document (in Markdown format)." } }, "type": "object" }, "GoogleCloudAiplatformV1ImportFeatureValuesRequest": { "description": "Request message for FeaturestoreService.ImportFeatureValues.", "properties": { "featureTime": { "format": "google-datetime", "description": "Single Feature timestamp for all entities being imported. The timestamp must not have higher than millisecond precision.", "type": "string" }, "avroSource": { "$ref": "GoogleCloudAiplatformV1AvroSource" }, "workerCount": { "type": "integer", "description": "Specifies the number of workers that are used to write data to the Featurestore. Consider the online serving capacity that you require to achieve the desired import throughput without interfering with online serving. The value must be positive, and less than or equal to 100. If not set, defaults to using 1 worker. The low count ensures minimal impact on online serving performance.", "format": "int32" }, "featureTimeField": { "description": "Source column that holds the Feature timestamp for all Feature values in each entity.", "type": "string" }, "disableIngestionAnalysis": { "type": "boolean", "description": "If true, API doesn't start ingestion analysis pipeline." }, "entityIdField": { "description": "Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id.", "type": "string" }, "csvSource": { "$ref": "GoogleCloudAiplatformV1CsvSource" }, "featureSpecs": { "type": "array", "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.", "items": { "$ref": "GoogleCloudAiplatformV1ImportFeatureValuesRequestFeatureSpec" } }, "disableOnlineServing": { "description": "If set, data will not be imported for online serving. This is typically used for backfilling, where Feature generation timestamps are not in the timestamp range needed for online serving.", "type": "boolean" }, "bigquerySource": { "$ref": "GoogleCloudAiplatformV1BigQuerySource" } }, "id": "GoogleCloudAiplatformV1ImportFeatureValuesRequest", "type": "object" }, "GoogleCloudAiplatformV1ListMetadataSchemasResponse": { "description": "Response message for MetadataService.ListMetadataSchemas.", "id": "GoogleCloudAiplatformV1ListMetadataSchemasResponse", "type": "object", "properties": { "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" }, "metadataSchemas": { "items": { "$ref": "GoogleCloudAiplatformV1MetadataSchema" }, "description": "The MetadataSchemas found for the MetadataStore.", "type": "array" } } }, "GoogleCloudAiplatformV1RemoveDatapointsRequest": { "properties": { "datapointIds": { "description": "A list of datapoint ids to be deleted.", "type": "array", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1RemoveDatapointsRequest", "description": "Request message for IndexService.RemoveDatapoints", "type": "object" }, "GenaiVertexV1FileSearch": { "description": "A tool that can be used by the model to search files.", "properties": { "metadataFilter": { "type": "string", "description": "Metadata filter to apply to the semantic retrieval documents and chunks." }, "fileSearchStoreNames": { "items": { "type": "string" }, "description": "The file search store names to search.", "type": "array" }, "topK": { "format": "int32", "type": "integer", "description": "The number of semantic retrieval chunks to retrieve." } }, "type": "object", "id": "GenaiVertexV1FileSearch" }, "GoogleCloudAiplatformV1ListContextsResponse": { "description": "Response message for MetadataService.ListContexts.", "id": "GoogleCloudAiplatformV1ListContextsResponse", "properties": { "contexts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Context" }, "description": "The Contexts retrieved from the MetadataStore." }, "nextPageToken": { "type": "string", "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": "object" }, "GoogleCloudAiplatformV1EvaluationSet": { "id": "GoogleCloudAiplatformV1EvaluationSet", "type": "object", "properties": { "name": { "description": "Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`", "type": "string" }, "updateTime": { "description": "Output only. Timestamp when this item was last updated.", "readOnly": true, "type": "string", "format": "google-datetime" }, "evaluationItems": { "description": "Required. The EvaluationItems that are part of this dataset.", "type": "array", "items": { "type": "string" } }, "agentConfigs": { "additionalProperties": { "$ref": "GoogleCloudAiplatformV1AgentConfig" }, "type": "object", "description": "Optional. Static configurations for each agent associated with the items in this set. Key: `agent_id` (matches the `author` field in `events`). Value: The static configuration of the agent." }, "createTime": { "type": "string", "description": "Output only. Timestamp when this item was created.", "readOnly": true, "format": "google-datetime" }, "encryptionSpec": { "description": "Optional. Customer-managed encryption key spec for this EvaluationSet. If set, this EvaluationSet and its sub-resources will be secured by this key.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "metadata": { "description": "Optional. Metadata for the EvaluationSet.", "type": "any" }, "displayName": { "type": "string", "description": "Required. The display name of the EvaluationSet." } }, "description": "EvaluationSet is a collection of related EvaluationItems that are evaluated together." }, "GoogleCloudAiplatformV1GenAiAdvancedFeaturesConfig": { "type": "object", "description": "Configuration for GenAiAdvancedFeatures.", "properties": { "ragConfig": { "description": "Configuration for Retrieval Augmented Generation feature.", "$ref": "GoogleCloudAiplatformV1GenAiAdvancedFeaturesConfigRagConfig" } }, "id": "GoogleCloudAiplatformV1GenAiAdvancedFeaturesConfig" }, "GenaiVertexV1GoogleMaps": { "properties": { "enableWidget": { "type": "boolean", "description": "Whether to return a widget context token in the tool call result of the response." }, "latitude": { "description": "The latitude of the user's location.", "type": "number", "format": "double" }, "longitude": { "format": "double", "type": "number", "description": "The longitude of the user's location." } }, "description": "A tool that can be used by the model to call Google Maps.", "type": "object", "id": "GenaiVertexV1GoogleMaps" }, "GoogleCloudAiplatformV1BatchPredictionJobOutputConfig": { "id": "GoogleCloudAiplatformV1BatchPredictionJobOutputConfig", "properties": { "bigqueryDestination": { "$ref": "GoogleCloudAiplatformV1BigQueryDestination", "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`." }, "predictionsFormat": { "type": "string", "description": "Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats." }, "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.", "$ref": "GoogleCloudAiplatformV1GcsDestination" }, "vertexMultimodalDatasetDestination": { "$ref": "GoogleCloudAiplatformV1VertexMultimodalDatasetDestination", "description": "The details for a Vertex Multimodal Dataset that will be created for the output." } }, "type": "object", "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." }, "GoogleCloudAiplatformV1ListFeatureOnlineStoresResponse": { "type": "object", "id": "GoogleCloudAiplatformV1ListFeatureOnlineStoresResponse", "properties": { "nextPageToken": { "type": "string", "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." }, "featureOnlineStores": { "description": "The FeatureOnlineStores matching the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1FeatureOnlineStore" } } }, "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureOnlineStores." }, "GoogleCloudAiplatformV1CreateEndpointOperationMetadata": { "id": "GoogleCloudAiplatformV1CreateEndpointOperationMetadata", "properties": { "deploymentStage": { "readOnly": true, "enumDescriptions": [ "Default value. This value is unused.", "The deployment is initializing and setting up the environment.", "The deployment is preparing the model assets.", "The deployment is creating the underlying serving cluster.", "The deployment is adding nodes to the serving cluster.", "The deployment is getting the container image for the model server.", "The deployment is starting the model server.", "The deployment is performing finalization steps.", "The deployment has terminated.", "The deployment has succeeded.", "The deployment has failed." ], "description": "Output only. The deployment stage of the model. Only populated if this CreateEndpoint request deploys a model at the same time.", "enum": [ "DEPLOYMENT_STAGE_UNSPECIFIED", "STARTING_DEPLOYMENT", "PREPARING_MODEL", "CREATING_SERVING_CLUSTER", "ADDING_NODES_TO_CLUSTER", "GETTING_CONTAINER_IMAGE", "STARTING_MODEL_SERVER", "FINISHING_UP", "DEPLOYMENT_TERMINATED", "SUCCESSFULLY_DEPLOYED", "FAILED_TO_DEPLOY" ], "type": "string" }, "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "type": "object", "description": "Runtime operation information for EndpointService.CreateEndpoint." }, "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotation": { "properties": { "polylineAnnotation": { "$ref": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolylineAnnotation", "description": "Polyline annotation." }, "maskAnnotation": { "$ref": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationMaskAnnotation", "description": "Mask based segmentation annotation. Only one mask annotation can exist for one image." }, "polygonAnnotation": { "description": "Polygon annotation.", "$ref": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolygonAnnotation" } }, "description": "Annotation details specific to image segmentation.", "id": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotation", "type": "object" }, "GenaiVertexV1InteractionStatusUpdate": { "id": "GenaiVertexV1InteractionStatusUpdate", "type": "object", "properties": { "status": { "enum": [ "UNSPECIFIED", "IN_PROGRESS", "REQUIRES_ACTION", "COMPLETED", "FAILED", "CANCELLED", "INCOMPLETE", "QUEUED" ], "enumDescriptions": [ "Default value. This value is unused.", "The interaction is in progress.", "The interaction requires action/input from the user.", "The interaction is completed.", "The interaction failed.", "The interaction was cancelled.", "The interaction is completed, but contains incomplete results (e.g. hitting max_tokens).", "The interaction is queued, waiting for processing (e.g. waiting for off-peak capacity)." ], "type": "string" }, "interactionId": { "type": "string" }, "usage": { "description": "Model usage statistics up to this checkpoint.", "$ref": "GenaiVertexV1InteractionUsage" } } }, "GoogleCloudAiplatformV1ErrorAnalysisAnnotationAttributedItem": { "type": "object", "properties": { "annotationResourceName": { "type": "string", "description": "The unique ID for each annotation. Used by FE to allocate the annotation in DB." }, "distance": { "description": "The distance of this item to the annotation.", "type": "number", "format": "double" } }, "id": "GoogleCloudAiplatformV1ErrorAnalysisAnnotationAttributedItem", "description": "Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type." }, "GoogleCloudAiplatformV1EvaluationRunMetricLLMBasedMetricSpec": { "type": "object", "description": "Specification for an LLM based metric.", "properties": { "rubricGenerationSpec": { "$ref": "GoogleCloudAiplatformV1EvaluationRunMetricRubricGenerationSpec", "description": "Dynamically generate rubrics using this specification." }, "predefinedRubricGenerationSpec": { "$ref": "GoogleCloudAiplatformV1EvaluationRunMetricPredefinedMetricSpec", "description": "Dynamically generate rubrics using a predefined spec." }, "metricPromptTemplate": { "type": "string", "description": "Required. Template for the prompt sent to the judge model." }, "judgeAutoraterConfig": { "description": "Optional. Optional configuration for the judge LLM (Autorater).", "$ref": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigAutoraterConfig" }, "systemInstruction": { "description": "Optional. System instructions for the judge model.", "type": "string" }, "rubricGroupKey": { "type": "string", "description": "Use a pre-defined group of rubrics associated with the input. Refers to a key in the rubric_groups map of EvaluationInstance." }, "additionalConfig": { "type": "object", "description": "Optional. Optional additional configuration for the metric.", "additionalProperties": { "type": "any", "description": "Properties of the object." } } }, "id": "GoogleCloudAiplatformV1EvaluationRunMetricLLMBasedMetricSpec" }, "GoogleCloudAiplatformV1Fact": { "type": "object", "properties": { "uri": { "description": "If present, this uri links to the source of the fact.", "type": "string" }, "summary": { "description": "If present, the summary/snippet of the fact.", "type": "string" }, "query": { "description": "Query that is used to retrieve this fact.", "type": "string" }, "vectorDistance": { "format": "double", "deprecated": true, "description": "If present, the distance between the query vector and this fact vector.", "type": "number" }, "title": { "description": "If present, it refers to the title of this fact.", "type": "string" }, "score": { "format": "double", "type": "number", "description": "If present, according to the underlying Vector DB and the selected metric type, the score can be either the distance or the similarity between the query and the fact and its range depends on the metric type. For example, if the metric type is COSINE_DISTANCE, it represents the distance between the query and the fact. The larger the distance, the less relevant the fact is to the query. The range is [0, 2], while 0 means the most relevant and 2 means the least relevant." }, "chunk": { "description": "If present, chunk properties.", "$ref": "GoogleCloudAiplatformV1RagChunk" } }, "description": "The fact used in grounding.", "id": "GoogleCloudAiplatformV1Fact" }, "GoogleCloudAiplatformV1MemoryFilter": { "type": "object", "id": "GoogleCloudAiplatformV1MemoryFilter", "properties": { "value": { "$ref": "GoogleCloudAiplatformV1MemoryMetadataValue", "description": "Represents the value to compare to." }, "op": { "description": "Represents the operator to apply to the filter. If not set, then EQUAL will be used.", "enum": [ "OPERATOR_UNSPECIFIED", "EQUAL", "GREATER_THAN", "LESS_THAN" ], "type": "string", "enumDescriptions": [ "Represents an unspecified operator. Defaults to EQUAL.", "Equal to.", "Greater than.", "Less than." ] }, "negate": { "type": "boolean", "description": "Indicates whether the filter will be negated." }, "key": { "description": "Represents the key of the filter. For example, \"author\" would apply to `metadata` entries with the key \"author\".", "type": "string" } }, "description": "Filter to apply when retrieving memories." }, "GenaiVertexV1GoogleMapsCallStepGoogleMapsCallStepArguments": { "properties": { "queries": { "description": "The queries to be executed.", "items": { "type": "string" }, "type": "array" } }, "type": "object", "description": "The arguments to pass to the Google Maps tool.", "id": "GenaiVertexV1GoogleMapsCallStepGoogleMapsCallStepArguments" }, "GoogleCloudAiplatformV1ProbeExecAction": { "properties": { "command": { "type": "array", "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.", "items": { "type": "string" } } }, "description": "ExecAction specifies a command to execute.", "type": "object", "id": "GoogleCloudAiplatformV1ProbeExecAction" }, "GoogleCloudAiplatformV1RagFileParsingConfig": { "id": "GoogleCloudAiplatformV1RagFileParsingConfig", "description": "Specifies the parsing config for RagFiles.", "type": "object", "properties": { "llmParser": { "description": "The LLM Parser to use for RagFiles.", "$ref": "GoogleCloudAiplatformV1RagFileParsingConfigLlmParser" }, "layoutParser": { "$ref": "GoogleCloudAiplatformV1RagFileParsingConfigLayoutParser", "description": "The Layout Parser to use for RagFiles." } } }, "GenaiVertexV1GoogleSearch": { "properties": { "searchTypes": { "type": "array", "items": { "enum": [ "SEARCH_TYPE_UNSPECIFIED", "SEARCH_TYPE_WEB_SEARCH", "SEARCH_TYPE_IMAGE_SEARCH", "SEARCH_TYPE_ENTERPRISE_WEB_SEARCH" ], "type": "string", "enumDescriptions": [ "Unspecified search type. This value should not be used.", "Setting this field enables web search. Only text results are returned.", "Setting this field enables image search. Image bytes are returned.", "Setting this field enables enterprise web search." ] }, "description": "The types of search grounding to enable." } }, "type": "object", "id": "GenaiVertexV1GoogleSearch", "description": "A tool that can be used by the model to search Google." }, "GenaiVertexV1GoogleSearchResultDelta": { "type": "object", "id": "GenaiVertexV1GoogleSearchResultDelta", "properties": { "isError": { "type": "boolean" }, "result": { "items": { "$ref": "GenaiVertexV1GoogleSearchResultContentGoogleSearchResult" }, "type": "array" } } }, "GoogleCloudAiplatformV1AudioTranscriptionConfigLanguageHints": { "description": "Deprecated: Use top-level `language_codes` instead. Provides hints to the model about possible languages present in the audio.", "id": "GoogleCloudAiplatformV1AudioTranscriptionConfigLanguageHints", "properties": { "languageCodes": { "deprecated": true, "items": { "type": "string" }, "type": "array", "description": "Required. Deprecated: Use top-level `language_codes` instead. BCP-47 language codes. At least one must be specified." } }, "type": "object", "deprecated": true }, "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolylineAnnotation": { "description": "Represents a polyline in image.", "type": "object", "properties": { "displayName": { "description": "The display name of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "vertexes": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SchemaVertex" }, "description": "The vertexes are connected one by one and the last vertex in not connected to the first one." }, "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" } }, "id": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolylineAnnotation" }, "GoogleCloudAiplatformV1Execution": { "properties": { "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" }, "name": { "type": "string", "description": "Output only. The resource name of the Execution.", "readOnly": true }, "createTime": { "description": "Output only. Timestamp when this Execution was created.", "type": "string", "readOnly": true, "format": "google-datetime" }, "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" }, "updateTime": { "readOnly": true, "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when this Execution was last updated." }, "metadata": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "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." }, "state": { "type": "string", "enum": [ "STATE_UNSPECIFIED", "NEW", "RUNNING", "COMPLETE", "FAILED", "CACHED", "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.", "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." ] }, "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" }, "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)." }, "displayName": { "description": "User provided display name of the Execution. May be up to 128 Unicode characters.", "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1Execution", "description": "Instance of a general execution." }, "GenaiVertexV1GoogleMapsResultContentGoogleMapsResult": { "description": "The result of the Google Maps.", "type": "object", "id": "GenaiVertexV1GoogleMapsResultContentGoogleMapsResult", "properties": { "widgetContextToken": { "type": "string", "description": "Resource name of the Google Maps widget context token." }, "places": { "description": "The places that were found.", "items": { "$ref": "GenaiVertexV1GoogleMapsResultContentGoogleMapsResultPlaces" }, "type": "array" } } }, "GoogleCloudAiplatformV1SchemaPromptSpecTranslationExample": { "properties": { "referenceSentencePairLists": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecReferenceSentencePairList" }, "description": "The reference sentences from inline text." }, "referenceSentencesFileInputs": { "description": "The reference sentences from file.", "items": { "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationSentenceFileInput" }, "type": "array" } }, "description": "The translation example that contains reference sentences from various sources.", "type": "object", "id": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationExample" }, "GoogleCloudAiplatformV1RetrieveContextsRequestVertexRagStore": { "type": "object", "id": "GoogleCloudAiplatformV1RetrieveContextsRequestVertexRagStore", "properties": { "vectorDistanceThreshold": { "deprecated": true, "type": "number", "format": "double", "description": "Optional. Only return contexts with vector distance smaller than the threshold." }, "ragResources": { "items": { "$ref": "GoogleCloudAiplatformV1RetrieveContextsRequestVertexRagStoreRagResource" }, "description": "Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.", "type": "array" } }, "description": "The data source for Vertex RagStore." }, "GoogleCloudAiplatformV1Blob": { "description": "A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video.", "properties": { "displayName": { "description": "Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.", "type": "string" }, "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" }, "data": { "type": "string", "description": "Required. The raw bytes of the data.", "format": "byte" } }, "id": "GoogleCloudAiplatformV1Blob", "type": "object" }, "GoogleCloudAiplatformV1NotebookExecutionJobWorkbenchRuntime": { "id": "GoogleCloudAiplatformV1NotebookExecutionJobWorkbenchRuntime", "type": "object", "description": "Configuration for a Workbench Instances-based environment.", "properties": { "vmImage": { "$ref": "GoogleCloudAiplatformV1NotebookExecutionJobWorkbenchRuntimeVmImage", "description": "A specific Compute Engine VM image to run the notebook on." }, "customContainerImage": { "description": "A user-provided container image. The notebook executes inside this container on a managed container-host (COS) VM.", "$ref": "GoogleCloudAiplatformV1NotebookExecutionJobWorkbenchRuntimeContainerImage" } } }, "GoogleCloudAiplatformV1ListHyperparameterTuningJobsResponse": { "properties": { "hyperparameterTuningJobs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1HyperparameterTuningJob" }, "description": "List of HyperparameterTuningJobs in the requested page. HyperparameterTuningJob.trials of the jobs will be not be returned." }, "nextPageToken": { "type": "string", "description": "A token to retrieve the next page of results. Pass to ListHyperparameterTuningJobsRequest.page_token to obtain that page." } }, "id": "GoogleCloudAiplatformV1ListHyperparameterTuningJobsResponse", "description": "Response message for JobService.ListHyperparameterTuningJobs", "type": "object" }, "GoogleCloudAiplatformV1SchemaPredictParamsVideoClassificationPredictionParams": { "id": "GoogleCloudAiplatformV1SchemaPredictParamsVideoClassificationPredictionParams", "properties": { "shotClassification": { "type": "boolean", "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" }, "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" }, "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" }, "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" }, "confidenceThreshold": { "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", "format": "float", "type": "number" } }, "type": "object", "description": "Prediction model parameters for Video Classification." }, "GoogleCloudAiplatformV1SearchMigratableResourcesResponse": { "properties": { "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" }, "migratableResources": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1MigratableResource" }, "description": "All migratable resources that can be migrated to the location specified in the request." } }, "type": "object", "description": "Response message for MigrationService.SearchMigratableResources.", "id": "GoogleCloudAiplatformV1SearchMigratableResourcesResponse" }, "GoogleCloudAiplatformV1TFRecordDestination": { "id": "GoogleCloudAiplatformV1TFRecordDestination", "description": "The storage details for TFRecord output content.", "properties": { "gcsDestination": { "description": "Required. Google Cloud Storage location.", "$ref": "GoogleCloudAiplatformV1GcsDestination" } }, "type": "object" }, "GoogleCloudAiplatformV1FeatureOnlineStore": { "properties": { "labels": { "additionalProperties": { "type": "string" }, "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" }, "encryptionSpec": { "description": "Optional. Customer-managed encryption key spec for data storage. If set, online store will be secured by this key.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "dedicatedServingEndpoint": { "$ref": "GoogleCloudAiplatformV1FeatureOnlineStoreDedicatedServingEndpoint", "description": "Optional. The dedicated serving endpoint for this FeatureOnlineStore, which is different from common Vertex service endpoint." }, "createTime": { "description": "Output only. Timestamp when this FeatureOnlineStore was created.", "format": "google-datetime", "readOnly": true, "type": "string" }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "optimized": { "$ref": "GoogleCloudAiplatformV1FeatureOnlineStoreOptimized", "description": "Contains settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. When choose Optimized storage type, need to set PrivateServiceConnectConfig.enable_private_service_connect to use private endpoint. Otherwise will use public endpoint by default." }, "state": { "type": "string", "enum": [ "STATE_UNSPECIFIED", "STABLE", "UPDATING" ], "readOnly": true, "description": "Output only. State of the featureOnlineStore.", "enumDescriptions": [ "Default value. This value is unused.", "State when the featureOnlineStore configuration is not being updated and the fields reflect the current configuration of the featureOnlineStore. The featureOnlineStore is usable in this state.", "The state of the featureOnlineStore configuration when it is being updated. During an update, the fields reflect either the original configuration or the updated configuration of the featureOnlineStore. The featureOnlineStore is still usable in this state." ] }, "satisfiesPzs": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "bigtable": { "description": "Contains settings for the Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.", "$ref": "GoogleCloudAiplatformV1FeatureOnlineStoreBigtable" }, "updateTime": { "format": "google-datetime", "type": "string", "readOnly": true, "description": "Output only. Timestamp when this FeatureOnlineStore was last updated." }, "name": { "description": "Identifier. Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`", "type": "string" } }, "type": "object", "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.", "id": "GoogleCloudAiplatformV1FeatureOnlineStore" }, "GoogleCloudAiplatformV1PscAutomatedEndpoints": { "type": "object", "properties": { "projectId": { "description": "Corresponding project_id in pscAutomationConfigs", "type": "string" }, "matchAddress": { "type": "string", "description": "Ip Address created by the automated forwarding rule." }, "network": { "description": "Corresponding network in pscAutomationConfigs.", "type": "string" } }, "description": "PscAutomatedEndpoints defines the output of the forwarding rule automatically created by each PscAutomationConfig.", "id": "GoogleCloudAiplatformV1PscAutomatedEndpoints" }, "GoogleCloudAiplatformV1TrajectoryInOrderMatchSpec": { "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.", "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1TrajectoryInOrderMatchSpec" }, "GoogleCloudAiplatformV1GenerationConfigRoutingConfigManualRoutingMode": { "id": "GoogleCloudAiplatformV1GenerationConfigRoutingConfigManualRoutingMode", "type": "object", "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." }, "GoogleCloudAiplatformV1DirectPredictRequest": { "type": "object", "description": "Request message for PredictionService.DirectPredict.", "properties": { "parameters": { "description": "The parameters that govern the prediction.", "$ref": "GoogleCloudAiplatformV1Tensor" }, "inputs": { "items": { "$ref": "GoogleCloudAiplatformV1Tensor" }, "type": "array", "description": "The prediction input." } }, "id": "GoogleCloudAiplatformV1DirectPredictRequest" }, "GoogleCloudAiplatformV1SafetyRating": { "id": "GoogleCloudAiplatformV1SafetyRating", "properties": { "category": { "enumDeprecated": [ false, false, false, false, false, true, false, false, false, false, false ], "type": "string", "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" ], "readOnly": true, "description": "Output only. The harm category of this rating.", "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." ] }, "severityScore": { "type": "number", "description": "Output only. The severity score of harm for this category.", "readOnly": true, "format": "float" }, "probability": { "description": "Output only. The probability of harm for this category.", "readOnly": true, "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" ], "type": "string" }, "severity": { "description": "Output only. The severity of harm for this category.", "type": "string", "readOnly": true, "enum": [ "HARM_SEVERITY_UNSPECIFIED", "HARM_SEVERITY_NEGLIGIBLE", "HARM_SEVERITY_LOW", "HARM_SEVERITY_MEDIUM", "HARM_SEVERITY_HIGH" ], "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." ] }, "overwrittenThreshold": { "enum": [ "HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF" ], "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." ], "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 }, "probabilityScore": { "readOnly": true, "type": "number", "description": "Output only. The probability score of harm for this category.", "format": "float" }, "blocked": { "type": "boolean", "readOnly": true, "description": "Output only. Indicates whether the content was blocked because of this rating." } }, "type": "object", "description": "A safety rating for a piece of content. The safety rating contains the harm category and the harm probability level." }, "GoogleCloudAiplatformV1ImportEvaluationSetRequestInlineSource": { "description": "Wrapper for inline data.", "properties": { "content": { "format": "byte", "type": "string", "description": "Required. The content of the inline data." }, "importSchemaConfig": { "description": "Required. Schema configuration for the inline data.", "$ref": "GoogleCloudAiplatformV1ImportEvaluationSetRequestImportSchemaConfig" } }, "id": "GoogleCloudAiplatformV1ImportEvaluationSetRequestInlineSource", "type": "object" }, "GoogleCloudAiplatformV1TrajectoryInOrderMatchResults": { "properties": { "trajectoryInOrderMatchMetricValues": { "type": "array", "description": "Output only. TrajectoryInOrderMatch metric values.", "items": { "$ref": "GoogleCloudAiplatformV1TrajectoryInOrderMatchMetricValue" }, "readOnly": true } }, "description": "Results for TrajectoryInOrderMatch metric.", "type": "object", "id": "GoogleCloudAiplatformV1TrajectoryInOrderMatchResults" }, "CloudAiLargeModelsVisionGenerateVideoExperimentsVideoTransform": { "type": "object", "properties": { "noiseStrength": { "format": "float", "type": "number", "description": "Optional. Noise strength for video transform." }, "mask": { "$ref": "CloudAiLargeModelsVisionGenerateVideoRequestVideo", "description": "Optional. Mask for video transform (diffdiff)." }, "initializationVideo": { "$ref": "CloudAiLargeModelsVisionGenerateVideoRequestVideo", "description": "Optional. Input for video transform (sdedit, diffdiff). Note the input video from the main GenerateVideoRequest will be used as the conditioning." } }, "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsVideoTransform" }, "CloudAiLargeModelsVisionGenerateVideoExperimentsOmniRewriterConfig": { "description": "Configuration for Omni Rewriter.", "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsOmniRewriterConfig", "properties": { "rewriterInputFps": { "type": "integer", "description": "Optional. FPS used to generate gemini chunks for video inputs.", "format": "int32" }, "maxChunkDuration": { "type": "number", "format": "float", "description": "Optional. Maximum duration of a chunk in seconds." } }, "type": "object" }, "GenaiVertexV1ResponseFormatList": { "type": "object", "properties": { "responseFormats": { "items": { "$ref": "GenaiVertexV1ResponseFormat" }, "type": "array" } }, "id": "GenaiVertexV1ResponseFormatList" }, "CloudAiLargeModelsVisionRaiInfo": { "description": "Next ID: 6", "id": "CloudAiLargeModelsVisionRaiInfo", "type": "object", "properties": { "raiCategories": { "type": "array", "items": { "type": "string" }, "description": "List of rai categories' information to return" }, "modelName": { "type": "string", "description": "The model name used to indexing into the RaiFilterConfig map. Would either be one of imagegeneration@002-006, imagen-3.0-... api endpoint names, or internal names used for mapping to different filter configs (genselfie, ai_watermark) than its api endpoint." }, "detectedLabels": { "items": { "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabels" }, "description": "The list of detected labels for different rai categories.", "type": "array" }, "scores": { "type": "array", "description": "List of rai scores mapping to the rai categories. Rounded to 1 decimal place.", "items": { "type": "number", "format": "float" } }, "blockedEntities": { "items": { "type": "string" }, "description": "List of blocked entities from the blocklist if it is detected.", "type": "array" } } }, "GoogleCloudAiplatformV1CustomCodeExecutionResult": { "properties": { "score": { "readOnly": true, "format": "float", "description": "Output only. Custom code execution score.", "type": "number" } }, "type": "object", "description": "Result for custom code execution metric.", "id": "GoogleCloudAiplatformV1CustomCodeExecutionResult" }, "GoogleCloudAiplatformV1EvaluationRunMetricRubricBasedMetricSpec": { "id": "GoogleCloudAiplatformV1EvaluationRunMetricRubricBasedMetricSpec", "type": "object", "properties": { "rubricGroupKey": { "type": "string", "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`." }, "rubricGenerationSpec": { "$ref": "GoogleCloudAiplatformV1EvaluationRunMetricRubricGenerationSpec", "description": "Dynamically generate rubrics for evaluation using this specification." }, "inlineRubrics": { "description": "Use rubrics provided directly in the spec.", "$ref": "GoogleCloudAiplatformV1EvaluationRunMetricRubricBasedMetricSpecRepeatedRubrics" }, "metricPromptTemplate": { "type": "string", "description": "Optional. Template for the prompt used by the judge model to evaluate against rubrics." }, "judgeAutoraterConfig": { "description": "Optional. Optional configuration for the judge LLM (Autorater). The definition of AutoraterConfig needs to be provided.", "$ref": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigAutoraterConfig" } }, "description": "Specification for a metric that is based on rubrics." }, "GoogleCloudAiplatformV1UrlContextMetadata": { "id": "GoogleCloudAiplatformV1UrlContextMetadata", "properties": { "urlMetadata": { "readOnly": true, "type": "array", "description": "Output only. A list of URL metadata, with one entry for each URL retrieved by the tool.", "items": { "$ref": "GoogleCloudAiplatformV1UrlMetadata" } } }, "description": "Metadata returned when the model uses the `url_context` tool to get information from a user-provided URL.", "type": "object" }, "GoogleCloudAiplatformV1MetadataStoreDataplexConfig": { "description": "Represents Dataplex integration settings.", "properties": { "enabledPipelinesLineage": { "description": "Optional. Whether or not Data Lineage synchronization is enabled for Vertex Pipelines.", "type": "boolean" } }, "type": "object", "id": "GoogleCloudAiplatformV1MetadataStoreDataplexConfig" }, "GoogleCloudAiplatformV1MemoryBankCustomizationConfig": { "description": "Represents configuration for organizing natural language memories for a particular scope.", "properties": { "consolidationConfig": { "$ref": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigConsolidationConfig", "description": "Optional. Represents configuration for customizing how memories are consolidated together." }, "scopeKeys": { "type": "array", "items": { "type": "string" }, "description": "Optional. Represents the scope keys (i.e. 'user_id') for which to use this config. A request's scope must include all of the provided keys for the config to be used (order does not matter). If empty, then the config will be used for all requests that do not have a more specific config. Only one default config is allowed per Memory Bank." }, "enableThirdPersonMemories": { "type": "boolean", "description": "Optional. Indicates whether the memories will be generated in the third person (i.e. \"The user generates memories with Memory Bank.\"). By default, the memories will be generated in the first person (i.e. \"I generate memories with Memory Bank.\")" }, "disableNaturalLanguageMemories": { "description": "Optional. Indicates whether natural language memory generation should be disabled for all requests. By default, natural language memory generation is enabled. Set this to `true` when you only want to generate structured memories.", "type": "boolean" }, "generateMemoriesExamples": { "items": { "$ref": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExample" }, "type": "array", "description": "Optional. Provides examples of how to generate memories for a particular scope." }, "memoryTopics": { "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.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigMemoryTopic" } } }, "id": "GoogleCloudAiplatformV1MemoryBankCustomizationConfig", "type": "object" }, "GoogleCloudAiplatformV1DirectRawPredictResponse": { "type": "object", "id": "GoogleCloudAiplatformV1DirectRawPredictResponse", "description": "Response message for PredictionService.DirectRawPredict.", "properties": { "output": { "type": "string", "format": "byte", "description": "The prediction output." } } }, "GoogleCloudAiplatformV1WriteFeatureValuesRequest": { "description": "Request message for FeaturestoreOnlineServingService.WriteFeatureValues.", "properties": { "payloads": { "description": "Required. The entities to be written. Up to 100,000 feature values can be written across all `payloads`.", "items": { "$ref": "GoogleCloudAiplatformV1WriteFeatureValuesPayload" }, "type": "array" } }, "type": "object", "id": "GoogleCloudAiplatformV1WriteFeatureValuesRequest" }, "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInput": { "type": "object", "id": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInput", "description": "Input for question answering correctness metric.", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessSpec", "description": "Required. Spec for question answering correctness score metric." }, "instance": { "description": "Required. Question answering correctness instance.", "$ref": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInstance" } } }, "GoogleCloudAiplatformV1LineageSubgraph": { "description": "A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.", "id": "GoogleCloudAiplatformV1LineageSubgraph", "properties": { "executions": { "description": "The Execution nodes in the subgraph.", "items": { "$ref": "GoogleCloudAiplatformV1Execution" }, "type": "array" }, "artifacts": { "items": { "$ref": "GoogleCloudAiplatformV1Artifact" }, "description": "The Artifact nodes in the subgraph.", "type": "array" }, "events": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Event" }, "description": "The Event edges between Artifacts and Executions in the subgraph." } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaPromptInstancePromptExecution": { "description": "A prompt instance's parameters set that contains a set of variable values.", "properties": { "arguments": { "description": "Maps variable names to their value.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1SchemaPromptInstanceVariableValue" } } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaPromptInstancePromptExecution" }, "GoogleCloudAiplatformV1FeatureOnlineStoreBigtable": { "type": "object", "id": "GoogleCloudAiplatformV1FeatureOnlineStoreBigtable", "properties": { "enableDirectBigtableAccess": { "description": "Optional. It true, enable direct access to the Bigtable instance.", "type": "boolean" }, "bigtableMetadata": { "readOnly": true, "description": "Output only. Metadata of the Bigtable instance. Output only.", "$ref": "GoogleCloudAiplatformV1FeatureOnlineStoreBigtableBigtableMetadata" }, "zone": { "description": "Optional. The zone where the underlying Bigtable cluster for the primary Bigtable instance will be provisioned. Only the zone must be provided. For example, only \"us-central1-a\" should be provided.", "type": "string" }, "autoScaling": { "description": "Required. Autoscaling config applied to Bigtable Instance.", "$ref": "GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScaling" } } }, "GoogleCloudAiplatformV1CsvSource": { "properties": { "gcsSource": { "$ref": "GoogleCloudAiplatformV1GcsSource", "description": "Required. Google Cloud Storage location." } }, "id": "GoogleCloudAiplatformV1CsvSource", "description": "The storage details for CSV input content.", "type": "object" }, "GoogleCloudAiplatformV1PairwiseMetricInput": { "properties": { "instance": { "description": "Required. Pairwise metric instance.", "$ref": "GoogleCloudAiplatformV1PairwiseMetricInstance" }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1PairwiseMetricSpec", "description": "Required. Spec for pairwise metric." } }, "id": "GoogleCloudAiplatformV1PairwiseMetricInput", "description": "Input for pairwise metric.", "type": "object" }, "GoogleCloudAiplatformV1GenerateFetchAccessTokenRequest": { "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1GenerateFetchAccessTokenRequest", "description": "Request message for FeatureOnlineStoreService.GenerateFetchAccessToken." }, "GoogleCloudAiplatformV1MutateDeployedIndexOperationMetadata": { "description": "Runtime operation information for IndexEndpointService.MutateDeployedIndex.", "type": "object", "properties": { "deployedIndexId": { "type": "string", "description": "The unique index id specified by user" }, "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The operation generic information." } }, "id": "GoogleCloudAiplatformV1MutateDeployedIndexOperationMetadata" }, "GoogleCloudAiplatformV1FeatureStatsAnomaly": { "type": "object", "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": { "statsUri": { "type": "string", "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)." }, "distributionDeviation": { "type": "number", "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.", "format": "double" }, "anomalyDetectionThreshold": { "type": "number", "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.", "format": "double" }, "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" }, "endTime": { "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).", "type": "string", "format": "google-datetime" }, "startTime": { "type": "string", "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)." }, "score": { "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.", "type": "number", "format": "double" } }, "id": "GoogleCloudAiplatformV1FeatureStatsAnomaly" }, "GoogleCloudAiplatformV1RetrieveMemoriesRequestSimilaritySearchParams": { "description": "Parameters for semantic similarity search based retrieval.", "properties": { "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." }, "searchQuery": { "type": "string", "description": "Required. Query to use for similarity search retrieval. If provided, then the parent ReasoningEngine must have ReasoningEngineContextSpec.MemoryBankConfig.SimilaritySearchConfig set." } }, "id": "GoogleCloudAiplatformV1RetrieveMemoriesRequestSimilaritySearchParams", "type": "object" }, "GoogleCloudAiplatformV1IndexDatapointRestriction": { "type": "object", "description": "Restriction of a datapoint which describe its attributes(tokens) from each of several attribute categories(namespaces).", "properties": { "denyList": { "type": "array", "description": "The attributes to deny in this namespace. e.g.: 'blue'", "items": { "type": "string" } }, "namespace": { "description": "The namespace of this restriction. e.g.: color.", "type": "string" }, "allowList": { "type": "array", "items": { "type": "string" }, "description": "The attributes to allow in this namespace. e.g.: 'red'" } }, "id": "GoogleCloudAiplatformV1IndexDatapointRestriction" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation", "properties": { "timeFormat": { "type": "string", "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)" }, "columnName": { "type": "string" } }, "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." }, "GoogleCloudAiplatformV1RetrieveMemoriesRequestSimpleRetrievalParams": { "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": { "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", "type": "integer" } }, "id": "GoogleCloudAiplatformV1RetrieveMemoriesRequestSimpleRetrievalParams", "type": "object" }, "GoogleCloudAiplatformV1PredictRequestResponseLoggingConfig": { "properties": { "bigqueryDestination": { "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`", "$ref": "GoogleCloudAiplatformV1BigQueryDestination" }, "enabled": { "type": "boolean", "description": "If logging is enabled or not." }, "samplingRate": { "description": "Percentage of requests to be logged, expressed as a fraction in range(0,1].", "type": "number", "format": "double" } }, "type": "object", "description": "Configuration for logging request-response to a BigQuery table.", "id": "GoogleCloudAiplatformV1PredictRequestResponseLoggingConfig" }, "GoogleCloudAiplatformV1PurgeArtifactsRequest": { "description": "Request message for MetadataService.PurgeArtifacts.", "properties": { "filter": { "type": "string", "description": "Required. A required filter matching the Artifacts to be purged. E.g., `update_time \u003c= 2020-11-19T11:30:00-04:00`." }, "force": { "type": "boolean", "description": "Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Artifact names that would be deleted." } }, "type": "object", "id": "GoogleCloudAiplatformV1PurgeArtifactsRequest" }, "GenaiVertexV1GoogleMapsResultStep": { "type": "object", "description": "Google Maps result step.", "id": "GenaiVertexV1GoogleMapsResultStep", "properties": { "result": { "type": "array", "items": { "$ref": "GenaiVertexV1GoogleMapsResultStepGoogleMapsResultItem" } } } }, "GoogleCloudAiplatformV1EvaluationRunMetricPredefinedMetricSpec": { "id": "GoogleCloudAiplatformV1EvaluationRunMetricPredefinedMetricSpec", "type": "object", "description": "Specification for a pre-defined metric.", "properties": { "metricSpecName": { "type": "string", "description": "Required. The name of a pre-defined metric, such as \"instruction_following_v1\" or \"text_quality_v1\"." }, "parameters": { "type": "object", "description": "Optional. The parameters needed to run the pre-defined metric.", "additionalProperties": { "description": "Properties of the object.", "type": "any" } } } }, "GoogleCloudAiplatformV1FetchPredictOperationRequest": { "type": "object", "id": "GoogleCloudAiplatformV1FetchPredictOperationRequest", "properties": { "operationName": { "description": "Required. The server-assigned name for the operation.", "type": "string" } }, "description": "Request message for PredictionService.FetchPredictOperation." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingMetadata": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingMetadata", "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" } }, "type": "object", "description": "Model metadata specific to TFT Forecasting." }, "GoogleCloudAiplatformV1SchemaTextExtractionAnnotation": { "description": "Annotation details specific to text extraction.", "properties": { "annotationSpecId": { "type": "string", "description": "The resource Id of the AnnotationSpec that this Annotation pertains to." }, "textSegment": { "description": "The segment of the text content.", "$ref": "GoogleCloudAiplatformV1SchemaTextSegment" }, "displayName": { "type": "string", "description": "The display name of the AnnotationSpec that this Annotation pertains to." } }, "id": "GoogleCloudAiplatformV1SchemaTextExtractionAnnotation", "type": "object" }, "GoogleCloudAiplatformV1FeatureViewIndexConfig": { "description": "Configuration for vector indexing.", "properties": { "embeddingColumn": { "description": "Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search.", "type": "string" }, "crowdingColumn": { "description": "Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.", "type": "string" }, "treeAhConfig": { "description": "Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396", "$ref": "GoogleCloudAiplatformV1FeatureViewIndexConfigTreeAHConfig" }, "embeddingDimension": { "type": "integer", "description": "Optional. The number of dimensions of the input embedding.", "format": "int32" }, "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.", "$ref": "GoogleCloudAiplatformV1FeatureViewIndexConfigBruteForceConfig" }, "distanceMeasureType": { "enumDescriptions": [ "Should not be set.", "Euclidean (L_2) Distance.", "Cosine Distance. Defined as 1 - cosine similarity. We strongly suggest using DOT_PRODUCT_DISTANCE + UNIT_L2_NORM instead of COSINE distance. Our algorithms have been more optimized for DOT_PRODUCT distance which, when combined with UNIT_L2_NORM, is mathematically equivalent to COSINE distance and results in the same ranking.", "Dot Product Distance. Defined as a negative of the dot product." ], "type": "string", "description": "Optional. The distance measure used in nearest neighbor search.", "enum": [ "DISTANCE_MEASURE_TYPE_UNSPECIFIED", "SQUARED_L2_DISTANCE", "COSINE_DISTANCE", "DOT_PRODUCT_DISTANCE" ] }, "filterColumns": { "description": "Optional. Columns of features that're used to filter vector search results.", "type": "array", "items": { "type": "string" } } }, "type": "object", "id": "GoogleCloudAiplatformV1FeatureViewIndexConfig" }, "GoogleCloudAiplatformV1ToolCallValidInput": { "type": "object", "description": "Input for tool call valid metric.", "id": "GoogleCloudAiplatformV1ToolCallValidInput", "properties": { "instances": { "description": "Required. Repeated tool call valid instances.", "items": { "$ref": "GoogleCloudAiplatformV1ToolCallValidInstance" }, "type": "array" }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1ToolCallValidSpec", "description": "Required. Spec for tool call valid metric." } } }, "GoogleCloudAiplatformV1SearchMigratableResourcesRequest": { "id": "GoogleCloudAiplatformV1SearchMigratableResourcesRequest", "description": "Request message for MigrationService.SearchMigratableResources.", "properties": { "pageToken": { "type": "string", "description": "The standard page token." }, "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": { "format": "int32", "type": "integer", "description": "The standard page size. The default and maximum value is 100." } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation": { "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.", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation", "properties": { "columnName": { "type": "string" } } }, "GoogleCloudAiplatformV1CreateFeatureViewOperationMetadata": { "id": "GoogleCloudAiplatformV1CreateFeatureViewOperationMetadata", "type": "object", "description": "Details of operations that perform create FeatureView.", "properties": { "genericMetadata": { "description": "Operation metadata for FeatureView Create.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1BleuResults": { "properties": { "bleuMetricValues": { "description": "Output only. Bleu metric values.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1BleuMetricValue" }, "readOnly": true } }, "description": "Results for bleu metric.", "type": "object", "id": "GoogleCloudAiplatformV1BleuResults" }, "CloudAiLargeModelsVisionGenerateVideoExperiments": { "type": "object", "description": "Experimental parameters for video generation.", "id": "CloudAiLargeModelsVisionGenerateVideoExperiments", "properties": { "videoTransformMaskGcsUri": { "description": "GCS URI of the grayscale video mask for Differential Diffusion. Maps to sdedit_video_tmax_scale_map ", "deprecated": true, "type": "string" }, "originalRequestJson": { "description": "The original REST API request JSON sent by the user, in the instances/parameters format. Preserved for saving alongside output artifacts so users can reproduce their requests. This field is populated by the API handler and is not user-settable.", "type": "string" }, "cfgScale": { "type": "number", "description": "CFG scale for video-transform, perf-generation, a2v, video-textures models.", "format": "float" }, "codec": { "enum": [ "VIDEO_CODEC_UNSPECIFIED", "VIDEO_CODEC_H264", "VIDEO_CODEC_PRORES", "VIDEO_CODEC_DNXHR" ], "description": "Optional. Video codec to use for output.", "type": "string", "enumDescriptions": [ "", "", "", "" ] }, "customParameters": { "type": "object", "description": "Generic key-value pairs for experimental parameters. This allows adding new parameters without changing the dataplane binary.", "additionalProperties": { "description": "Properties of the object.", "type": "any" } }, "proEdit": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsProEditConfig", "description": "Configuration for Pro Edit." }, "allowMeteredBilling": { "type": "boolean", "description": "If false, when a non-subscription customer tries to call an experimental feature, the request will be rejected. This field has no effect for subscription customers." }, "omniRewriter": { "description": "Optional. Omni Rewriter configuration.", "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsOmniRewriterConfig" }, "audioControl": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsAudioControlConfig", "description": "Optional. Audio control configuration." }, "numDiffusionSteps": { "description": "Number of diffusion steps", "type": "integer", "format": "int32" }, "promptInputs": { "description": "Prompt chunks for \"ProModel\" prompting. If set, the prompt will not be rewritten, and top-level prompt ignored.", "$ref": "CloudAiLargeModelsVisionPromptInputs" }, "requestOriginTag": { "type": "string", "description": "Optional tag for tracking the source of this request. Allowed values: \"colab\", \"comfyui\", \"curl\", \"flowresearch\", \"vertexstudio\". Unrecognized tags are recorded as \"unknown\" in metrics. Tags do not affect video generation behavior. Up to 16 characters, ASCII alphanumeric, hyphens, and underscores only." }, "anchorLastFrame": { "type": "boolean", "description": "Optional. If true, anchors the last frame in video generation by generating a custom border mask." }, "truncateInputVideo": { "description": "If true (default), truncate input videos that exceed the model's maximum frame count by applying a frame_selection_config to __video_file__ inputs. Set to false to preserve the existing fail-fast behavior.", "type": "boolean" }, "seamless": { "description": "Parameters for seamless (edge-continuous) video generation, enabling temporal looping and/or spatial tessellation.", "$ref": "CloudAiLargeModelsVisionSeamless" }, "superResConfig": { "description": "Config for the Pro Super Res upsampling task.", "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsSuperResConfig" }, "modelEndpointOverride": { "description": "Optional. BNS override for model backend. Enabled only for local and autopush environments by the flag `lvm_allow_model_zoo_bns_override`.", "type": "string" }, "spatialAlignment": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsSpatialAlignmentConfig", "description": "Optional. Spatial alignment configuration." }, "colorAlignment": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsColorAlignmentConfig", "description": "Optional. Color alignment configuration." }, "modelName": { "type": "string", "description": "Model names, as defined in: xyz " }, "schedulingConfig": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsVESchedulingConfig", "description": "Optional. Scheduling configuration." }, "outpaintConfig": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsOutpaintConfig", "description": "Config for Outpainting task." }, "loraConfig": { "description": "Optional. LoRA configuration for Omni editing/stylization models.", "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsLoraConfig" }, "videoTransform": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsVideoTransform", "description": "Video transform configuration for omni editing models." }, "humanPose": { "$ref": "CloudAiLargeModelsVisionHumanPose", "description": "Human pose parameters for Pose Control" }, "exrColorSpaceOverride": { "type": "string", "description": "Optional. Colorspace to be used for all EXR inputs." }, "videoTransformStrength": { "description": "SDEdit: Scalar noise level (0.0 to 1.0) Maps to sdedit_tmax ", "deprecated": true, "format": "float", "type": "number" }, "conditioningFrames": { "type": "array", "items": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsConditioningFrame" }, "description": "Conditioning frames for veo experimental models ONLY, not to be confused with keyframes (ID:31) in GenerateVideoRequest." } } }, "GoogleCloudAiplatformV1ImportEvaluationSetRequestAgentEngineSource": { "id": "GoogleCloudAiplatformV1ImportEvaluationSetRequestAgentEngineSource", "description": "Source for loading Agent Engine sessions.", "properties": { "reasoningEngineId": { "description": "Required. Reasoning Engine ID for the Agent Engine sessions.", "type": "string" }, "sessionIds": { "type": "array", "items": { "type": "string" }, "description": "Required. Session IDs for the Agent Engine sessions to retrieve." }, "projectId": { "type": "string", "description": "Required. Project ID for the Agent Engine sessions." }, "location": { "description": "Required. Location for the Agent Engine sessions.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1ImportDataOperationMetadata": { "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1ImportDataOperationMetadata", "description": "Runtime operation information for DatasetService.ImportData.", "type": "object" }, "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataBigQuerySource": { "type": "object", "properties": { "uri": { "type": "string", "description": "The URI of a BigQuery table. e.g. bq://projectId.bqDatasetId.bqTableId" } }, "id": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataBigQuerySource" }, "GoogleCloudAiplatformV1VideoResponseFormat": { "properties": { "delivery": { "type": "string", "description": "Optional. Delivery mode for the generated content.", "enum": [ "DELIVERY_UNSPECIFIED", "INLINE", "URI" ], "enumDescriptions": [ "Default value. This value is unused.", "Generated bytes are returned inline in the response.", "Generated content is stored and a URI is returned." ] }, "aspectRatio": { "enumDescriptions": [ "Default value. This value is unused.", "16:9 aspect ratio.", "9:16 aspect ratio." ], "description": "The aspect ratio for the video output.", "enum": [ "ASPECT_RATIO_UNSPECIFIED", "ASPECT_RATIO_SIXTEEN_BY_NINE", "ASPECT_RATIO_NINE_BY_SIXTEEN" ], "type": "string" }, "duration": { "description": "Optional. The duration for the video output.", "type": "string", "format": "google-duration" }, "gcsUri": { "description": "Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.", "type": "string" }, "resolution": { "description": "Optional. The video output resolution. Supported values: \"360p\", \"720p\", \"1080p\", \"4k\".", "type": "string" } }, "id": "GoogleCloudAiplatformV1VideoResponseFormat", "description": "Configuration for video-specific output formatting.", "type": "object" }, "GoogleCloudAiplatformV1MetricxInstance": { "properties": { "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "source": { "type": "string", "description": "Optional. Source text in original language." } }, "description": "Spec for MetricX instance - The fields used for evaluation are dependent on the MetricX version.", "type": "object", "id": "GoogleCloudAiplatformV1MetricxInstance" }, "GoogleCloudAiplatformV1PublisherModelCallToActionDeployVertex": { "id": "GoogleCloudAiplatformV1PublisherModelCallToActionDeployVertex", "properties": { "multiDeployVertex": { "items": { "$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionDeploy" }, "description": "Optional. One click deployment configurations.", "type": "array" } }, "type": "object", "description": "Multiple setups to deploy the PublisherModel." }, "CloudAiLargeModelsVisionExperimentsResponse": { "description": "Experimental response metadata for video generation.", "id": "CloudAiLargeModelsVisionExperimentsResponse", "type": "object", "properties": { "proEditResult": { "$ref": "CloudAiLargeModelsVisionExperimentsResponseProEditResult", "description": "Result metadata from a Pro Edit operation, populated for edit requests." } } }, "GenaiVertexV1DeepResearchAgentConfig": { "id": "GenaiVertexV1DeepResearchAgentConfig", "description": "Configuration for the Deep Research agent.", "type": "object", "properties": { "visualization": { "enum": [ "UNSPECIFIED", "OFF", "AUTO" ], "enumDescriptions": [ "The default visualization mode. Will default to AUTO.", "Do not include visualizations.", "Automatically include visualizations." ], "type": "string", "description": "Whether to include visualizations in the response." }, "collaborativePlanning": { "type": "boolean", "description": "Enables human-in-the-loop planning for the Deep Research agent. If set to true, the Deep Research agent will provide a research plan in its response. The agent will then proceed only if the user confirms the plan in the next turn." }, "thinkingSummaries": { "enum": [ "THINKING_SUMMARIES_UNSPECIFIED", "THINKING_SUMMARIES_AUTO", "THINKING_SUMMARIES_NONE" ], "enumDescriptions": [ "Default value. This value is unused.", "Auto thinking summaries.", "No thinking summaries." ], "description": "Whether to include thought summaries in the response.", "type": "string" }, "enableBigqueryTool": { "description": "Enables bigquery tool for the Deep Research agent.", "type": "boolean" } } }, "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExample": { "id": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExample", "type": "object", "description": "An example of how to generate memories for a particular scope.", "properties": { "conversationSource": { "$ref": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSource", "description": "A conversation source for the example." }, "generatedMemories": { "type": "array", "description": "Optional. Represents the memories that are expected to be generated from the input conversation. An empty list indicates that no memories are expected to be generated for the input conversation.", "items": { "$ref": "GoogleCloudAiplatformV1MemoryBankCustomizationConfigGenerateMemoriesExampleGeneratedMemory" } } } }, "GoogleCloudAiplatformV1SandboxEnvironmentConnectionInfo": { "type": "object", "properties": { "loadBalancerHostname": { "description": "Output only. The hostname of the load balancer.", "type": "string", "readOnly": true }, "sandboxInternalIp": { "type": "string", "description": "Output only. The internal IP address of the SandboxEnvironment.", "readOnly": true }, "serviceAttachment": { "description": "Output only. The name of the PSC-E service attachment created for private ingress to this SandboxEnvironment. Only populated when the template enables private ingress (see SandboxEnvironmentTemplate.ingress_control_config). VPC-SC customers use this to create a PSC endpoint in their VPC.", "readOnly": true, "type": "string" }, "loadBalancerIp": { "type": "string", "description": "Output only. The IP address of the load balancer.", "readOnly": true }, "routingToken": { "readOnly": true, "description": "Output only. The routing token for the SandboxEnvironment.", "type": "string" } }, "description": "The connection information of the SandboxEnvironment.", "id": "GoogleCloudAiplatformV1SandboxEnvironmentConnectionInfo" }, "GoogleCloudAiplatformV1TextResponseFormat": { "id": "GoogleCloudAiplatformV1TextResponseFormat", "description": "Configuration for text-specific output formatting.", "properties": { "mimeType": { "type": "string", "enum": [ "MIME_TYPE_UNSPECIFIED", "APPLICATION_JSON", "TEXT_PLAIN" ], "description": "Optional. The IANA standard MIME type of the response.", "enumDescriptions": [ "Default value. This value is unused.", "JSON output format.", "Plain text output format." ] }, "schema": { "type": "any", "description": "Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON." } }, "type": "object" }, "GoogleCloudAiplatformV1MigratableResourceMlEngineModelVersion": { "description": "Represents one model Version in ml.googleapis.com.", "type": "object", "id": "GoogleCloudAiplatformV1MigratableResourceMlEngineModelVersion", "properties": { "endpoint": { "type": "string", "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" }, "version": { "type": "string", "description": "Full resource name of ml engine model Version. Format: `projects/{project}/models/{model}/versions/{version}`." } } }, "GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetail": { "id": "GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetail", "type": "object", "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" }, "failedPreCachingCheckJobs": { "readOnly": true, "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.", "type": "array", "items": { "type": "string" } }, "preCachingCheckJob": { "type": "string", "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.", "readOnly": true }, "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." } } }, "GoogleCloudAiplatformV1EvaluationConfig": { "type": "object", "id": "GoogleCloudAiplatformV1EvaluationConfig", "properties": { "metrics": { "items": { "$ref": "GoogleCloudAiplatformV1Metric" }, "description": "Required. The metrics used for evaluation.", "type": "array" }, "inferenceGenerationConfig": { "$ref": "GoogleCloudAiplatformV1GenerationConfig", "description": "Optional. Configuration options for inference generation and outputs. If not set, default generation parameters are used." }, "autoraterConfig": { "$ref": "GoogleCloudAiplatformV1AutoraterConfig", "description": "Optional. Autorater config for evaluation." }, "datasetCustomMetrics": { "description": "Optional. Specifications for custom dataset-level aggregations.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1DatasetCustomMetric" } }, "outputConfig": { "description": "Required. Config for evaluation output.", "$ref": "GoogleCloudAiplatformV1OutputConfig" } }, "description": "Evaluation Config for Tuning Job." }, "GoogleCloudAiplatformV1InvokeRequest": { "properties": { "deployedModelId": { "type": "string", "description": "ID of the DeployedModel that serves the invoke request." }, "httpBody": { "description": "The invoke method input. Supports HTTP headers and arbitrary data payload.", "$ref": "GoogleApiHttpBody" } }, "type": "object", "description": "Request message for PredictionService.Invoke.", "id": "GoogleCloudAiplatformV1InvokeRequest" }, "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigTtlConfig": { "description": "Configuration for automatically setting the TTL (\"time-to-live\") of the memories in the Memory Bank.", "properties": { "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." }, "memoryRevisionDefaultTtl": { "format": "google-duration", "type": "string", "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." }, "granularTtlConfig": { "description": "Optional. The granular TTL configuration of the memories in the Memory Bank.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigTtlConfigGranularTtlConfig" } }, "id": "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigTtlConfig", "type": "object" }, "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInstance": { "id": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInstance", "description": "Spec for question answering correctness instance.", "type": "object", "properties": { "instruction": { "type": "string", "description": "Required. The question asked and other instruction in the inference prompt." }, "context": { "description": "Optional. Text provided as context to answer the question.", "type": "string" }, "prediction": { "type": "string", "description": "Required. Output of the evaluated model." }, "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" } } }, "GoogleCloudAiplatformV1FileData": { "id": "GoogleCloudAiplatformV1FileData", "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.", "type": "object", "properties": { "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" }, "displayName": { "type": "string", "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." } } }, "GoogleCloudAiplatformV1SupervisedTuningDatasetDistribution": { "id": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistribution", "properties": { "mean": { "description": "Output only. The arithmetic mean of the values in the population.", "type": "number", "readOnly": true, "format": "double" }, "p95": { "format": "double", "type": "number", "readOnly": true, "description": "Output only. The 95th percentile of the values in the population." }, "sum": { "format": "int64", "type": "string", "description": "Output only. Sum of a given population of values.", "readOnly": true }, "median": { "format": "double", "description": "Output only. The median of the values in the population.", "readOnly": true, "type": "number" }, "max": { "format": "double", "description": "Output only. The maximum of the population values.", "readOnly": true, "type": "number" }, "p5": { "format": "double", "type": "number", "readOnly": true, "description": "Output only. The 5th percentile of the values in the population." }, "buckets": { "readOnly": true, "type": "array", "description": "Output only. Defines the histogram bucket.", "items": { "$ref": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistributionDatasetBucket" } }, "billableSum": { "type": "string", "description": "Output only. Sum of a given population of values that are billable.", "format": "int64", "readOnly": true }, "min": { "format": "double", "readOnly": true, "description": "Output only. The minimum of the population values.", "type": "number" } }, "description": "Dataset distribution for Supervised Tuning.", "type": "object" }, "GoogleCloudAiplatformV1SuggestTrialsResponse": { "id": "GoogleCloudAiplatformV1SuggestTrialsResponse", "properties": { "trials": { "items": { "$ref": "GoogleCloudAiplatformV1Trial" }, "description": "A list of Trials.", "type": "array" }, "studyState": { "description": "The state of the Study.", "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." ], "type": "string", "enum": [ "STATE_UNSPECIFIED", "ACTIVE", "INACTIVE", "COMPLETED" ] }, "startTime": { "description": "The time at which the operation was started.", "type": "string", "format": "google-datetime" }, "endTime": { "format": "google-datetime", "description": "The time at which operation processing completed.", "type": "string" } }, "type": "object", "description": "Response message for VizierService.SuggestTrials." }, "GoogleTypeExpr": { "type": "object", "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.", "properties": { "title": { "type": "string", "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." }, "expression": { "description": "Textual representation of an expression in Common Expression Language syntax.", "type": "string" }, "description": { "type": "string", "description": "Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI." }, "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" } }, "id": "GoogleTypeExpr" }, "GenaiVertexV1DocumentContent": { "type": "object", "properties": { "data": { "type": "string", "description": "The document content.", "format": "byte" }, "uri": { "type": "string", "description": "The URI of the document." }, "mimeTypeString": { "description": "Flexible MIME type string of the document, superseding mime_type = 1. Note: Bespoke logic in the GAOS parser/serializer maps this to the \"mime_type\" JSON key.", "type": "string" } }, "description": "A document content block. ", "id": "GenaiVertexV1DocumentContent" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesMetadata": { "properties": { "evaluatedDataItemsBigqueryUri": { "description": "BigQuery destination uri for exported evaluated examples.", "type": "string" }, "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.", "type": "string", "format": "int64" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesMetadata", "description": "Model metadata specific to AutoML Tables." }, "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInstance": { "id": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInstance", "properties": { "context": { "type": "string", "description": "Optional. Text provided as context to answer the question." }, "prediction": { "type": "string", "description": "Required. Output of the evaluated model." }, "reference": { "type": "string", "description": "Optional. Ground truth used to compare against the prediction." }, "instruction": { "type": "string", "description": "Required. The question asked and other instruction in the inference prompt." } }, "description": "Spec for question answering helpfulness instance.", "type": "object" }, "GoogleCloudAiplatformV1ListOptimalTrialsResponse": { "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", "items": { "$ref": "GoogleCloudAiplatformV1Trial" }, "type": "array" } }, "id": "GoogleCloudAiplatformV1ListOptimalTrialsResponse", "type": "object" }, "GoogleCloudAiplatformV1ReasoningEngine": { "description": "ReasoningEngine provides a customizable runtime for models to determine which actions to take and in which order.", "type": "object", "properties": { "spec": { "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpec", "description": "Optional. Configurations of the ReasoningEngine" }, "displayName": { "type": "string", "description": "Required. The display name of the ReasoningEngine." }, "createTime": { "format": "google-datetime", "readOnly": true, "description": "Output only. Timestamp when this ReasoningEngine was created.", "type": "string" }, "labels": { "description": "Labels for the ReasoningEngine.", "type": "object", "additionalProperties": { "type": "string" } }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1EncryptionSpec", "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": { "description": "Optional. The description of the ReasoningEngine.", "type": "string" }, "name": { "description": "Identifier. The resource name of the ReasoningEngine. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string" }, "etag": { "type": "string", "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." }, "contextSpec": { "$ref": "GoogleCloudAiplatformV1ReasoningEngineContextSpec", "description": "Optional. Configuration for how Agent Engine sub-resources should manage context." }, "updateTime": { "type": "string", "format": "google-datetime", "readOnly": true, "description": "Output only. Timestamp when this ReasoningEngine was most recently updated." } }, "id": "GoogleCloudAiplatformV1ReasoningEngine" }, "GoogleCloudAiplatformV1GenerateInstanceRubricsRequest": { "id": "GoogleCloudAiplatformV1GenerateInstanceRubricsRequest", "description": "Request message for EvaluationService.GenerateInstanceRubrics.", "properties": { "location": { "type": "string", "description": "Required. The resource name of the Location to generate rubrics from. Format: `projects/{project}/locations/{location}`" }, "contents": { "items": { "$ref": "GoogleCloudAiplatformV1Content" }, "type": "array", "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." }, "rubricGenerationSpec": { "description": "Optional. Specification for how the rubrics should be generated.", "$ref": "GoogleCloudAiplatformV1RubricGenerationSpec" }, "metricResourceName": { "description": "Optional. The resource name of a registered metric. Rubric generation using predefined metric spec or LLMBasedMetricSpec is supported. If this field is set, the configuration provided in this field is used for rubric generation. The `predefined_rubric_generation_spec` and `rubric_generation_spec` fields will be ignored.", "type": "string" }, "agentConfig": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentConfig", "description": "Optional. Agent configuration, required for agent-based rubric generation." }, "predefinedRubricGenerationSpec": { "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.", "$ref": "GoogleCloudAiplatformV1PredefinedMetricSpec" } }, "type": "object" }, "GoogleCloudAiplatformV1CreateIndexOperationMetadata": { "description": "Runtime operation information for IndexService.CreateIndex.", "id": "GoogleCloudAiplatformV1CreateIndexOperationMetadata", "type": "object", "properties": { "nearestNeighborSearchOperationMetadata": { "description": "The operation metadata with regard to Matching Engine Index operation.", "$ref": "GoogleCloudAiplatformV1NearestNeighborSearchOperationMetadata" }, "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1TuningJob": { "type": "object", "properties": { "experiment": { "description": "Output only. The Experiment associated with this TuningJob.", "readOnly": true, "type": "string" }, "description": { "type": "string", "description": "Optional. The description of the TuningJob." }, "createTime": { "description": "Output only. Time when the TuningJob was created.", "readOnly": true, "type": "string", "format": "google-datetime" }, "labels": { "additionalProperties": { "type": "string" }, "description": "Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.", "type": "object" }, "gcsMetricsUri": { "readOnly": true, "description": "Output only. The Cloud Storage metrics URI associated with this TuningJob.", "type": "string" }, "name": { "description": "Output only. Identifier. Resource name of a TuningJob. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`", "type": "string", "readOnly": true }, "tunedModel": { "description": "Output only. The tuned model resources associated with this TuningJob.", "$ref": "GoogleCloudAiplatformV1TunedModel", "readOnly": true }, "error": { "description": "Output only. Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1EncryptionSpec", "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." }, "preferenceOptimizationSpec": { "description": "Tuning Spec for Preference Optimization.", "$ref": "GoogleCloudAiplatformV1PreferenceOptimizationSpec" }, "evaluateDatasetRuns": { "description": "Output only. Evaluation runs for the Tuning Job.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1EvaluateDatasetRun" } }, "preTunedModel": { "$ref": "GoogleCloudAiplatformV1PreTunedModel", "description": "The pre-tuned model for continuous tuning." }, "supervisedTuningSpec": { "$ref": "GoogleCloudAiplatformV1SupervisedTuningSpec", "description": "Tuning Spec for Supervised Fine Tuning." }, "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" }, "tunedModelDisplayName": { "type": "string", "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." }, "state": { "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.", "type": "string", "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" ] }, "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" }, "tuningDataStats": { "description": "Output only. The tuning data statistics associated with this TuningJob.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1TuningDataStats" }, "startTime": { "description": "Output only. Time when the TuningJob for the first time entered the `JOB_STATE_RUNNING` state.", "type": "string", "readOnly": true, "format": "google-datetime" }, "updateTime": { "description": "Output only. Time when the TuningJob was most recently updated.", "type": "string", "readOnly": true, "format": "google-datetime" }, "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" } }, "description": "Represents a TuningJob that runs with Google owned models.", "id": "GoogleCloudAiplatformV1TuningJob" }, "GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTable": { "description": "ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table.", "id": "GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTable", "properties": { "logSource": { "enum": [ "LOG_SOURCE_UNSPECIFIED", "TRAINING", "SERVING" ], "description": "The source of log.", "type": "string", "enumDescriptions": [ "Unspecified source.", "Logs coming from Training dataset.", "Logs coming from Serving traffic." ] }, "bigqueryTablePath": { "description": "The created BigQuery table to store logs. Customer could do their own query & analysis. Format: `bq://.model_deployment_monitoring_._`", "type": "string" }, "logType": { "enumDescriptions": [ "Unspecified type.", "Predict logs.", "Explain logs." ], "enum": [ "LOG_TYPE_UNSPECIFIED", "PREDICT", "EXPLAIN" ], "type": "string", "description": "The type of log." }, "requestResponseLoggingSchemaVersion": { "type": "string", "description": "Output only. The schema version of the request/response logging BigQuery table. Default to v1 if unset.", "readOnly": true } }, "type": "object" }, "GoogleCloudAiplatformV1NfsMount": { "type": "object", "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" } }, "id": "GoogleCloudAiplatformV1NfsMount", "description": "Represents a mount configuration for Network File System (NFS) to mount." }, "GoogleCloudAiplatformV1NotebookExecutionJobCustomEnvironmentSpec": { "type": "object", "description": "Compute configuration to use for an execution job.", "id": "GoogleCloudAiplatformV1NotebookExecutionJobCustomEnvironmentSpec", "properties": { "persistentDiskSpec": { "description": "The specification of a persistent disk to attach for the execution job.", "$ref": "GoogleCloudAiplatformV1PersistentDiskSpec" }, "networkSpec": { "description": "The network configuration to use for the execution job.", "$ref": "GoogleCloudAiplatformV1NetworkSpec" }, "machineSpec": { "$ref": "GoogleCloudAiplatformV1MachineSpec", "description": "The specification of a single machine for the execution job." }, "shieldedInstanceConfig": { "$ref": "GoogleCloudAiplatformV1NotebookExecutionJobCustomEnvironmentSpecShieldedInstanceConfig", "description": "Optional. Shielded VM configuration (for example, Secure Boot) for the execution VM." } } }, "GoogleCloudAiplatformV1FeatureViewDirectWriteRequestDataKeyAndFeatureValues": { "description": "A data key and associated feature values to write to the feature view.", "type": "object", "id": "GoogleCloudAiplatformV1FeatureViewDirectWriteRequestDataKeyAndFeatureValues", "properties": { "features": { "description": "List of features to write.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeature" } }, "dataKey": { "description": "The data key.", "$ref": "GoogleCloudAiplatformV1FeatureViewDataKey" } } }, "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfig": { "properties": { "dataset": { "type": "string", "description": "Required. Full resource name of data labeling Dataset. Format: `projects/{project}/datasets/{dataset}`." }, "datasetDisplayName": { "description": "Optional. Display name of the Dataset in Vertex AI. System will pick a display name if unspecified.", "type": "string" }, "migrateDataLabelingAnnotatedDatasetConfigs": { "type": "array", "description": "Optional. Configs for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery. The specified AnnotatedDatasets have to belong to the datalabeling Dataset.", "items": { "$ref": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig" } } }, "description": "Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset.", "id": "GoogleCloudAiplatformV1MigrateResourceRequestMigrateDataLabelingDatasetConfig", "type": "object" }, "GoogleCloudAiplatformV1IndexStats": { "type": "object", "description": "Stats of the Index.", "id": "GoogleCloudAiplatformV1IndexStats", "properties": { "sparseVectorsCount": { "description": "Output only. The number of sparse vectors in the Index.", "type": "string", "readOnly": true, "format": "int64" }, "vectorsCount": { "type": "string", "description": "Output only. The number of dense vectors in the Index.", "readOnly": true, "format": "int64" }, "shardsCount": { "format": "int32", "type": "integer", "description": "Output only. The number of shards in the Index.", "readOnly": true } } }, "GenaiVertexV1RagStoreConfigRagRetrievalConfigHybridSearch": { "properties": { "alpha": { "description": "Optional. Alpha value controls the weight between dense and sparse vector search results.", "format": "float", "type": "number" } }, "description": "Config for Hybrid Search.", "type": "object", "id": "GenaiVertexV1RagStoreConfigRagRetrievalConfigHybridSearch" }, "GoogleCloudAiplatformV1RagManagedDbConfigUnprovisioned": { "properties": {}, "id": "GoogleCloudAiplatformV1RagManagedDbConfigUnprovisioned", "type": "object", "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." }, "GoogleCloudAiplatformV1ExecuteCodeRequest": { "id": "GoogleCloudAiplatformV1ExecuteCodeRequest", "type": "object", "properties": { "inputs": { "items": { "$ref": "GoogleCloudAiplatformV1Chunk" }, "type": "array", "description": "Required. The inputs used for the stateless code execution." } }, "description": "Request message for SandboxEnvironmentExecutionService.ExecuteCode." }, "GoogleCloudAiplatformV1SchemaPromptInstanceVariableValue": { "id": "GoogleCloudAiplatformV1SchemaPromptInstanceVariableValue", "type": "object", "description": "The value of a variable in prompt.", "properties": { "partList": { "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecPartList", "description": "The parts of the variable value." } } }, "GoogleCloudAiplatformV1ReasoningEngineSpecContainerSpec": { "id": "GoogleCloudAiplatformV1ReasoningEngineSpecContainerSpec", "type": "object", "properties": { "port": { "format": "int32", "type": "integer", "description": "Optional. The port the container listens on. Defaults to 8080 if unset." }, "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" } }, "description": "Specification for deploying from a container image." }, "GoogleCloudAiplatformV1QuestionAnsweringRelevanceResult": { "description": "Spec for question answering relevance result.", "properties": { "explanation": { "type": "string", "description": "Output only. Explanation for question answering relevance score.", "readOnly": true }, "confidence": { "readOnly": true, "description": "Output only. Confidence for question answering relevance score.", "format": "float", "type": "number" }, "score": { "description": "Output only. Question Answering Relevance score.", "readOnly": true, "format": "float", "type": "number" } }, "id": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceResult", "type": "object" }, "GoogleCloudAiplatformV1ImportEvaluationSetRequestGcsSource": { "id": "GoogleCloudAiplatformV1ImportEvaluationSetRequestGcsSource", "properties": { "importSchemaConfig": { "description": "Required. Schema configuration for the input data.", "$ref": "GoogleCloudAiplatformV1ImportEvaluationSetRequestImportSchemaConfig" }, "gcsUri": { "description": "Required. The Cloud Storage location of the input data.", "type": "string" } }, "description": "Source for loading data from Cloud Storage.", "type": "object" }, "GoogleCloudAiplatformV1BatchCreateFeaturesRequest": { "description": "Request message for FeaturestoreService.BatchCreateFeatures. Request message for FeatureRegistryService.BatchCreateFeatures.", "properties": { "requests": { "description": "Required. The request message specifying the Features to create. All Features must be created under the same parent EntityType / FeatureGroup. The `parent` field in each child request message can be omitted. If `parent` is set in a child request, then the value must match the `parent` value in this request message.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1CreateFeatureRequest" } } }, "type": "object", "id": "GoogleCloudAiplatformV1BatchCreateFeaturesRequest" }, "GoogleCloudAiplatformV1ListIndexEndpointsResponse": { "type": "object", "description": "Response message for IndexEndpointService.ListIndexEndpoints.", "properties": { "indexEndpoints": { "description": "List of IndexEndpoints in the requested page.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1IndexEndpoint" } }, "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListIndexEndpointsRequest.page_token to obtain that page.", "type": "string" } }, "id": "GoogleCloudAiplatformV1ListIndexEndpointsResponse" }, "GoogleCloudAiplatformV1SandboxEnvironmentTemplateDefaultContainerEnvironment": { "id": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateDefaultContainerEnvironment", "type": "object", "properties": { "resources": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateResourceRequirements", "description": "Optional. Resource requests and limits for the default container." }, "defaultContainerCategory": { "enum": [ "DEFAULT_CONTAINER_CATEGORY_UNSPECIFIED", "DEFAULT_CONTAINER_CATEGORY_COMPUTER_USE", "DEFAULT_CONTAINER_CATEGORY_SHELL_SANDBOX" ], "enumDescriptions": [ "The default value. This value is unused.", "The default container image for Computer Use.", "The default container image for Shell Sandbox." ], "description": "Required. The category of the default container image.", "type": "string" } }, "description": "The default sandbox runtime environment for default container workloads." }, "GoogleCloudAiplatformV1EvaluationResults": { "type": "object", "description": "The results of the evaluation run.", "properties": { "evaluationSet": { "type": "string", "description": "The evaluation set where item level results are stored." }, "summaryMetrics": { "description": "Optional. The summary metrics for the evaluation run.", "$ref": "GoogleCloudAiplatformV1SummaryMetrics" } }, "id": "GoogleCloudAiplatformV1EvaluationResults" }, "GoogleCloudAiplatformV1UpdateTensorboardOperationMetadata": { "description": "Details of operations that perform update Tensorboard.", "properties": { "genericMetadata": { "description": "Operation metadata for Tensorboard.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1UpdateTensorboardOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoActionRecognition": { "description": "A TrainingJob that trains and uploads an AutoML Video Action Recognition Model.", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoActionRecognition", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs" } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentation": { "description": "A TrainingJob that trains and uploads an AutoML Image Segmentation Model.", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs" }, "metadata": { "description": "The metadata information.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentation", "type": "object" }, "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateRequest": { "properties": {}, "type": "object", "id": "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateRequest", "description": "Request message for VizierService.CheckTrialEarlyStoppingState." }, "GoogleCloudAiplatformV1ToolGoogleSearchImageSearch": { "type": "object", "id": "GoogleCloudAiplatformV1ToolGoogleSearchImageSearch", "description": "Image search for grounding and related configurations.", "properties": {} }, "GoogleLongrunningListOperationsResponse": { "description": "The response message for Operations.ListOperations.", "type": "object", "properties": { "operations": { "description": "A list of operations that matches the specified filter in the request.", "items": { "$ref": "GoogleLongrunningOperation" }, "type": "array" }, "unreachable": { "items": { "type": "string" }, "type": "array", "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." }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "id": "GoogleLongrunningListOperationsResponse" }, "GoogleCloudAiplatformV1DoubleArray": { "description": "A list of double values.", "properties": { "values": { "type": "array", "description": "A list of double values.", "items": { "format": "double", "type": "number" } } }, "id": "GoogleCloudAiplatformV1DoubleArray", "type": "object" }, "GoogleCloudAiplatformV1ListAnnotationsResponse": { "properties": { "nextPageToken": { "description": "The standard List next-page token.", "type": "string" }, "annotations": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Annotation" }, "description": "A list of Annotations that matches the specified filter in the request." } }, "id": "GoogleCloudAiplatformV1ListAnnotationsResponse", "type": "object", "description": "Response message for DatasetService.ListAnnotations." }, "GoogleCloudAiplatformV1PersistentResource": { "description": "Represents long-lasting resources that are dedicated to users to runs custom workloads. A PersistentResource can have multiple node pools and each node pool can have its own machine spec.", "properties": { "error": { "description": "Output only. Only populated when persistent resource's state is `STOPPING` or `ERROR`.", "readOnly": true, "$ref": "GoogleRpcStatus" }, "resourcePools": { "description": "Required. The spec of the pools of different resources.", "items": { "$ref": "GoogleCloudAiplatformV1ResourcePool" }, "type": "array" }, "resourceRuntime": { "$ref": "GoogleCloudAiplatformV1ResourceRuntime", "description": "Output only. Runtime information of the Persistent Resource.", "readOnly": true }, "labels": { "type": "object", "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.", "additionalProperties": { "type": "string" } }, "displayName": { "type": "string", "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." }, "reservedIpRanges": { "type": "array", "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'].", "items": { "type": "string" } }, "createTime": { "format": "google-datetime", "type": "string", "readOnly": true, "description": "Output only. Time when the PersistentResource was created." }, "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" }, "startTime": { "description": "Output only. Time when the PersistentResource for the first time entered the `RUNNING` state.", "type": "string", "readOnly": true, "format": "google-datetime" }, "state": { "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." ], "readOnly": true, "description": "Output only. The detailed state of a Study.", "enum": [ "STATE_UNSPECIFIED", "PROVISIONING", "RUNNING", "STOPPING", "ERROR", "REBOOTING", "UPDATING" ], "type": "string" }, "pscInterfaceConfig": { "description": "Optional. Configuration for PSC-I for PersistentResource.", "$ref": "GoogleCloudAiplatformV1PscInterfaceConfig" }, "satisfiesPzs": { "readOnly": true, "description": "Output only. Reserved for future use.", "type": "boolean" }, "updateTime": { "description": "Output only. Time when the PersistentResource was most recently updated.", "readOnly": true, "format": "google-datetime", "type": "string" }, "encryptionSpec": { "description": "Optional. Customer-managed encryption key spec for a PersistentResource. If set, this PersistentResource and all sub-resources of this PersistentResource will be secured by this key.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "readOnly": true, "type": "boolean" }, "resourceRuntimeSpec": { "description": "Optional. Persistent Resource runtime spec. For example, used for Ray cluster configuration.", "$ref": "GoogleCloudAiplatformV1ResourceRuntimeSpec" }, "name": { "description": "Immutable. Resource name of a PersistentResource.", "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1PersistentResource" }, "GoogleCloudAiplatformV1GenieSource": { "type": "object", "properties": { "baseModelUri": { "description": "Required. The public base model URI.", "type": "string" } }, "description": "Contains information about the source of the models generated from Generative AI Studio.", "id": "GoogleCloudAiplatformV1GenieSource" }, "GoogleCloudAiplatformV1ActivateOnlineEvaluatorRequest": { "properties": {}, "id": "GoogleCloudAiplatformV1ActivateOnlineEvaluatorRequest", "description": "Request message for ActivateOnlineEvaluator.", "type": "object" }, "GoogleCloudAiplatformV1SampleConfig": { "id": "GoogleCloudAiplatformV1SampleConfig", "type": "object", "description": "Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.", "properties": { "initialBatchSamplePercentage": { "format": "int32", "description": "The percentage of data needed to be labeled in the first batch.", "type": "integer" }, "sampleStrategy": { "type": "string", "description": "Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.", "enumDescriptions": [ "Default will be treated as UNCERTAINTY.", "Sample the most uncertain data to label." ], "enum": [ "SAMPLE_STRATEGY_UNSPECIFIED", "UNCERTAINTY" ] }, "followingBatchSamplePercentage": { "description": "The percentage of data needed to be labeled in each following batch (except the first batch).", "type": "integer", "format": "int32" } } }, "GoogleCloudAiplatformV1FeatureOnlineStoreOptimized": { "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1FeatureOnlineStoreOptimized", "description": "Optimized storage type" }, "GoogleCloudAiplatformV1PurgeExecutionsMetadata": { "description": "Details of operations that perform MetadataService.PurgeExecutions.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Operation metadata for purging Executions." } }, "id": "GoogleCloudAiplatformV1PurgeExecutionsMetadata", "type": "object" }, "GenaiVertexV1CodeMenderAgentConfigFindRequest": { "properties": { "findingId": { "type": "string", "description": "The identifier of a specific finding to verify. This is primarily used in VERIFY mode to focus the agent's execution-based validation on a single vulnerability." }, "description": { "description": "Additional context or custom instructions provided by the user to guide the vulnerability analysis.", "type": "string" }, "mode": { "enumDescriptions": [ "Default value. This value is unused.", "Fast scan using only the initial classifier.", "Performs classification followed by detailed investigation." ], "description": "The mode of the find session.", "type": "string", "enum": [ "MODE_UNSPECIFIED", "MODE_SCAN", "MODE_VERIFY" ] }, "sourceFiles": { "description": "A list of source files to provide as context for the scan.", "type": "array", "items": { "$ref": "GenaiVertexV1CodeMenderAgentConfigFileContent" } } }, "id": "GenaiVertexV1CodeMenderAgentConfigFindRequest", "description": "Request parameters specific to FIND sessions, used for discovering vulnerabilities in a codebase.", "type": "object" }, "GoogleCloudAiplatformV1SandboxEnvironmentTemplateEgressControlConfig": { "properties": { "internetAccess": { "description": "Optional. Whether to allow internet access.", "type": "boolean" }, "networkAttachment": { "type": "string", "description": "Optional. The name of the customer VPC `NetworkAttachment` used to draw a PSC interface IP into the customer VPC for sandbox egress." }, "dnsPeeringConfigs": { "items": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateEgressControlConfigDnsPeeringConfig" }, "description": "Optional. DNS peering configurations that allow sandbox egress to resolve customer-internal domains via the customer VPC.", "type": "array" } }, "id": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateEgressControlConfig", "description": "Configuration for egress control of sandbox instances.", "type": "object" }, "GoogleCloudAiplatformV1BatchCreateFeaturesResponse": { "type": "object", "description": "Response message for FeaturestoreService.BatchCreateFeatures.", "id": "GoogleCloudAiplatformV1BatchCreateFeaturesResponse", "properties": { "features": { "type": "array", "description": "The Features created.", "items": { "$ref": "GoogleCloudAiplatformV1Feature" } } } }, "GoogleCloudAiplatformV1PipelineJobRuntimeConfig": { "description": "The runtime config of a PipelineJob.", "properties": { "failurePolicy": { "enum": [ "PIPELINE_FAILURE_POLICY_UNSPECIFIED", "PIPELINE_FAILURE_POLICY_FAIL_SLOW", "PIPELINE_FAILURE_POLICY_FAIL_FAST" ], "enumDescriptions": [ "Default value, and follows fail slow behavior.", "Indicates that the pipeline should continue to run until all possible tasks have been scheduled and completed.", "Indicates that the pipeline should stop scheduling new tasks after a task has failed." ], "type": "string", "description": "Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion." }, "parameterValues": { "type": "object", "additionalProperties": { "type": "any" }, "description": "The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL." }, "parameters": { "deprecated": true, "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1Value" }, "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." }, "inputArtifacts": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1PipelineJobRuntimeConfigInputArtifact" }, "description": "The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact." }, "gcsOutputDirectory": { "type": "string", "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." } }, "id": "GoogleCloudAiplatformV1PipelineJobRuntimeConfig", "type": "object" }, "GoogleCloudAiplatformV1AgentTool": { "description": "A tool provides a list of actions available to the Agent during the process of executing a task. Example JSON for an MCP server tool: { \"type\": \"mcp_server\", \"name\": \"my-mcp-server\", \"url\": \"https://api.example.com/mcp\", \"headers\": { \"Authorization\": \"Bearer token123\" } }", "id": "GoogleCloudAiplatformV1AgentTool", "type": "object", "properties": { "headers": { "additionalProperties": { "type": "string" }, "type": "object", "description": "Optional. The headers for the MCP server, such as for authentication. Only applicable when `type` is `mcp_server`." }, "type": { "type": "string", "description": "Required. The type of the tool. Supported types: * `code_execution` * `endpoint` * `filesystem` * `google_search` * `mcp_server` * `url_context`" }, "name": { "type": "string", "description": "Optional. The tool's Google Cloud resource name, used to resolve the tool. Applicable when `type` is `mcp_server` or `endpoint` (a tool registered in Agent Registry), for example `projects/{project}/locations/{location}/.../mcpServers/{id}` or `projects/{project}/locations/{location}/.../endpoints/{id}`." }, "url": { "description": "Optional. Fallback for the tool's runtime reference, consumed by `CreateAgent` to create the downstream AI App. Applicable when `type` is `mcp_server` or `endpoint`, and optional: the Agent service derives the runtime reference from `name` via Agent Registry (`GetMcpServer` / `GetEndpoint`), and reads this only when that lookup yields none.", "type": "string" } } }, "GenaiVertexV1CodeMenderAgentConfig": { "properties": { "sessionConfig": { "description": "Optional session-specific configurations to override default agent behavior.", "$ref": "GenaiVertexV1CodeMenderAgentConfigSessionConfig" }, "findRequest": { "description": "Parameters for finding vulnerabilities.", "$ref": "GenaiVertexV1CodeMenderAgentConfigFindRequest" }, "model": { "type": "string", "description": "The name of the model to use for the CodeMender agent. One CodeMender session will only use one model." }, "sessionId": { "description": "Parameter for grouping multiple interactions that belong to the same CodeMender session.", "type": "string" }, "fixRequest": { "description": "Parameters for fixing vulnerabilities.", "$ref": "GenaiVertexV1CodeMenderAgentConfigFixRequest" } }, "description": "Configuration for the CodeMender agent.", "id": "GenaiVertexV1CodeMenderAgentConfig", "type": "object" }, "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectContentsSource": { "id": "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectContentsSource", "properties": { "events": { "items": { "$ref": "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectContentsSourceEvent" }, "description": "Required. The source content (i.e. chat history) to generate memories from.", "type": "array" } }, "type": "object", "description": "Defines a direct source of content from which to generate the memories." }, "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigGenerationConfig": { "properties": { "generationTriggerConfig": { "$ref": "GoogleCloudAiplatformV1MemoryGenerationTriggerConfig", "description": "Optional. Specifies the default trigger configuration for generating memories using `IngestEvents`." }, "model": { "description": "Optional. The model used to generate memories. Format: `projects/{project}/locations/{location}/publishers/google/models/{model}`.", "type": "string" } }, "description": "Configuration for how to generate memories.", "id": "GoogleCloudAiplatformV1ReasoningEngineContextSpecMemoryBankConfigGenerationConfig", "type": "object" }, "GenaiVertexV1RagStoreConfigRagResource": { "id": "GenaiVertexV1RagStoreConfigRagResource", "type": "object", "description": "The definition of the Rag resource.", "properties": { "ragFileIds": { "description": "Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.", "items": { "type": "string" }, "type": "array" }, "ragCorpus": { "description": "Optional. RagCorpora resource name.", "type": "string" } } }, "GoogleCloudAiplatformV1RagFileParsingConfigLayoutParser": { "id": "GoogleCloudAiplatformV1RagFileParsingConfigLayoutParser", "properties": { "maxParsingRequestsPerMin": { "type": "integer", "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.", "format": "int32" }, "processorName": { "type": "string", "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}`" } }, "description": "Document AI Layout Parser config.", "type": "object" }, "GoogleCloudAiplatformV1LustreMount": { "type": "object", "properties": { "mountPoint": { "type": "string", "description": "Required. Destination mount path. The Lustre file system will be mounted for the user under /mnt/lustre/" }, "filesystem": { "type": "string", "description": "Required. The name of the Lustre filesystem." }, "instanceIp": { "description": "Required. IP address of the Lustre instance.", "type": "string" }, "volumeHandle": { "type": "string", "description": "Required. The unique identifier of the Lustre volume." } }, "description": "Represents a mount configuration for Lustre file system.", "id": "GoogleCloudAiplatformV1LustreMount" }, "GoogleCloudAiplatformV1CreateTensorboardTimeSeriesRequest": { "id": "GoogleCloudAiplatformV1CreateTensorboardTimeSeriesRequest", "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": { "description": "Required. The TensorboardTimeSeries to create.", "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" } }, "description": "Request message for TensorboardService.CreateTensorboardTimeSeries.", "type": "object" }, "GoogleCloudAiplatformV1FunctionResponse": { "properties": { "parts": { "type": "array", "description": "Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.", "items": { "$ref": "GoogleCloudAiplatformV1FunctionResponsePart" } }, "scheduling": { "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.", "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." ], "type": "string", "enum": [ "SCHEDULING_UNSPECIFIED", "SILENT", "WHEN_IDLE", "INTERRUPT" ] }, "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" }, "response": { "type": "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.", "additionalProperties": { "description": "Properties of the object.", "type": "any" } }, "name": { "type": "string", "description": "Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name." } }, "id": "GoogleCloudAiplatformV1FunctionResponse", "type": "object", "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." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation": { "properties": { "columnName": { "type": "string" } }, "description": "Training pipeline will infer the proper transformation based on the statistic of dataset.", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation", "type": "object" }, "GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpec": { "properties": { "updateAllStoppedTrials": { "type": "boolean", "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." }, "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" }, "minMeasurementCount": { "type": "string", "format": "int64", "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." }, "useElapsedDuration": { "type": "boolean", "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." }, "minStepCount": { "format": "int64", "type": "string", "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." }, "maxStepCount": { "type": "string", "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." } }, "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.", "id": "GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpec", "type": "object" }, "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesResponse": { "type": "object", "id": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesResponse", "description": "Response message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.", "properties": { "monitoringStats": { "type": "array", "description": "Stats retrieved for requested objectives. There are at most 1000 ModelMonitoringStatsAnomalies.FeatureHistoricStatsAnomalies.prediction_stats in the response.", "items": { "$ref": "GoogleCloudAiplatformV1ModelMonitoringStatsAnomalies" } }, "nextPageToken": { "type": "string", "description": "The page token that can be used by the next JobService.SearchModelDeploymentMonitoringStatsAnomalies call." } } }, "GoogleCloudAiplatformV1FeatureViewBigtableMetadata": { "id": "GoogleCloudAiplatformV1FeatureViewBigtableMetadata", "type": "object", "properties": { "readAppProfile": { "description": "Output only. The Bigtable App Profile to use for reading from Bigtable.", "type": "string", "readOnly": true } }, "description": "Metadata for the Cloud Bigtable that supports directly interacting Bigtable instances." }, "GoogleCloudAiplatformV1ListModelVersionsResponse": { "properties": { "models": { "items": { "$ref": "GoogleCloudAiplatformV1Model" }, "description": "List of Model versions in the requested page. In the returned Model name field, version ID instead of regvision tag will be included.", "type": "array" }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListModelVersionsRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for ModelService.ListModelVersions", "type": "object", "id": "GoogleCloudAiplatformV1ListModelVersionsResponse" }, "GenaiVertexV1RagStoreConfig": { "type": "object", "id": "GenaiVertexV1RagStoreConfig", "properties": { "ragResources": { "type": "array", "description": "Optional. The representation of the rag source.", "items": { "$ref": "GenaiVertexV1RagStoreConfigRagResource" } }, "ragRetrievalConfig": { "description": "Optional. The retrieval config for the Rag query.", "$ref": "GenaiVertexV1RagStoreConfigRagRetrievalConfig" } }, "description": "Use to specify configuration for RAG Store." }, "GenaiVertexV1CodeExecutionResultStep": { "properties": { "isError": { "type": "boolean", "description": "Whether the code execution resulted in an error." }, "result": { "description": "Required. The output of the code execution.", "type": "string" } }, "description": "Code execution result step.", "id": "GenaiVertexV1CodeExecutionResultStep", "type": "object" }, "GoogleCloudAiplatformV1ReadFeatureValuesResponseHeader": { "type": "object", "id": "GoogleCloudAiplatformV1ReadFeatureValuesResponseHeader", "properties": { "featureDescriptors": { "description": "List of Feature metadata corresponding to each piece of ReadFeatureValuesResponse.EntityView.data.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponseFeatureDescriptor" } }, "entityType": { "description": "The resource name of the EntityType from the ReadFeatureValuesRequest. Value format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`.", "type": "string" } }, "description": "Response header with metadata for the requested ReadFeatureValuesRequest.entity_type and Features." }, "GoogleCloudAiplatformV1SchemaVertex": { "properties": { "y": { "type": "number", "format": "double", "description": "Y coordinate of the vertex, normalized to [0.0, 1.0]." }, "x": { "format": "double", "description": "X coordinate of the vertex, normalized to [0.0, 1.0].", "type": "number" } }, "type": "object", "description": "Represents a 2D point in the image. Vertex coordinates are normalized to be relative to the original image dimensions and range from 0 to 1. The origin of the coordinate system (0,0) is the top-left corner of the image. x increases to the right, and y increases to the bottom.", "id": "GoogleCloudAiplatformV1SchemaVertex" }, "GenaiVertexV1GoogleSearchCallDelta": { "type": "object", "id": "GenaiVertexV1GoogleSearchCallDelta", "properties": { "arguments": { "$ref": "GenaiVertexV1GoogleSearchCallContentGoogleSearchCallArguments" } } }, "GoogleCloudAiplatformV1SchemaPredictPredictionTftFeatureImportance": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaPredictPredictionTftFeatureImportance", "properties": { "contextColumns": { "type": "array", "items": { "type": "string" } }, "horizonWeights": { "type": "array", "items": { "type": "number", "format": "float" } }, "attributeColumns": { "items": { "type": "string" }, "type": "array" }, "horizonColumns": { "type": "array", "items": { "type": "string" } }, "contextWeights": { "description": "TFT feature importance values. Each pair for {context/horizon/attribute} should have the same shape since the weight corresponds to the column names.", "type": "array", "items": { "format": "float", "type": "number" } }, "attributeWeights": { "items": { "type": "number", "format": "float" }, "type": "array" } } }, "GoogleCloudAiplatformV1ReplicatedVoiceConfig": { "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", "description": "Optional. The sample of the custom voice.", "format": "byte" } }, "id": "GoogleCloudAiplatformV1ReplicatedVoiceConfig", "description": "The configuration for the replicated voice to use.", "type": "object" }, "GoogleCloudAiplatformV1CancelHyperparameterTuningJobRequest": { "properties": {}, "id": "GoogleCloudAiplatformV1CancelHyperparameterTuningJobRequest", "description": "Request message for JobService.CancelHyperparameterTuningJob.", "type": "object" }, "GoogleCloudAiplatformV1UpdateExplanationDatasetRequest": { "description": "Request message for ModelService.UpdateExplanationDataset.", "id": "GoogleCloudAiplatformV1UpdateExplanationDatasetRequest", "type": "object", "properties": { "examples": { "$ref": "GoogleCloudAiplatformV1Examples", "description": "The example config containing the location of the dataset." } } }, "GoogleCloudAiplatformV1ListSandboxEnvironmentTemplatesResponse": { "id": "GoogleCloudAiplatformV1ListSandboxEnvironmentTemplatesResponse", "properties": { "nextPageToken": { "type": "string", "description": "A token, which can be sent as ListSandboxEnvironmentTemplatesRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages." }, "sandboxEnvironmentTemplates": { "items": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplate" }, "description": "The SandboxEnvironmentTemplates matching the request.", "type": "array" } }, "description": "Response message for SandboxEnvironmentService.ListSandboxEnvironmentTemplates.", "type": "object" }, "GoogleCloudAiplatformV1GenerateUserScenariosRequest": { "id": "GoogleCloudAiplatformV1GenerateUserScenariosRequest", "type": "object", "properties": { "allowCrossRegionModel": { "type": "boolean", "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." }, "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. Required unless `gemini_agent_config` is set, in which case the agents map and `root_agent_id` are derived from the referenced Gemini Agent.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1AgentConfig" } }, "rootAgentId": { "type": "string", "description": "Optional. The agent id to identify the root agent. Required unless `gemini_agent_config` is set, in which case it is derived from the referenced Gemini Agent." }, "geminiAgentConfig": { "$ref": "GoogleCloudAiplatformV1GeminiAgentConfig", "description": "Optional. Config for a Gemini Agent to generate user scenarios for." }, "userScenarioGenerationConfig": { "description": "Required. Configuration for generating user scenarios.", "$ref": "GoogleCloudAiplatformV1UserScenarioGenerationConfig" } }, "description": "Request message for DataFoundryService.GenerateUserScenarios." }, "GoogleCloudAiplatformV1CometSpec": { "properties": { "sourceLanguage": { "description": "Optional. Source language in BCP-47 format.", "type": "string" }, "targetLanguage": { "type": "string", "description": "Optional. Target language in BCP-47 format. Covers both prediction and reference." }, "version": { "enumDescriptions": [ "Comet version unspecified.", "Comet 22 for translation + source + reference (source-reference-combined)." ], "enum": [ "COMET_VERSION_UNSPECIFIED", "COMET_22_SRC_REF" ], "description": "Required. Which version to use for evaluation.", "type": "string" } }, "description": "Spec for Comet metric.", "id": "GoogleCloudAiplatformV1CometSpec", "type": "object" }, "GoogleCloudAiplatformV1ReadFeatureValuesResponseFeatureDescriptor": { "id": "GoogleCloudAiplatformV1ReadFeatureValuesResponseFeatureDescriptor", "description": "Metadata for requested Features.", "properties": { "id": { "type": "string", "description": "Feature ID." } }, "type": "object" }, "GenaiVertexV1DynamicAgentConfig": { "description": "Configuration for dynamic agents.", "properties": { "config": { "description": "For agents that are not supported statically in the API definition.", "$ref": "GenaiVertexV1Struct" } }, "id": "GenaiVertexV1DynamicAgentConfig", "type": "object" }, "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization": { "properties": { "clipPercentLowerbound": { "type": "number", "format": "float", "description": "Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62." }, "polarity": { "enum": [ "POLARITY_UNSPECIFIED", "POSITIVE", "NEGATIVE", "BOTH" ], "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." ], "type": "string", "description": "Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE." }, "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." ], "enum": [ "OVERLAY_TYPE_UNSPECIFIED", "NONE", "ORIGINAL", "GRAYSCALE", "MASK_BLACK" ], "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." }, "type": { "type": "string", "enum": [ "TYPE_UNSPECIFIED", "PIXELS", "OUTLINES" ], "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.", "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." ] }, "colorMap": { "enum": [ "COLOR_MAP_UNSPECIFIED", "PINK_GREEN", "VIRIDIS", "RED", "GREEN", "RED_GREEN", "PINK_WHITE_GREEN" ], "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.", "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." ] } }, "type": "object", "description": "Visualization configurations for image explanation.", "id": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization" }, "GoogleCloudAiplatformV1SchemaPredictParamsVideoActionRecognitionPredictionParams": { "properties": { "maxPredictions": { "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", "format": "int32" }, "confidenceThreshold": { "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", "type": "number", "format": "float" } }, "type": "object", "description": "Prediction model parameters for Video Action Recognition.", "id": "GoogleCloudAiplatformV1SchemaPredictParamsVideoActionRecognitionPredictionParams" }, "GoogleCloudAiplatformV1CreateIndexEndpointOperationMetadata": { "description": "Runtime operation information for IndexEndpointService.CreateIndexEndpoint.", "type": "object", "id": "GoogleCloudAiplatformV1CreateIndexEndpointOperationMetadata", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The operation generic information." } } }, "GenaiVertexV1VideoContent": { "description": "A video content block. ", "id": "GenaiVertexV1VideoContent", "type": "object", "properties": { "processingType": { "enumDescriptions": [ "Default. Uses model-specific processing (3.5 Pro+ --\u003e AGENTIC, older models --\u003e STATIC)", "Fixed-rate frame extraction. All frames placed in context.", "Model-driven dynamic navigation." ], "type": "string", "enum": [ "PROCESSING_UNSPECIFIED", "STATIC", "AGENTIC" ] }, "processingConfig": { "$ref": "GenaiVertexV1VideoContentMediaProcessing" }, "name": { "description": "A user-defined name for this content block. Can be referenced by the model in the final response.", "type": "string" }, "resolution": { "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "LOW", "MEDIUM", "HIGH", "ULTRA_HIGH" ], "description": "The resolution of the media.", "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "Low resolution.", "Medium resolution.", "High resolution.", "Ultra high resolution." ] }, "uri": { "type": "string", "description": "The URI of the video." }, "mimeTypeString": { "description": "Flexible MIME type string of the video, superseding mime_type = 1. Note: Bespoke logic in the GAOS parser/serializer maps this to the \"mime_type\" JSON key.", "type": "string" }, "data": { "description": "The video content.", "format": "byte", "type": "string" } } }, "GoogleCloudAiplatformV1ListDataLabelingJobsResponse": { "properties": { "nextPageToken": { "description": "The standard List next-page token.", "type": "string" }, "dataLabelingJobs": { "items": { "$ref": "GoogleCloudAiplatformV1DataLabelingJob" }, "description": "A list of DataLabelingJobs that matches the specified filter in the request.", "type": "array" } }, "description": "Response message for JobService.ListDataLabelingJobs.", "type": "object", "id": "GoogleCloudAiplatformV1ListDataLabelingJobsResponse" }, "GoogleCloudAiplatformV1CreateRegistryFeatureOperationMetadata": { "type": "object", "properties": { "genericMetadata": { "description": "Operation metadata for Feature.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "description": "Details of operations that perform create FeatureGroup.", "id": "GoogleCloudAiplatformV1CreateRegistryFeatureOperationMetadata" }, "GoogleCloudAiplatformV1SchemaPromptSpecInteractionData": { "description": "Defines data for an interaction prompt.", "properties": { "interactionIds": { "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.", "type": "array", "items": { "type": "string" } } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaPromptSpecInteractionData" }, "GoogleCloudAiplatformV1ModelContainerSpec": { "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).", "id": "GoogleCloudAiplatformV1ModelContainerSpec", "type": "object", "properties": { "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" }, "ports": { "items": { "$ref": "GoogleCloudAiplatformV1Port" }, "description": "Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: ```json [ { \"containerPort\": 8080 } ] ``` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).", "type": "array" }, "imageUri": { "description": "Required. Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.", "type": "string" }, "deploymentTimeout": { "type": "string", "description": "Immutable. Deployment timeout. Limit for deployment timeout is 2 hours.", "format": "google-duration" }, "startupProbe": { "description": "Immutable. Specification for Kubernetes startup probe.", "$ref": "GoogleCloudAiplatformV1Probe" }, "env": { "items": { "$ref": "GoogleCloudAiplatformV1EnvVar" }, "description": "Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ```json [ { \"name\": \"VAR_1\", \"value\": \"foo\" }, { \"name\": \"VAR_2\", \"value\": \"$(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). At most 200 environment variables can be specified. Each variable (`NAME=value`) must be smaller than 128 KiB, and the total size of all variables must not exceed 512 KiB.", "type": "array" }, "healthProbe": { "$ref": "GoogleCloudAiplatformV1Probe", "description": "Immutable. Specification for Kubernetes readiness probe." }, "command": { "type": "array", "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).", "items": { "type": "string" } }, "livenessProbe": { "description": "Immutable. Specification for Kubernetes liveness probe.", "$ref": "GoogleCloudAiplatformV1Probe" }, "args": { "items": { "type": "string" }, "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" }, "sharedMemorySizeMb": { "format": "int64", "description": "Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes.", "type": "string" }, "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": "GoogleCloudAiplatformV1Port" } }, "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" }, "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" } } }, "GoogleCloudAiplatformV1CancelTrainingPipelineRequest": { "type": "object", "properties": {}, "description": "Request message for PipelineService.CancelTrainingPipeline.", "id": "GoogleCloudAiplatformV1CancelTrainingPipelineRequest" }, "GoogleCloudAiplatformV1SummaryMetrics": { "description": "The summary metrics for the evaluation run.", "properties": { "totalItems": { "format": "int32", "type": "integer", "description": "Optional. The total number of items that were evaluated." }, "metrics": { "additionalProperties": { "type": "any" }, "description": "Optional. Map of metric name to metric value.", "type": "object" }, "failedItems": { "type": "integer", "description": "Optional. The number of items that failed to be evaluated.", "format": "int32" } }, "type": "object", "id": "GoogleCloudAiplatformV1SummaryMetrics" }, "GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig": { "description": "The config for scheduling monitoring job.", "properties": { "monitorWindow": { "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.", "type": "string" }, "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" } }, "id": "GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig", "type": "object" }, "CloudAiLargeModelsVisionGenerateVideoExperimentsConditioningFrame": { "type": "object", "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsConditioningFrame", "properties": { "frameNum": { "description": "The index of the frame, starts with zero and must be a multiple of 8.", "format": "int32", "type": "integer" }, "image": { "$ref": "CloudAiLargeModelsVisionGenerateVideoRequestImage", "description": "The image data for this conditioning frame." } } }, "CloudAiLargeModelsVisionVideo": { "description": "Video", "properties": { "video": { "type": "string", "description": "Raw bytes.", "format": "byte" }, "text": { "description": "Text/Expanded text input for Help Me Write.", "type": "string" }, "encodedVideo": { "description": "Base 64 encoded video bytes.", "type": "string" }, "encoding": { "description": "Video encoding, for example \"video/mp4\".", "type": "string" }, "uri": { "description": "Path to another storage (typically Google Cloud Storage).", "type": "string" } }, "type": "object", "id": "CloudAiLargeModelsVisionVideo" }, "GoogleCloudAiplatformV1ListModelDeploymentMonitoringJobsResponse": { "properties": { "modelDeploymentMonitoringJobs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob" }, "description": "A list of ModelDeploymentMonitoringJobs that matches the specified filter in the request." }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "type": "object", "description": "Response message for JobService.ListModelDeploymentMonitoringJobs.", "id": "GoogleCloudAiplatformV1ListModelDeploymentMonitoringJobsResponse" }, "CloudAiLargeModelsVisionImage": { "properties": { "raiInfo": { "$ref": "CloudAiLargeModelsVisionRaiInfo", "description": "RAI info for image." }, "image": { "format": "byte", "type": "string", "description": "Raw bytes." }, "uri": { "description": "Path to another storage (typically Google Cloud Storage).", "type": "string" }, "text": { "description": "Text/Expanded text input for imagen.", "type": "string" }, "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" }, "imageSize": { "description": "Image size. The size of the image. Can be self reported, or computed from the image bytes.", "$ref": "CloudAiLargeModelsVisionImageImageSize" }, "semanticFilterResponse": { "$ref": "CloudAiLargeModelsVisionSemanticFilterResponse", "description": "Semantic filter info for image." }, "imageRaiScores": { "description": "RAI scores for generated image.", "$ref": "CloudAiLargeModelsVisionImageRAIScores" }, "encoding": { "type": "string", "description": "Image encoding, encoded as \"image/png\" or \"image/jpg\"." } }, "description": "Image.", "id": "CloudAiLargeModelsVisionImage", "type": "object" }, "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScaling": { "description": "Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).", "properties": { "minNodeCount": { "format": "int32", "type": "integer", "description": "Required. The minimum number of nodes to scale down to. Must be greater than or equal to 1." }, "maxNodeCount": { "type": "integer", "description": "The maximum number of nodes to scale up to. Must be greater than min_node_count, and less than or equal to 10 times of 'min_node_count'.", "format": "int32" }, "cpuUtilizationTarget": { "description": "Optional. The cpu utilization that the Autoscaler should be trying to achieve. This number is on a scale from 0 (no utilization) to 100 (total utilization), and is limited between 10 and 80. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set or set to 0, default to 50.", "format": "int32", "type": "integer" } }, "id": "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScaling", "type": "object" }, "GoogleCloudAiplatformV1PairwiseMetricInstance": { "type": "object", "properties": { "contentMapInstance": { "$ref": "GoogleCloudAiplatformV1ContentMap", "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" } }, "description": "Pairwise metric instance. Usually one instance corresponds to one row in an evaluation dataset.", "id": "GoogleCloudAiplatformV1PairwiseMetricInstance" }, "GoogleCloudAiplatformV1CreatePersistentResourceOperationMetadata": { "description": "Details of operations that perform create PersistentResource.", "properties": { "progressMessage": { "type": "string", "description": "Progress Message for Create LRO" }, "genericMetadata": { "description": "Operation metadata for PersistentResource.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "type": "object", "id": "GoogleCloudAiplatformV1CreatePersistentResourceOperationMetadata" }, "GoogleCloudAiplatformV1Measurement": { "properties": { "metrics": { "items": { "$ref": "GoogleCloudAiplatformV1MeasurementMetric" }, "readOnly": true, "description": "Output only. A list of metrics got by evaluating the objective functions using suggested Parameter values.", "type": "array" }, "stepCount": { "description": "Output only. The number of steps the machine learning model has been trained for. Must be non-negative.", "format": "int64", "readOnly": true, "type": "string" }, "elapsedDuration": { "format": "google-duration", "type": "string", "description": "Output only. Time that the Trial has been running at the point of this Measurement.", "readOnly": true } }, "id": "GoogleCloudAiplatformV1Measurement", "type": "object", "description": "A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values." }, "GoogleCloudAiplatformV1ListEventsResponse": { "description": "Response message for SessionService.ListEvents.", "type": "object", "properties": { "nextPageToken": { "type": "string", "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." }, "sessionEvents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SessionEvent" }, "description": "A list of events matching the request. Ordered by timestamp in ascending order." } }, "id": "GoogleCloudAiplatformV1ListEventsResponse" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics": { "properties": { "f1Score": { "description": "The harmonic mean of recall and precision.", "format": "float", "type": "number" }, "confidenceThreshold": { "description": "Metrics are computed with an assumption that the Model never returns predictions with score lower than this value.", "type": "number", "format": "float" }, "precision": { "description": "Precision for the given confidence threshold.", "format": "float", "type": "number" }, "recall": { "description": "Recall (True Positive Rate) for the given confidence threshold.", "type": "number", "format": "float" } }, "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics", "type": "object" }, "GoogleCloudAiplatformV1ExportModelOperationMetadataOutputInfo": { "id": "GoogleCloudAiplatformV1ExportModelOperationMetadataOutputInfo", "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.", "readOnly": true, "type": "string" }, "imageOutputUri": { "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.", "type": "string", "readOnly": true } }, "type": "object", "description": "Further describes the output of the ExportModel. Supplements ExportModelRequest.OutputConfig." }, "GoogleCloudAiplatformV1ModelOriginalModelInfo": { "id": "GoogleCloudAiplatformV1ModelOriginalModelInfo", "description": "Contains information about the original Model if this Model is a copy.", "type": "object", "properties": { "model": { "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}`", "type": "string", "readOnly": true } } }, "GenaiVertexV1Tool": { "type": "object", "description": "A tool that can be used by the model.", "properties": { "function": { "description": "A function that can be used by the model.", "$ref": "GenaiVertexV1Function" }, "codeExecution": { "$ref": "GenaiVertexV1CodeExecution", "description": "A tool that can be used by the model to execute code." }, "googleSearch": { "description": "A tool that can be used by the model to search Google.", "$ref": "GenaiVertexV1GoogleSearch" }, "urlContext": { "description": "A tool that can be used by the model to fetch URL context.", "$ref": "GenaiVertexV1UrlContext" }, "computerUse": { "$ref": "GenaiVertexV1ComputerUse", "description": "Tool to support the model interacting directly with the computer." }, "fileSearch": { "$ref": "GenaiVertexV1FileSearch", "description": "A tool that can be used by the model to search files." }, "googleMaps": { "description": "A tool that can be used by the model to search Google Maps.", "$ref": "GenaiVertexV1GoogleMaps" }, "retrieval": { "description": "A tool that can be used by the model to retrieve files.", "$ref": "GenaiVertexV1Retrieval" }, "mcpServer": { "description": "A MCPServer is a server that can be called by the model to perform actions.", "$ref": "GenaiVertexV1McpServer" } }, "id": "GenaiVertexV1Tool" }, "GoogleCloudAiplatformV1DeployResponse": { "properties": { "model": { "description": "Output only. The name of the Model created. Format: `projects/{project}/locations/{location}/models/{model}`", "type": "string", "readOnly": true }, "endpoint": { "type": "string", "description": "Output only. The name of the Endpoint created. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "readOnly": true }, "publisherModel": { "description": "Output only. 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`", "type": "string", "readOnly": true } }, "description": "Response message for ModelGardenService.Deploy.", "id": "GoogleCloudAiplatformV1DeployResponse", "type": "object" }, "GoogleCloudAiplatformV1ToolGoogleSearchSearchTypes": { "description": "Different types of search that can be enabled on the GoogleSearch tool.", "id": "GoogleCloudAiplatformV1ToolGoogleSearchSearchTypes", "type": "object", "properties": { "imageSearch": { "$ref": "GoogleCloudAiplatformV1ToolGoogleSearchImageSearch", "description": "Optional. Setting this field enables image search. Image bytes are returned." }, "webSearch": { "description": "Optional. Setting this field enables web search. Only text results are returned.", "$ref": "GoogleCloudAiplatformV1ToolGoogleSearchWebSearch" } } }, "GoogleCloudAiplatformV1PartialArg": { "type": "object", "properties": { "jsonPath": { "description": "Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. \"$.foo.bar[0].data\".", "type": "string" }, "boolValue": { "description": "Optional. Represents a boolean value.", "type": "boolean" }, "numberValue": { "type": "number", "description": "Optional. Represents a double value.", "format": "double" }, "stringValue": { "type": "string", "description": "Optional. Represents a string value." }, "nullValue": { "type": "string", "description": "Optional. Represents a null value.", "enum": [ "NULL_VALUE" ], "enumDescriptions": [ "Null value." ] }, "willContinue": { "type": "boolean", "description": "Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow." } }, "id": "GoogleCloudAiplatformV1PartialArg", "description": "Partial argument value of the function call." }, "GoogleCloudAiplatformV1ListRagCorporaResponse": { "type": "object", "description": "Response message for VertexRagDataService.ListRagCorpora.", "properties": { "ragCorpora": { "description": "List of RagCorpora in the requested page.", "items": { "$ref": "GoogleCloudAiplatformV1RagCorpus" }, "type": "array" }, "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListRagCorporaRequest.page_token to obtain that page.", "type": "string" } }, "id": "GoogleCloudAiplatformV1ListRagCorporaResponse" }, "GoogleCloudAiplatformV1RagRetrievalConfig": { "id": "GoogleCloudAiplatformV1RagRetrievalConfig", "type": "object", "description": "Specifies the context retrieval config.", "properties": { "ranking": { "description": "Optional. Config for ranking and reranking.", "$ref": "GoogleCloudAiplatformV1RagRetrievalConfigRanking" }, "topK": { "description": "Optional. The number of contexts to retrieve.", "format": "int32", "type": "integer" }, "filter": { "description": "Optional. Config for filters.", "$ref": "GoogleCloudAiplatformV1RagRetrievalConfigFilter" } } }, "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain": { "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.", "properties": { "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.", "type": "number", "format": "float" }, "maxValue": { "type": "number", "description": "The maximum permissible value for this feature.", "format": "float" }, "minValue": { "format": "float", "description": "The minimum permissible value for this feature.", "type": "number" }, "originalMean": { "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.", "type": "number", "format": "float" } }, "type": "object", "id": "GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain" }, "GoogleCloudAiplatformV1PredictRequest": { "id": "GoogleCloudAiplatformV1PredictRequest", "properties": { "instances": { "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.", "type": "array" }, "labels": { "description": "Optional. The user labels for Imagen billing usage only. Only Imagen supports labels. For other use cases, it will be ignored.", "type": "object", "additionalProperties": { "type": "string" } }, "parameters": { "type": "any", "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." } }, "description": "Request message for PredictionService.Predict.", "type": "object" }, "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity": { "description": "The properties for a detected entity from the rai signal.", "id": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity", "properties": { "description": { "description": "Description of the label", "type": "string" }, "score": { "type": "number", "format": "float", "description": "Confidence score of the label" }, "iouScore": { "format": "float", "description": "The intersection ratio between the detection bounding box and the mask.", "type": "number" }, "mid": { "description": "MID of the label", "type": "string" }, "boundingBox": { "description": "Bounding box of the label", "$ref": "CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox" } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaVideoDataItem": { "id": "GoogleCloudAiplatformV1SchemaVideoDataItem", "type": "object", "description": "Payload of Video DataItem.", "properties": { "gcsUri": { "type": "string", "description": "Required. Google Cloud Storage URI points to the original video in user's bucket. The video is up to 50 GB in size and up to 3 hour in duration." }, "mimeType": { "description": "Output only. The mime type of the content of the video. Only the videos in below listed mime types are supported. Supported mime_type: - video/mp4 - video/avi - video/quicktime", "readOnly": true, "type": "string" } } }, "GoogleCloudAiplatformV1CancelDataLabelingJobRequest": { "type": "object", "description": "Request message for JobService.CancelDataLabelingJob.", "properties": {}, "id": "GoogleCloudAiplatformV1CancelDataLabelingJobRequest" }, "GoogleCloudAiplatformV1InputDataConfig": { "description": "Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.", "id": "GoogleCloudAiplatformV1InputDataConfig", "properties": { "fractionSplit": { "$ref": "GoogleCloudAiplatformV1FractionSplit", "description": "Split based on fractions defining the size of each set." }, "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" }, "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" }, "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": "GoogleCloudAiplatformV1GcsDestination" }, "filterSplit": { "$ref": "GoogleCloudAiplatformV1FilterSplit", "description": "Split based on the provided filters for each set." }, "annotationsFilter": { "description": "Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem.", "type": "string" }, "stratifiedSplit": { "$ref": "GoogleCloudAiplatformV1StratifiedSplit", "description": "Supported only for tabular Datasets. Split based on the distribution of the specified column." }, "persistMlUseAssignment": { "description": "Whether to persist the ML use assignment to data item system labels.", "type": "boolean" }, "timestampSplit": { "$ref": "GoogleCloudAiplatformV1TimestampSplit", "description": "Supported only for tabular Datasets. Split based on the timestamp of the input data pieces." }, "predefinedSplit": { "$ref": "GoogleCloudAiplatformV1PredefinedSplit", "description": "Supported only for tabular Datasets. Split based on a predefined key." }, "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\"", "$ref": "GoogleCloudAiplatformV1BigQueryDestination" }, "datasetId": { "type": "string", "description": "Required. The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from." } }, "type": "object" }, "GoogleCloudAiplatformV1ToolParameterKVMatchMetricValue": { "id": "GoogleCloudAiplatformV1ToolParameterKVMatchMetricValue", "description": "Tool parameter key value match metric value for an instance.", "properties": { "score": { "readOnly": true, "format": "float", "type": "number", "description": "Output only. Tool parameter key value match score." } }, "type": "object" }, "GoogleCloudAiplatformV1FeatureGroup": { "id": "GoogleCloudAiplatformV1FeatureGroup", "properties": { "labels": { "description": "Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded).\" System reserved label keys are prefixed with \"aiplatform.googleapis.com/\" and are immutable.", "type": "object", "additionalProperties": { "type": "string" } }, "bigQuery": { "$ref": "GoogleCloudAiplatformV1FeatureGroupBigQuery", "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", "enum": [ "SERVICE_AGENT_TYPE_UNSPECIFIED", "SERVICE_AGENT_TYPE_PROJECT", "SERVICE_AGENT_TYPE_FEATURE_GROUP" ], "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." }, "description": { "type": "string", "description": "Optional. Description of the FeatureGroup." }, "createTime": { "description": "Output only. Timestamp when this FeatureGroup was created.", "type": "string", "format": "google-datetime", "readOnly": true }, "serviceAccountEmail": { "type": "string", "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.", "readOnly": true }, "name": { "description": "Identifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`", "type": "string" }, "updateTime": { "readOnly": true, "format": "google-datetime", "description": "Output only. Timestamp when this FeatureGroup was last updated.", "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 Group.", "type": "object" }, "GoogleCloudAiplatformV1SyntheticExample": { "properties": { "fields": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SyntheticField" }, "description": "Required. A list of fields that constitute an example." } }, "description": "A single instance of generated synthetic data. Each example is made up of one or more named fields, as defined in `OutputFieldSpec`. These examples are used as few-shot examples to show the model what you want (in `GenerateSyntheticDataRequest.examples`) and to return generated examples in the response (in `GenerateSyntheticDataResponse.synthetic_examples`).", "id": "GoogleCloudAiplatformV1SyntheticExample", "type": "object" }, "GoogleCloudAiplatformV1FluencySpec": { "type": "object", "id": "GoogleCloudAiplatformV1FluencySpec", "properties": { "version": { "description": "Optional. Which version to use for evaluation.", "format": "int32", "type": "integer" } }, "description": "Spec for fluency score metric." }, "GoogleCloudAiplatformV1Port": { "type": "object", "id": "GoogleCloudAiplatformV1Port", "description": "Represents a network port in a container.", "properties": { "containerPort": { "description": "The number of the port to expose on the pod's IP address. Must be a valid port number, between 1 and 65535 inclusive.", "format": "int32", "type": "integer" } } }, "GenaiVertexV1VideoContentMediaProcessing": { "type": "object", "properties": { "static": { "$ref": "GenaiVertexV1VideoContentStaticMediaProcessing" } }, "id": "GenaiVertexV1VideoContentMediaProcessing" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetrics": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetrics", "properties": { "confidenceMetrics": { "type": "array", "description": "Metrics for each label-match confidence_threshold from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99.", "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics" } }, "precisionWindowLength": { "format": "google-duration", "type": "string", "description": "This VideoActionMetrics is calculated based on this prediction window length. If the predicted action's timestamp is inside the time window whose center is the ground truth action's timestamp with this specific length, the prediction result is treated as a true positive." }, "meanAveragePrecision": { "description": "The mean average precision.", "format": "float", "type": "number" } }, "description": "The Evaluation metrics given a specific precision_window_length.", "type": "object" }, "GoogleCloudAiplatformV1ModelBaseModelSource": { "properties": { "modelGardenSource": { "$ref": "GoogleCloudAiplatformV1ModelGardenSource", "description": "Source information of Model Garden models." }, "genieSource": { "description": "Information about the base model of Genie models.", "$ref": "GoogleCloudAiplatformV1GenieSource" } }, "description": "User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models.", "type": "object", "id": "GoogleCloudAiplatformV1ModelBaseModelSource" }, "GoogleCloudAiplatformV1ExportFractionSplit": { "id": "GoogleCloudAiplatformV1ExportFractionSplit", "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.", "type": "object", "properties": { "testFraction": { "format": "double", "type": "number", "description": "The fraction of the input data that is to be used to evaluate the Model." }, "trainingFraction": { "type": "number", "description": "The fraction of the input data that is to be used to train the Model.", "format": "double" }, "validationFraction": { "type": "number", "description": "The fraction of the input data that is to be used to validate the Model.", "format": "double" } } }, "GoogleCloudAiplatformV1CancelBatchPredictionJobRequest": { "id": "GoogleCloudAiplatformV1CancelBatchPredictionJobRequest", "description": "Request message for JobService.CancelBatchPredictionJob.", "properties": {}, "type": "object" }, "GoogleCloudAiplatformV1TensorboardBlob": { "id": "GoogleCloudAiplatformV1TensorboardBlob", "description": "One blob (e.g, image, graph) viewable on a blob metric plot.", "properties": { "data": { "description": "Optional. The bytes of the blob is not present unless it's returned by the ReadTensorboardBlobData endpoint.", "type": "string", "format": "byte" }, "id": { "type": "string", "readOnly": true, "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": "object" }, "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestEntityTypeSpec": { "type": "object", "properties": { "featureSelector": { "description": "Required. Selectors choosing which Feature values to read from the EntityType.", "$ref": "GoogleCloudAiplatformV1FeatureSelector" }, "settings": { "items": { "$ref": "GoogleCloudAiplatformV1DestinationFeatureSetting" }, "description": "Per-Feature settings for the batch read.", "type": "array" }, "entityTypeId": { "description": "Required. ID of the EntityType to select Features. The EntityType id is the entity_type_id specified during EntityType creation.", "type": "string" } }, "id": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestEntityTypeSpec", "description": "Selects Features of an EntityType to read values of and specifies read settings." }, "GoogleCloudAiplatformV1PredictSchemata": { "id": "GoogleCloudAiplatformV1PredictSchemata", "properties": { "instanceSchemaUri": { "type": "string", "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." }, "predictionSchemaUri": { "type": "string", "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." }, "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" } }, "type": "object", "description": "Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob." }, "GoogleCloudAiplatformV1ScheduleRunResponse": { "id": "GoogleCloudAiplatformV1ScheduleRunResponse", "type": "object", "properties": { "scheduledRunTime": { "type": "string", "format": "google-datetime", "description": "The scheduled run time based on the user-specified schedule." }, "runResponse": { "description": "The response of the scheduled run.", "type": "string" } }, "description": "Status of a scheduled run." }, "GoogleCloudAiplatformV1SchemaImageDatasetMetadata": { "properties": { "gcsBucket": { "type": "string", "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset." }, "dataItemSchemaUri": { "type": "string", "description": "Points to a YAML file stored on Google Cloud Storage describing payload of the Image DataItems that belong to this Dataset." } }, "id": "GoogleCloudAiplatformV1SchemaImageDatasetMetadata", "type": "object", "description": "The metadata of Datasets that contain Image DataItems." }, "GoogleCloudAiplatformV1StructValue": { "description": "Struct (or object) type feature value.", "properties": { "values": { "items": { "$ref": "GoogleCloudAiplatformV1StructFieldValue" }, "description": "A list of field values.", "type": "array" } }, "type": "object", "id": "GoogleCloudAiplatformV1StructValue" }, "GoogleCloudAiplatformV1FluencyInput": { "description": "Input for fluency metric.", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1FluencySpec", "description": "Required. Spec for fluency score metric." }, "instance": { "$ref": "GoogleCloudAiplatformV1FluencyInstance", "description": "Required. Fluency instance." } }, "id": "GoogleCloudAiplatformV1FluencyInput", "type": "object" }, "GoogleCloudAiplatformV1PreferenceOptimizationDataStats": { "type": "object", "properties": { "scoreVariancePerExampleDistribution": { "$ref": "GoogleCloudAiplatformV1DatasetDistribution", "readOnly": true, "description": "Output only. Dataset distributions for scores variance per example." }, "userOutputTokenDistribution": { "$ref": "GoogleCloudAiplatformV1DatasetDistribution", "description": "Output only. Dataset distributions for the user output tokens.", "readOnly": true }, "scoresDistribution": { "$ref": "GoogleCloudAiplatformV1DatasetDistribution", "description": "Output only. Dataset distributions for scores.", "readOnly": true }, "tuningStepCount": { "readOnly": true, "description": "Output only. Number of tuning steps for this Tuning Job.", "type": "string", "format": "int64" }, "userInputTokenDistribution": { "description": "Output only. Dataset distributions for the user input tokens.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1DatasetDistribution" }, "userDatasetExamples": { "type": "array", "readOnly": true, "description": "Output only. Sample user examples in the training dataset.", "items": { "$ref": "GoogleCloudAiplatformV1GeminiPreferenceExample" } }, "droppedExampleIndices": { "items": { "type": "string", "format": "int64" }, "type": "array", "description": "Output only. A partial sample of the indices (starting from 1) of the dropped examples.", "readOnly": true }, "totalBillableTokenCount": { "readOnly": true, "type": "string", "description": "Output only. Number of billable tokens in the tuning dataset.", "format": "int64" }, "droppedExampleReasons": { "description": "Output only. For each index in `dropped_example_indices`, the user-facing reason why the example was dropped.", "readOnly": true, "type": "array", "items": { "type": "string" } }, "tuningDatasetExampleCount": { "description": "Output only. Number of examples in the tuning dataset.", "type": "string", "format": "int64", "readOnly": true } }, "description": "Statistics computed for datasets used for preference optimization.", "id": "GoogleCloudAiplatformV1PreferenceOptimizationDataStats" }, "GoogleCloudAiplatformV1EvaluationInstanceInstanceDataContents": { "properties": { "contents": { "description": "Optional. Repeated contents.", "items": { "$ref": "GoogleCloudAiplatformV1Content" }, "type": "array" } }, "description": "List of standard Content messages from Gemini API.", "id": "GoogleCloudAiplatformV1EvaluationInstanceInstanceDataContents", "type": "object" }, "GenaiVertexV1FileSearchCallDelta": { "id": "GenaiVertexV1FileSearchCallDelta", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1RestoreDatasetVersionOperationMetadata": { "description": "Runtime operation information for DatasetService.RestoreDatasetVersion.", "id": "GoogleCloudAiplatformV1RestoreDatasetVersionOperationMetadata", "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataBigQuerySource": { "id": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataBigQuerySource", "properties": { "uri": { "type": "string", "description": "The URI of a BigQuery table." } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaPredictPredictionTextSentimentPredictionResult": { "id": "GoogleCloudAiplatformV1SchemaPredictPredictionTextSentimentPredictionResult", "description": "Prediction output format for Text Sentiment", "type": "object", "properties": { "sentiment": { "format": "int32", "type": "integer", "description": "The integer sentiment labels between 0 (inclusive) and sentimentMax label (inclusive), while 0 maps to the least positive sentiment and sentimentMax maps to the most positive one. The higher the score is, the more positive the sentiment in the text snippet is. Note: sentimentMax is an integer value between 1 (inclusive) and 10 (inclusive)." } } }, "GoogleCloudAiplatformV1EvaluationRunMetricRubricBasedMetricSpecRepeatedRubrics": { "properties": { "rubrics": { "description": "The list of rubrics.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Rubric" } } }, "description": "Defines a list of rubrics, used when providing rubrics inline.", "id": "GoogleCloudAiplatformV1EvaluationRunMetricRubricBasedMetricSpecRepeatedRubrics", "type": "object" }, "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectMemoriesSourceDirectMemory": { "id": "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectMemoriesSourceDirectMemory", "properties": { "topics": { "type": "array", "description": "Optional. The topics that the consolidated memories should be associated with.", "items": { "$ref": "GoogleCloudAiplatformV1MemoryTopicId" } }, "fact": { "description": "Required. The fact to consolidate with existing memories.", "type": "string" } }, "description": "A direct memory to upload to Memory Bank.", "type": "object" }, "GoogleCloudAiplatformV1ImportDataConfig": { "id": "GoogleCloudAiplatformV1ImportDataConfig", "type": "object", "description": "Describes the location from where we import data into a Dataset, together with the labels that will be applied to the DataItems and the Annotations.", "properties": { "dataItemLabels": { "description": "Labels that will be applied to newly imported DataItems. If an identical DataItem as one being imported already exists in the Dataset, then these labels will be appended to these of the already existing one, and if labels with identical key is imported before, the old label value will be overwritten. If two DataItems are identical in the same import data operation, the labels will be combined and if key collision happens in this case, one of the values will be picked randomly. Two DataItems are considered identical if their content bytes are identical (e.g. image bytes or pdf bytes). These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file.", "type": "object", "additionalProperties": { "type": "string" } }, "gcsSource": { "description": "The Google Cloud Storage location for the input content.", "$ref": "GoogleCloudAiplatformV1GcsSource" }, "annotationLabels": { "additionalProperties": { "type": "string" }, "type": "object", "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." }, "importSchemaUri": { "type": "string", "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)." } } }, "GenaiVertexV1CreateInteractionRequest": { "id": "GenaiVertexV1CreateInteractionRequest", "properties": { "store": { "type": "boolean", "description": "Input only. Whether to store the response and request for later retrieval." }, "background": { "description": "Input only. Whether to run the model interaction in the background.", "type": "boolean" }, "stream": { "description": "Input only. Whether the interaction will be streamed.", "type": "boolean" }, "interaction": { "description": "The interaction to create.", "$ref": "GenaiVertexV1Interaction" } }, "description": "Configuration parameters for creating an interaction.", "type": "object" }, "GoogleCloudAiplatformV1SchemaPredictInstanceTextClassificationPredictionInstance": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaPredictInstanceTextClassificationPredictionInstance", "properties": { "content": { "description": "The text snippet to make the predictions on.", "type": "string" }, "mimeType": { "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain", "type": "string" } }, "description": "Prediction input format for Text Classification." }, "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectMemoriesSource": { "id": "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectMemoriesSource", "type": "object", "description": "Defines a direct source of memories that should be uploaded to Memory Bank with consolidation.", "properties": { "directMemories": { "items": { "$ref": "GoogleCloudAiplatformV1GenerateMemoriesRequestDirectMemoriesSourceDirectMemory" }, "description": "Required. The direct memories to upload to Memory Bank. At most 5 direct memories are allowed per request.", "type": "array" } } }, "GoogleCloudAiplatformV1UploadRagFileRequest": { "id": "GoogleCloudAiplatformV1UploadRagFileRequest", "properties": { "ragFile": { "description": "Required. The RagFile to upload.", "$ref": "GoogleCloudAiplatformV1RagFile" }, "uploadRagFileConfig": { "$ref": "GoogleCloudAiplatformV1UploadRagFileConfig", "description": "Required. The config for the RagFiles to be uploaded into the RagCorpus. VertexRagDataService.UploadRagFile." } }, "description": "Request message for VertexRagDataService.UploadRagFile.", "type": "object" }, "GoogleCloudAiplatformV1SchemaPromptApiSchema": { "type": "object", "properties": { "multimodalPrompt": { "description": "Multimodal prompt which embeds preambles to prompt string.", "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecMultimodalPrompt" }, "translationPrompt": { "description": "The prompt variation for Translation use case.", "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecTranslationPrompt" }, "structuredPrompt": { "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecStructuredPrompt", "description": "The prompt variation that stores preambles in separate fields." }, "apiSchemaVersion": { "description": "The Schema version that represents changes to the API behavior.", "type": "string" }, "executions": { "items": { "$ref": "GoogleCloudAiplatformV1SchemaPromptInstancePromptExecution" }, "type": "array", "description": "A list of execution instances for constructing a ready-to-use prompt." } }, "description": "The A2 schema of a prompt.", "id": "GoogleCloudAiplatformV1SchemaPromptApiSchema" }, "CloudAiLargeModelsVisionGenerateVideoExperimentsSpatialAlignmentConfig": { "type": "object", "properties": { "enable": { "type": "boolean", "description": "Optional. If true, enable alignment." } }, "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsSpatialAlignmentConfig", "description": "Configuration for spatial alignment." }, "GoogleCloudAiplatformV1FunctionDeclaration": { "id": "GoogleCloudAiplatformV1FunctionDeclaration", "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": { "parameters": { "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", "$ref": "GoogleCloudAiplatformV1Schema" }, "description": { "type": "string", "description": "Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function." }, "parametersJsonSchema": { "type": "any", "description": "Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { \"type\": \"object\", \"properties\": { \"name\": { \"type\": \"string\" }, \"age\": { \"type\": \"integer\" } }, \"additionalProperties\": false, \"required\": [\"name\", \"age\"], \"propertyOrdering\": [\"name\", \"age\"] } ``` This field is mutually exclusive with `parameters`." }, "response": { "$ref": "GoogleCloudAiplatformV1Schema", "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." }, "behavior": { "enumDescriptions": [ "This value is unspecified.", "If set, the system will wait to receive the function response before continuing the conversation.", "If set, the system will not wait to receive the function response. Instead, it will attempt to handle function responses as they become available while maintaining the conversation between the user and the model." ], "enum": [ "UNSPECIFIED", "BLOCKING", "NON_BLOCKING" ], "description": "Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.", "type": "string" }, "name": { "type": "string", "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." }, "responseJsonSchema": { "type": "any", "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`." } } }, "GenaiVertexV1ProcessingResultDelta": { "description": "Streaming delta for the result of a server-initiated media processing step.", "id": "GenaiVertexV1ProcessingResultDelta", "properties": {}, "type": "object" }, "GoogleCloudAiplatformV1SchemaPredictInstanceTextSentimentPredictionInstance": { "id": "GoogleCloudAiplatformV1SchemaPredictInstanceTextSentimentPredictionInstance", "description": "Prediction input format for Text Sentiment.", "type": "object", "properties": { "content": { "type": "string", "description": "The text snippet to make the predictions on." }, "mimeType": { "description": "The MIME type of the text snippet. The supported MIME types are listed below. - text/plain", "type": "string" } } }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix": { "properties": { "annotationSpecs": { "type": "array", "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.", "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef" } }, "rows": { "description": "Rows in the confusion matrix. The number of rows is equal to the size of `annotationSpecs`. `rowsi` is the number of DataItems that have ground truth of the `annotationSpecs[i]` and are predicted as `annotationSpecs[j]` by the Model being evaluated. For Text Extraction, when `annotationSpecs[i]` is the last element in `annotationSpecs`, i.e. the special negative AnnotationSpec, `rowsi` is the number of predicted entities of `annoatationSpec[j]` that are not labeled as any of the ground truth AnnotationSpec. When annotationSpecs[j] is the special negative AnnotationSpec, `rowsi` is the number of entities have ground truth of `annotationSpec[i]` that are not predicted as an entity by the Model. The value of the last cell, i.e. `rowi` where i == j and `annotationSpec[i]` is the special negative AnnotationSpec, is always 0.", "items": { "type": "array", "items": { "type": "any" } }, "type": "array" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix" }, "GoogleCloudAiplatformV1ListTensorboardExperimentsResponse": { "properties": { "tensorboardExperiments": { "items": { "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" }, "description": "The TensorboardExperiments mathching the request.", "type": "array" }, "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" } }, "description": "Response message for TensorboardService.ListTensorboardExperiments.", "type": "object", "id": "GoogleCloudAiplatformV1ListTensorboardExperimentsResponse" }, "GoogleCloudAiplatformV1PrivateServiceConnectConfig": { "properties": { "enablePrivateServiceConnect": { "type": "boolean", "description": "Required. If true, expose the IndexEndpoint via private service connect." }, "pscAutomationConfigs": { "items": { "$ref": "GoogleCloudAiplatformV1PSCAutomationConfig" }, "type": "array", "description": "Optional. List of projects and networks where the PSC endpoints will be created. This field is used by Online Inference(Prediction) only." }, "serviceAttachment": { "description": "Output only. The name of the generated service attachment resource. This is only populated if the endpoint is deployed with PrivateServiceConnect.", "type": "string", "readOnly": true }, "projectAllowlist": { "type": "array", "items": { "type": "string" }, "description": "A list of Projects from which the forwarding rule will target the service attachment." } }, "id": "GoogleCloudAiplatformV1PrivateServiceConnectConfig", "description": "Represents configuration for private service connect.", "type": "object" }, "GoogleCloudAiplatformV1NearestNeighborsNeighbor": { "id": "GoogleCloudAiplatformV1NearestNeighborsNeighbor", "properties": { "entityId": { "type": "string", "description": "The id of the similar entity." }, "entityKeyValues": { "description": "The attributes of the neighbor, e.g. filters, crowding and metadata Note that full entities are returned only when \"return_full_entity\" is set to true. Otherwise, only the \"entity_id\" and \"distance\" fields are populated.", "$ref": "GoogleCloudAiplatformV1FetchFeatureValuesResponse" }, "distance": { "type": "number", "description": "The distance between the neighbor and the query vector.", "format": "double" } }, "type": "object", "description": "A neighbor of the query vector." }, "GoogleCloudAiplatformV1ExecutableCode": { "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.", "type": "object", "properties": { "id": { "type": "string", "description": "Optional. Unique identifier of the `ExecutableCode` part. The server returns the `CodeExecutionResult` with the matching `id`." }, "language": { "description": "Required. Programming language of the `code`.", "enum": [ "LANGUAGE_UNSPECIFIED", "PYTHON" ], "type": "string", "enumDescriptions": [ "Unspecified language. This value should not be used.", "Python \u003e= 3.10, with numpy and simpy available." ] }, "code": { "type": "string", "description": "Required. The code to be executed." } }, "id": "GoogleCloudAiplatformV1ExecutableCode" }, "GoogleIamV1Policy": { "type": "object", "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/).", "properties": { "etag": { "format": "byte", "type": "string", "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." }, "version": { "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).", "type": "integer", "format": "int32" }, "bindings": { "type": "array", "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`.", "items": { "$ref": "GoogleIamV1Binding" } } }, "id": "GoogleIamV1Policy" }, "GoogleCloudAiplatformV1DeleteFeatureValuesRequest": { "id": "GoogleCloudAiplatformV1DeleteFeatureValuesRequest", "properties": { "selectEntity": { "description": "Select feature values to be deleted by specifying entities.", "$ref": "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectEntity" }, "selectTimeRangeAndFeature": { "description": "Select feature values to be deleted by specifying time range and features.", "$ref": "GoogleCloudAiplatformV1DeleteFeatureValuesRequestSelectTimeRangeAndFeature" } }, "description": "Request message for FeaturestoreService.DeleteFeatureValues.", "type": "object" }, "GoogleCloudAiplatformV1ListModelEvaluationsResponse": { "properties": { "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListModelEvaluationsRequest.page_token to obtain that page.", "type": "string" }, "modelEvaluations": { "items": { "$ref": "GoogleCloudAiplatformV1ModelEvaluation" }, "description": "List of ModelEvaluations in the requested page.", "type": "array" } }, "id": "GoogleCloudAiplatformV1ListModelEvaluationsResponse", "type": "object", "description": "Response message for ModelService.ListModelEvaluations." }, "GoogleCloudAiplatformV1FunctionCallingConfig": { "properties": { "mode": { "description": "Optional. Function calling mode.", "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\"." ], "enum": [ "MODE_UNSPECIFIED", "AUTO", "ANY", "NONE", "VALIDATED" ], "type": "string" }, "allowedFunctionNames": { "items": { "type": "string" }, "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" }, "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" } }, "description": "Function calling config.", "type": "object", "id": "GoogleCloudAiplatformV1FunctionCallingConfig" }, "GoogleCloudAiplatformV1SchemaTablesDatasetMetadata": { "properties": { "inputConfig": { "$ref": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadataInputConfig" } }, "id": "GoogleCloudAiplatformV1SchemaTablesDatasetMetadata", "description": "The metadata of Datasets that contain tables data.", "type": "object" }, "GoogleCloudAiplatformV1PipelineTaskExecutorDetail": { "type": "object", "id": "GoogleCloudAiplatformV1PipelineTaskExecutorDetail", "description": "The runtime detail of a pipeline executor.", "properties": { "containerDetail": { "description": "Output only. The detailed info for a container executor.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetail" }, "customJobDetail": { "$ref": "GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetail", "readOnly": true, "description": "Output only. The detailed info for a custom job executor." } } }, "GoogleCloudAiplatformV1AuthConfigApiKeyConfig": { "type": "object", "properties": { "apiKeySecret": { "description": "Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.", "type": "string" }, "httpElementLocation": { "enum": [ "HTTP_IN_UNSPECIFIED", "HTTP_IN_QUERY", "HTTP_IN_HEADER", "HTTP_IN_PATH", "HTTP_IN_BODY", "HTTP_IN_COOKIE" ], "type": "string", "enumDescriptions": [ "", "Element is in the HTTP request query.", "Element is in the HTTP request header.", "Element is in the HTTP request path.", "Element is in the HTTP request body.", "Element is in the HTTP request cookie." ], "description": "Optional. The location of the API key." }, "name": { "description": "Optional. The parameter name of the API key. E.g. If the API request is \"https://example.com/act?api_key=\", \"api_key\" would be the parameter name.", "type": "string" }, "apiKeyString": { "description": "Optional. The API key to be used in the request directly.", "type": "string" } }, "description": "Config for authentication with API key.", "id": "GoogleCloudAiplatformV1AuthConfigApiKeyConfig" }, "GoogleCloudAiplatformV1ToolParameterKeyMatchInput": { "type": "object", "description": "Input for tool parameter key match metric.", "id": "GoogleCloudAiplatformV1ToolParameterKeyMatchInput", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1ToolParameterKeyMatchSpec", "description": "Required. Spec for tool parameter key match metric." }, "instances": { "type": "array", "description": "Required. Repeated tool parameter key match instances.", "items": { "$ref": "GoogleCloudAiplatformV1ToolParameterKeyMatchInstance" } } } }, "GoogleCloudAiplatformV1Metadata": { "id": "GoogleCloudAiplatformV1Metadata", "properties": { "attributes": { "type": "object", "additionalProperties": { "format": "byte", "type": "string" }, "description": "Optional. Attributes attached to the data. The keys have semantic conventions and the consumers of the attributes should know how to deserialize the value bytes based on the keys." } }, "type": "object", "description": "Metadata for a chunk." }, "GoogleCloudAiplatformV1ListDatasetsResponse": { "properties": { "datasets": { "items": { "$ref": "GoogleCloudAiplatformV1Dataset" }, "description": "A list of Datasets that matches the specified filter in the request.", "type": "array" }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "type": "object", "id": "GoogleCloudAiplatformV1ListDatasetsResponse", "description": "Response message for DatasetService.ListDatasets." }, "GoogleCloudAiplatformV1TuningDataStats": { "description": "The tuning data statistic values for TuningJob.", "type": "object", "properties": { "supervisedTuningDataStats": { "description": "The SFT Tuning data stats.", "$ref": "GoogleCloudAiplatformV1SupervisedTuningDataStats" }, "preferenceOptimizationDataStats": { "readOnly": true, "description": "Output only. Statistics for preference optimization.", "$ref": "GoogleCloudAiplatformV1PreferenceOptimizationDataStats" } }, "id": "GoogleCloudAiplatformV1TuningDataStats" }, "GoogleTypeMoney": { "id": "GoogleTypeMoney", "description": "Represents an amount of money with its currency type.", "type": "object", "properties": { "units": { "description": "The whole units of the amount. For example if `currencyCode` is `\"USD\"`, then 1 unit is one US dollar.", "format": "int64", "type": "string" }, "nanos": { "format": "int32", "type": "integer", "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 $-1.75 is represented as `units`=-1 and `nanos`=-750,000,000." }, "currencyCode": { "description": "The three-letter currency code defined in ISO 4217.", "type": "string" } } }, "GoogleCloudAiplatformV1FeatureViewIndexConfigTreeAHConfig": { "description": "Configuration options for the tree-AH algorithm.", "properties": { "leafNodeEmbeddingCount": { "description": "Optional. Number of embeddings on each leaf node. The default value is 1000 if not set.", "format": "int64", "type": "string" } }, "id": "GoogleCloudAiplatformV1FeatureViewIndexConfigTreeAHConfig", "type": "object" }, "GoogleCloudAiplatformV1PreferenceOptimizationSpec": { "description": "Tuning Spec for Preference Optimization.", "properties": { "exportLastCheckpointOnly": { "type": "boolean", "description": "Optional. If set to true, disable intermediate checkpoints for Preference Optimization and only the last checkpoint will be exported. Otherwise, enable intermediate checkpoints for Preference Optimization. Default is false." }, "trainingDatasetUri": { "description": "Required. Cloud Storage path to file containing training dataset for preference optimization tuning. The dataset must be formatted as a JSONL file.", "type": "string" }, "validationDatasetUri": { "type": "string", "description": "Optional. Cloud Storage path to file containing validation dataset for preference optimization tuning. The dataset must be formatted as a JSONL file." }, "hyperParameters": { "$ref": "GoogleCloudAiplatformV1PreferenceOptimizationHyperParameters", "description": "Optional. Hyperparameters for Preference Optimization." } }, "type": "object", "id": "GoogleCloudAiplatformV1PreferenceOptimizationSpec" }, "GoogleCloudAiplatformV1ExecuteSandboxEnvironmentResponse": { "type": "object", "id": "GoogleCloudAiplatformV1ExecuteSandboxEnvironmentResponse", "properties": { "outputs": { "type": "array", "description": "The outputs from the sandbox environment.", "items": { "$ref": "GoogleCloudAiplatformV1Chunk" } } }, "description": "Response message for SandboxEnvironmentExecutionService.Execute." }, "GoogleCloudAiplatformV1RagVectorDbConfigPinecone": { "type": "object", "id": "GoogleCloudAiplatformV1RagVectorDbConfigPinecone", "properties": { "indexName": { "description": "Pinecone index name. This value cannot be changed after it's set.", "type": "string" } }, "description": "The config for the Pinecone." }, "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityResult": { "description": "Spec for pairwise question answering quality result.", "id": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityResult", "properties": { "pairwiseChoice": { "description": "Output only. Pairwise question answering prediction choice.", "enum": [ "PAIRWISE_CHOICE_UNSPECIFIED", "BASELINE", "CANDIDATE", "TIE" ], "readOnly": true, "type": "string", "enumDescriptions": [ "Unspecified prediction choice.", "Baseline prediction wins", "Candidate prediction wins", "Winner cannot be determined" ] }, "confidence": { "readOnly": true, "description": "Output only. Confidence for question answering quality score.", "type": "number", "format": "float" }, "explanation": { "description": "Output only. Explanation for question answering quality score.", "type": "string", "readOnly": true } }, "type": "object" }, "GenaiVertexV1GoogleSearchCallStepGoogleSearchCallStepArguments": { "properties": { "queries": { "type": "array", "description": "Web search queries for the following-up web search.", "items": { "type": "string" } } }, "type": "object", "id": "GenaiVertexV1GoogleSearchCallStepGoogleSearchCallStepArguments", "description": "The arguments to pass to Google Search." }, "GoogleCloudAiplatformV1GenerateContentResponse": { "id": "GoogleCloudAiplatformV1GenerateContentResponse", "type": "object", "description": "Response message for [PredictionService.GenerateContent].", "properties": { "modelVersion": { "readOnly": true, "description": "Output only. The model version used to generate the response.", "type": "string" }, "candidates": { "items": { "$ref": "GoogleCloudAiplatformV1Candidate" }, "type": "array", "readOnly": true, "description": "Output only. Generated candidates." }, "createTime": { "type": "string", "description": "Output only. Timestamp when the request is made to the server.", "format": "google-datetime", "readOnly": true }, "usageMetadata": { "$ref": "GoogleCloudAiplatformV1GenerateContentResponseUsageMetadata", "description": "Usage metadata about the response(s)." }, "responseId": { "type": "string", "readOnly": true, "description": "Output only. response_id is used to identify each response. It is the encoding of the event_id." }, "promptFeedback": { "description": "Output only. Content filter results for a prompt sent in the request. Note: Sent only in the first stream chunk. Only happens when no candidates were generated due to content violations.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1GenerateContentResponsePromptFeedback" } } }, "GoogleCloudAiplatformV1ComputeTokensRequest": { "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.", "items": { "type": "any" }, "type": "array" }, "model": { "description": "Optional. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers/*/models/*", "type": "string" }, "contents": { "description": "Optional. Input content.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Content" } } }, "id": "GoogleCloudAiplatformV1ComputeTokensRequest", "description": "Request message for ComputeTokens RPC call.", "type": "object" }, "GoogleCloudAiplatformV1RetrieveContextsResponse": { "description": "Response message for VertexRagService.RetrieveContexts.", "properties": { "contexts": { "$ref": "GoogleCloudAiplatformV1RagContexts", "description": "The contexts of the query." } }, "id": "GoogleCloudAiplatformV1RetrieveContextsResponse", "type": "object" }, "GoogleCloudAiplatformV1ToolCodeExecution": { "id": "GoogleCloudAiplatformV1ToolCodeExecution", "properties": {}, "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.", "type": "object" }, "GoogleCloudAiplatformV1ListIndexesResponse": { "properties": { "nextPageToken": { "type": "string", "description": "A token to retrieve next page of results. Pass to ListIndexesRequest.page_token to obtain that page." }, "indexes": { "description": "List of indexes in the requested page.", "items": { "$ref": "GoogleCloudAiplatformV1Index" }, "type": "array" } }, "id": "GoogleCloudAiplatformV1ListIndexesResponse", "type": "object", "description": "Response message for IndexService.ListIndexes." }, "GenaiVertexV1VideoContentStaticMediaProcessing": { "type": "object", "properties": { "endOffset": { "format": "google-duration", "type": "string", "description": "Optional. Segment end time. Specified as a decimal number of seconds followed by an 's' suffix, e.g., \"30s\". Must be non-negative and greater than `start_offset` if `start_offset` is set." }, "startOffset": { "format": "google-duration", "type": "string", "description": "Optional. Segment start time. Specified as a decimal number of seconds followed by an 's' suffix, e.g., \"10.5s\". Must be non-negative." }, "fps": { "format": "double", "description": "Optional. Video frame-rate sampling density.", "type": "number" } }, "id": "GenaiVertexV1VideoContentStaticMediaProcessing" }, "GoogleCloudAiplatformV1RagManagedDbConfigSpanner": { "id": "GoogleCloudAiplatformV1RagManagedDbConfigSpanner", "type": "object", "properties": { "basic": { "description": "Sets the RagManagedDb to the Basic tier. This is the default tier for Spanner mode if not explicitly chosen.", "$ref": "GoogleCloudAiplatformV1RagManagedDbConfigBasic" }, "scaled": { "$ref": "GoogleCloudAiplatformV1RagManagedDbConfigScaled", "description": "Sets the RagManagedDb to the Scaled tier." }, "unprovisioned": { "description": "Sets the RagManagedDb to the Unprovisioned tier.", "$ref": "GoogleCloudAiplatformV1RagManagedDbConfigUnprovisioned" } }, "description": "Message to configure the Spanner database used by RagManagedDb." }, "GoogleCloudAiplatformV1NearestNeighborQueryStringFilter": { "type": "object", "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.", "id": "GoogleCloudAiplatformV1NearestNeighborQueryStringFilter", "properties": { "name": { "description": "Required. Column names in BigQuery that used as filters.", "type": "string" }, "allowTokens": { "description": "Optional. The allowed tokens.", "items": { "type": "string" }, "type": "array" }, "denyTokens": { "description": "Optional. The denied tokens.", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1FindNeighborsResponseNeighbor": { "description": "A neighbor of the query vector.", "properties": { "distance": { "description": "The distance between the neighbor and the dense embedding query.", "type": "number", "format": "double" }, "sparseDistance": { "description": "The distance between the neighbor and the query sparse_embedding.", "type": "number", "format": "double" }, "datapoint": { "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.", "$ref": "GoogleCloudAiplatformV1IndexDatapoint" } }, "id": "GoogleCloudAiplatformV1FindNeighborsResponseNeighbor", "type": "object" }, "GoogleCloudAiplatformV1SuggestTrialsMetadata": { "description": "Details of operations that perform Trials suggestion.", "properties": { "genericMetadata": { "description": "Operation metadata for suggesting Trials.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" }, "clientId": { "type": "string", "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." } }, "id": "GoogleCloudAiplatformV1SuggestTrialsMetadata", "type": "object" }, "GoogleCloudAiplatformV1RagManagedDbConfigBasic": { "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": {}, "id": "GoogleCloudAiplatformV1RagManagedDbConfigBasic", "type": "object" }, "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessResult": { "type": "object", "id": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessResult", "description": "Spec for question answering helpfulness result.", "properties": { "score": { "format": "float", "type": "number", "readOnly": true, "description": "Output only. Question Answering Helpfulness score." }, "explanation": { "description": "Output only. Explanation for question answering helpfulness score.", "type": "string", "readOnly": true }, "confidence": { "type": "number", "format": "float", "readOnly": true, "description": "Output only. Confidence for question answering helpfulness score." } } }, "GenaiVertexV1VideoDelta": { "id": "GenaiVertexV1VideoDelta", "type": "object", "properties": { "data": { "type": "string", "format": "byte" }, "mimeType": { "enum": [ "TYPE_UNSPECIFIED", "TYPE_MP4", "TYPE_MPEG", "TYPE_MPG", "TYPE_MOV", "TYPE_AVI", "TYPE_X_FLV", "TYPE_WEBM", "TYPE_WMV", "TYPE_3GPP", "TYPE_JPEG2000" ], "enumDescriptions": [ "", "MP4 video format", "MPEG video format", "MPG video format", "MOV video format", "AVI video format", "FLV video format", "WebM video format", "WMV video format", "3GPP video format", "JPEG 2000 video format" ], "type": "string" }, "uri": { "type": "string" }, "resolution": { "enumDescriptions": [ "Default value. This value is unused.", "Low resolution.", "Medium resolution.", "High resolution.", "Ultra high resolution." ], "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "LOW", "MEDIUM", "HIGH", "ULTRA_HIGH" ], "description": "The resolution of the media.", "type": "string" } } }, "GoogleCloudAiplatformV1MultiSpeakerVoiceConfig": { "type": "object", "id": "GoogleCloudAiplatformV1MultiSpeakerVoiceConfig", "description": "Configuration for a multi-speaker text-to-speech request.", "properties": { "speakerVoiceConfigs": { "type": "array", "description": "Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.", "items": { "$ref": "GoogleCloudAiplatformV1SpeakerVoiceConfig" } } } }, "GenaiVertexV1GoogleMapsCallContentGoogleMapsCallArguments": { "type": "object", "id": "GenaiVertexV1GoogleMapsCallContentGoogleMapsCallArguments", "properties": { "queries": { "items": { "type": "string" }, "type": "array", "description": "The queries to be executed." } }, "description": "The arguments to pass to the Google Maps tool." }, "GoogleCloudAiplatformV1GenerateVideoResponse": { "properties": { "raiMediaFilteredCount": { "format": "int32", "description": "Returns if any videos were filtered due to RAI policies.", "type": "integer" }, "generatedSamples": { "type": "array", "description": "The cloud storage uris of the generated videos.", "deprecated": true, "items": { "type": "string" } }, "raiMediaFilteredReasons": { "type": "array", "items": { "type": "string" }, "description": "Returns rai failure reasons if any." }, "videos": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1GenerateVideoResponseVideo" }, "description": "List of video bytes or Cloud Storage URIs of the generated videos." } }, "description": "Generate video response.", "type": "object", "id": "GoogleCloudAiplatformV1GenerateVideoResponse" }, "GoogleCloudAiplatformV1SafetySpec": { "type": "object", "properties": { "version": { "description": "Optional. Which version to use for evaluation.", "format": "int32", "type": "integer" } }, "id": "GoogleCloudAiplatformV1SafetySpec", "description": "Spec for safety metric." }, "GoogleCloudAiplatformV1CancelPipelineJobRequest": { "description": "Request message for PipelineService.CancelPipelineJob.", "type": "object", "id": "GoogleCloudAiplatformV1CancelPipelineJobRequest", "properties": {} }, "GoogleCloudAiplatformV1ModelMonitoringStatsAnomalies": { "properties": { "objective": { "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." ], "type": "string", "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" ] }, "deployedModelId": { "description": "Deployed Model ID.", "type": "string" }, "anomalyCount": { "type": "integer", "format": "int32", "description": "Number of anomalies within all stats." }, "featureStats": { "type": "array", "description": "A list of historical Stats and Anomalies generated for all Features.", "items": { "$ref": "GoogleCloudAiplatformV1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies" } } }, "type": "object", "description": "Statistics and anomalies generated by Model Monitoring.", "id": "GoogleCloudAiplatformV1ModelMonitoringStatsAnomalies" }, "GoogleCloudAiplatformV1NasTrialDetail": { "description": "Represents a NasTrial details along with its parameters. If there is a corresponding train NasTrial, the train NasTrial is also returned.", "properties": { "name": { "description": "Output only. Resource name of the NasTrialDetail.", "type": "string", "readOnly": true }, "parameters": { "description": "The parameters for the NasJob NasTrial.", "type": "string" }, "trainTrial": { "$ref": "GoogleCloudAiplatformV1NasTrial", "description": "The train NasTrial corresponding to search_trial. Only populated if search_trial is used for training." }, "searchTrial": { "$ref": "GoogleCloudAiplatformV1NasTrial", "description": "The requested search NasTrial." } }, "type": "object", "id": "GoogleCloudAiplatformV1NasTrialDetail" }, "GoogleCloudAiplatformV1RagVectorDbConfig": { "description": "Config for the Vector DB to use for RAG.", "type": "object", "id": "GoogleCloudAiplatformV1RagVectorDbConfig", "properties": { "apiAuth": { "description": "Authentication config for the chosen Vector DB.", "$ref": "GoogleCloudAiplatformV1ApiAuth" }, "ragEmbeddingModelConfig": { "$ref": "GoogleCloudAiplatformV1RagEmbeddingModelConfig", "description": "Optional. Immutable. The embedding model config of the Vector DB." }, "pinecone": { "description": "The config for the Pinecone.", "$ref": "GoogleCloudAiplatformV1RagVectorDbConfigPinecone" }, "vertexVectorSearch": { "$ref": "GoogleCloudAiplatformV1RagVectorDbConfigVertexVectorSearch", "description": "The config for the Vertex Vector Search." }, "ragManagedDb": { "$ref": "GoogleCloudAiplatformV1RagVectorDbConfigRagManagedDb", "description": "The config for the RAG-managed Vector DB." } } }, "GoogleCloudAiplatformV1Metric": { "type": "object", "properties": { "exactMatchSpec": { "description": "Spec for exact match metric.", "$ref": "GoogleCloudAiplatformV1ExactMatchSpec" }, "pairwiseMetricSpec": { "$ref": "GoogleCloudAiplatformV1PairwiseMetricSpec", "description": "Spec for pairwise metric." }, "pointwiseMetricSpec": { "$ref": "GoogleCloudAiplatformV1PointwiseMetricSpec", "description": "Spec for pointwise metric." }, "llmBasedMetricSpec": { "description": "Spec for an LLM based metric.", "$ref": "GoogleCloudAiplatformV1LLMBasedMetricSpec" }, "customCodeExecutionSpec": { "$ref": "GoogleCloudAiplatformV1CustomCodeExecutionSpec", "description": "Spec for Custom Code Execution metric." }, "predefinedMetricSpec": { "description": "The spec for a pre-defined metric.", "$ref": "GoogleCloudAiplatformV1PredefinedMetricSpec" }, "rougeSpec": { "$ref": "GoogleCloudAiplatformV1RougeSpec", "description": "Spec for rouge metric." }, "metadata": { "$ref": "GoogleCloudAiplatformV1MetricMetadata", "description": "Optional. Metadata about the metric, used for visualization and organization." }, "bleuSpec": { "description": "Spec for bleu metric.", "$ref": "GoogleCloudAiplatformV1BleuSpec" }, "aggregationMetrics": { "items": { "enum": [ "AGGREGATION_METRIC_UNSPECIFIED", "AVERAGE", "MODE", "STANDARD_DEVIATION", "VARIANCE", "MINIMUM", "MAXIMUM", "MEDIAN", "PERCENTILE_P90", "PERCENTILE_P95", "PERCENTILE_P99" ], "type": "string", "enumDescriptions": [ "Unspecified aggregation metric.", "Average aggregation metric. Not supported for Pairwise metric.", "Mode aggregation metric.", "Standard deviation aggregation metric. Not supported for pairwise metric.", "Variance aggregation metric. Not supported for pairwise metric.", "Minimum aggregation metric. Not supported for pairwise metric.", "Maximum aggregation metric. Not supported for pairwise metric.", "Median aggregation metric. Not supported for pairwise metric.", "90th percentile aggregation metric. Not supported for pairwise metric.", "95th percentile aggregation metric. Not supported for pairwise metric.", "99th percentile aggregation metric. Not supported for pairwise metric." ] }, "type": "array", "description": "Optional. The aggregation metrics to use." }, "computationBasedMetricSpec": { "description": "Spec for a computation based metric.", "$ref": "GoogleCloudAiplatformV1ComputationBasedMetricSpec" } }, "description": "The metric used for running evaluations.", "id": "GoogleCloudAiplatformV1Metric" }, "GoogleTypeInterval": { "id": "GoogleTypeInterval", "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": { "description": "Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end.", "format": "google-datetime", "type": "string" } }, "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.", "type": "object" }, "GenaiVertexV1AudioDelta": { "type": "object", "id": "GenaiVertexV1AudioDelta", "properties": { "channels": { "format": "int32", "description": "The number of audio channels.", "type": "integer" }, "mimeType": { "enumDescriptions": [ "", "WAV audio format", "MP3 audio format", "AIFF audio format", "AAC audio format", "OGG audio format", "FLAC audio format", "MPEG audio format", "M4A audio format", "L16 audio format", "OPUS audio format", "ALAW audio format", "MULAW audio format", "WEBM audio format" ], "type": "string", "enum": [ "TYPE_UNSPECIFIED", "TYPE_WAV", "TYPE_MP3", "TYPE_AIFF", "TYPE_AAC", "TYPE_OGG", "TYPE_FLAC", "TYPE_MPEG", "TYPE_M4A", "TYPE_L16", "TYPE_OPUS", "TYPE_ALAW", "TYPE_MULAW", "TYPE_WEBM" ] }, "sampleRate": { "type": "integer", "format": "int32", "description": "The sample rate of the audio." }, "uri": { "type": "string" }, "data": { "format": "byte", "type": "string" } } }, "GoogleCloudAiplatformV1PublisherModelCallToActionDeployGke": { "id": "GoogleCloudAiplatformV1PublisherModelCallToActionDeployGke", "description": "Configurations for PublisherModel GKE deployment", "properties": { "gkeYamlConfigs": { "items": { "type": "string" }, "description": "Optional. GKE deployment configuration in yaml format.", "type": "array" } }, "type": "object" }, "GoogleCloudAiplatformV1GenerateContentRequest": { "description": "Request message for [PredictionService.GenerateContent].", "properties": { "modelArmorConfig": { "$ref": "GoogleCloudAiplatformV1ModelArmorConfig", "description": "Optional. Settings for prompt and response sanitization using the Model Armor service. If supplied, safety_settings must not be supplied." }, "cachedContent": { "description": "Optional. The name of the cached content used as context to serve the prediction. Note: only used in explicit caching, where users can have control over caching (e.g. what content to cache) and enjoy guaranteed cost savings. Format: `projects/{project}/locations/{location}/cachedContents/{cachedContent}`", "type": "string" }, "systemInstruction": { "description": "Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.", "$ref": "GoogleCloudAiplatformV1Content" }, "generationConfig": { "$ref": "GoogleCloudAiplatformV1GenerationConfig", "description": "Optional. Generation config." }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter." }, "contents": { "type": "array", "description": "Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request.", "items": { "$ref": "GoogleCloudAiplatformV1Content" } }, "toolConfig": { "description": "Optional. Tool config. This config is shared for all tools provided in the request.", "$ref": "GoogleCloudAiplatformV1ToolConfig" }, "tools": { "type": "array", "description": "Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model.", "items": { "$ref": "GoogleCloudAiplatformV1Tool" } }, "safetySettings": { "type": "array", "description": "Optional. Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates.", "items": { "$ref": "GoogleCloudAiplatformV1SafetySetting" } } }, "id": "GoogleCloudAiplatformV1GenerateContentRequest", "type": "object" }, "GoogleCloudAiplatformV1SchemaPromptSpecAppBuilderDataLinkedResource": { "type": "object", "description": "A linked resource attached to the application by the user.", "id": "GoogleCloudAiplatformV1SchemaPromptSpecAppBuilderDataLinkedResource", "properties": { "displayName": { "type": "string", "description": "A user-friendly name for the data source shown in the UI." }, "type": { "description": "The type of the linked resource. e.g., \"SAVED_PROMPT\", \"AI_AGENT\" This string corresponds to the name of the LinkedResourceType enum member. See: google3/cloud/console/web/ai/platform/llm/prompts/build/services/specs_repository_service/linked_resources/linked_resource.ts", "type": "string" }, "name": { "description": "The unique resource name of the data source. The format is determined by the 'type' field. For type \"SAVED_PROMPT\": projects/{project}/locations/{location}/datasets/{dataset} For type \"AI_AGENT\": projects/{project}/locations/{location}/agents/{agent}", "type": "string" } } }, "GoogleCloudAiplatformV1ListModelsResponse": { "id": "GoogleCloudAiplatformV1ListModelsResponse", "type": "object", "properties": { "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListModelsRequest.page_token to obtain that page.", "type": "string" }, "models": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Model" }, "description": "List of Models in the requested page." } }, "description": "Response message for ModelService.ListModels" }, "GoogleCloudAiplatformV1ToolNameMatchInstance": { "type": "object", "properties": { "prediction": { "type": "string", "description": "Required. Output of the evaluated model." }, "reference": { "description": "Required. Ground truth used to compare against the prediction.", "type": "string" } }, "description": "Spec for tool name match instance.", "id": "GoogleCloudAiplatformV1ToolNameMatchInstance" }, "GoogleCloudAiplatformV1FeatureValueDestination": { "type": "object", "description": "A destination location for Feature values and format.", "id": "GoogleCloudAiplatformV1FeatureValueDestination", "properties": { "bigqueryDestination": { "$ref": "GoogleCloudAiplatformV1BigQueryDestination", "description": "Output in BigQuery format. BigQueryDestination.output_uri in FeatureValueDestination.bigquery_destination must refer to a table." }, "csvDestination": { "$ref": "GoogleCloudAiplatformV1CsvDestination", "description": "Output in CSV format. Array Feature value types are not allowed in CSV format." }, "tfrecordDestination": { "$ref": "GoogleCloudAiplatformV1TFRecordDestination", "description": "Output in TFRecord format. Below are the mapping from Feature value type in Featurestore to Feature value type in TFRecord: Value type in Featurestore | Value type in TFRecord DOUBLE, DOUBLE_ARRAY | FLOAT_LIST INT64, INT64_ARRAY | INT64_LIST STRING, STRING_ARRAY, BYTES | BYTES_LIST true -\u003e byte_string(\"true\"), false -\u003e byte_string(\"false\") BOOL, BOOL_ARRAY (true, false) | BYTES_LIST" } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation": { "type": "object", "properties": { "columnName": { "type": "string" }, "invalidValuesAllowed": { "type": "boolean", "description": "If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data." } }, "description": "Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * A boolean value that indicates whether the value is valid.", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation" }, "GenaiVertexV1StepStart": { "properties": { "step": { "$ref": "GenaiVertexV1Step" }, "index": { "type": "integer", "format": "int32" } }, "type": "object", "id": "GenaiVertexV1StepStart" }, "GoogleCloudAiplatformV1SchemaImageClassificationAnnotation": { "properties": { "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" }, "displayName": { "type": "string", "description": "The display name of the AnnotationSpec that this Annotation pertains to." } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaImageClassificationAnnotation", "description": "Annotation details specific to image classification." }, "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchInstance": { "id": "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchInstance", "properties": { "predictedTrajectory": { "$ref": "GoogleCloudAiplatformV1Trajectory", "description": "Required. Spec for predicted tool call trajectory." }, "referenceTrajectory": { "description": "Required. Spec for reference tool call trajectory.", "$ref": "GoogleCloudAiplatformV1Trajectory" } }, "description": "Spec for TrajectoryAnyOrderMatch instance.", "type": "object" }, "GoogleCloudAiplatformV1RemoveContextChildrenRequest": { "id": "GoogleCloudAiplatformV1RemoveContextChildrenRequest", "properties": { "childContexts": { "type": "array", "description": "The resource names of the child Contexts.", "items": { "type": "string" } } }, "type": "object", "description": "Request message for MetadataService.DeleteContextChildrenRequest." }, "GenaiVertexV1GoogleSearchResultStepGoogleSearchResultItem": { "properties": { "searchSuggestions": { "type": "string", "description": "Web content snippet that can be embedded in a web page or an app webview." } }, "id": "GenaiVertexV1GoogleSearchResultStepGoogleSearchResultItem", "description": "The result of the Google Search.", "type": "object" }, "GoogleCloudAiplatformV1PredefinedMetricSpec": { "description": "The spec for a pre-defined metric.", "properties": { "metricSpecName": { "type": "string", "description": "Required. The name of a pre-defined metric, such as \"instruction_following_v1\" or \"text_quality_v1\"." }, "metricSpecParameters": { "type": "object", "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "description": "Optional. The parameters needed to run the pre-defined metric." } }, "id": "GoogleCloudAiplatformV1PredefinedMetricSpec", "type": "object" }, "GoogleCloudAiplatformV1BigQueryRequestSetSamplingConfig": { "id": "GoogleCloudAiplatformV1BigQueryRequestSetSamplingConfig", "type": "object", "properties": { "samplingDuration": { "type": "string", "format": "google-duration", "description": "Optional. How long to wait before sampling data from the BigQuery table. If not specified, defaults to 0." }, "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" }, "samplingMethod": { "enum": [ "SAMPLING_METHOD_UNSPECIFIED", "RANDOM" ], "type": "string", "enumDescriptions": [ "Unspecified sampling method.", "Random sampling." ], "description": "Optional. The sampling method to use." } }, "description": "The sampling config." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation", "type": "object", "properties": { "timeFormat": { "type": "string", "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)" }, "columnName": { "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." }, "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecAgentConfigSource": { "properties": { "adkConfig": { "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecAgentConfigSourceAdkConfig", "description": "Required. The ADK configuration." }, "inlineSource": { "description": "Optional. Any additional files needed to interpret the config. If a `requirements.txt` file is present in the `inline_source`, the corresponding packages will be installed. If no `requirements.txt` file is present in `inline_source`, then the latest version of `google-adk` will be installed for interpreting the ADK config.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecInlineSource" } }, "description": "Specification for the deploying from agent config.", "type": "object", "id": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecAgentConfigSource" }, "GoogleCloudAiplatformV1SupervisedTuningDatasetDistributionDatasetBucket": { "description": "Dataset bucket used to create a histogram for the distribution given a population of values.", "properties": { "left": { "description": "Output only. Left bound of the bucket.", "type": "number", "readOnly": true, "format": "double" }, "count": { "description": "Output only. Number of values in the bucket.", "readOnly": true, "format": "double", "type": "number" }, "right": { "type": "number", "readOnly": true, "format": "double", "description": "Output only. Right bound of the bucket." } }, "type": "object", "id": "GoogleCloudAiplatformV1SupervisedTuningDatasetDistributionDatasetBucket" }, "GenaiVertexV1CodeMenderAgentConfigFileContent": { "id": "GenaiVertexV1CodeMenderAgentConfigFileContent", "type": "object", "properties": { "path": { "description": "The relative path of the file from the project root.", "type": "string" }, "content": { "type": "string", "description": "The UTF-8 encoded text content of the file." } }, "description": "Content of a single file in the codebase." }, "GoogleCloudAiplatformV1LogprobsResult": { "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": { "items": { "$ref": "GoogleCloudAiplatformV1LogprobsResultTopCandidates" }, "type": "array", "description": "A list of the top candidate tokens at each decoding step. The length of this list is equal to the total number of decoding steps." }, "chosenCandidates": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1LogprobsResultCandidate" }, "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": "GoogleCloudAiplatformV1LogprobsResult", "type": "object" }, "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolygonAnnotation": { "description": "Represents a polygon in image.", "id": "GoogleCloudAiplatformV1SchemaImageSegmentationAnnotationPolygonAnnotation", "properties": { "displayName": { "type": "string", "description": "The display name of the AnnotationSpec that this Annotation pertains to." }, "vertexes": { "type": "array", "description": "The vertexes are connected one by one and the last vertex is connected to the first one to represent a polygon.", "items": { "$ref": "GoogleCloudAiplatformV1SchemaVertex" } }, "annotationSpecId": { "description": "The resource Id of the AnnotationSpec that this Annotation pertains to.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1BatchPredictionJobInstanceConfig": { "description": "Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.", "properties": { "keyField": { "type": "string", "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." }, "instanceType": { "type": "string", "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." }, "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" } }, "excludedFields": { "type": "array", "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.", "items": { "type": "string" } } }, "id": "GoogleCloudAiplatformV1BatchPredictionJobInstanceConfig", "type": "object" }, "GoogleCloudAiplatformV1EvaluationParserConfigCustomCodeParserConfig": { "description": "Configuration for parsing the LLM response using custom code.", "id": "GoogleCloudAiplatformV1EvaluationParserConfigCustomCodeParserConfig", "type": "object", "properties": { "parsingFunction": { "type": "string", "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" } } }, "GoogleCloudAiplatformV1PipelineJob": { "properties": { "scheduleName": { "type": "string", "description": "Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.", "readOnly": true }, "endTime": { "type": "string", "readOnly": true, "description": "Output only. Pipeline end time.", "format": "google-datetime" }, "createTime": { "description": "Output only. Pipeline creation time.", "readOnly": true, "format": "google-datetime", "type": "string" }, "name": { "readOnly": true, "description": "Output only. The resource name of the PipelineJob.", "type": "string" }, "serviceAccount": { "type": "string", "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." }, "error": { "readOnly": true, "description": "Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.", "$ref": "GoogleRpcStatus" }, "labels": { "additionalProperties": { "type": "string" }, "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" }, "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" }, "startTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Pipeline start time." }, "templateMetadata": { "$ref": "GoogleCloudAiplatformV1PipelineTemplateMetadata", "readOnly": true, "description": "Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry." }, "reservedIpRanges": { "items": { "type": "string" }, "description": "A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].", "type": "array" }, "network": { "type": "string", "description": "The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network." }, "pipelineSpec": { "type": "object", "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "description": "A compiled definition of a pipeline, represented as a `JSON` object. Defines the structure of the pipeline, including its components, tasks, and parameters. This specification is generated by compiling a pipeline function defined in `Python` using the `Kubeflow Pipelines SDK`." }, "pscInterfaceConfig": { "description": "Optional. Configuration for PSC-I for PipelineJob.", "$ref": "GoogleCloudAiplatformV1PscInterfaceConfig" }, "encryptionSpec": { "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.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "templateUri": { "description": "A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.", "type": "string" }, "state": { "type": "string", "enumDescriptions": [ "The pipeline state is unspecified.", "The pipeline has been created or resumed, and processing has not yet begun.", "The service is preparing to run the pipeline.", "The pipeline is in progress.", "The pipeline completed successfully.", "The pipeline failed.", "The pipeline is being cancelled. From this state, the pipeline may only go to either PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED.", "The pipeline has been cancelled.", "The pipeline has been stopped, and can be resumed." ], "enum": [ "PIPELINE_STATE_UNSPECIFIED", "PIPELINE_STATE_QUEUED", "PIPELINE_STATE_PENDING", "PIPELINE_STATE_RUNNING", "PIPELINE_STATE_SUCCEEDED", "PIPELINE_STATE_FAILED", "PIPELINE_STATE_CANCELLING", "PIPELINE_STATE_CANCELLED", "PIPELINE_STATE_PAUSED" ], "description": "Output only. The detailed state of the job.", "readOnly": true }, "preflightValidations": { "description": "Optional. Whether to do component level validations before job creation.", "type": "boolean" }, "updateTime": { "readOnly": true, "type": "string", "description": "Output only. Timestamp when this PipelineJob was most recently updated.", "format": "google-datetime" }, "runtimeConfig": { "$ref": "GoogleCloudAiplatformV1PipelineJobRuntimeConfig", "description": "Runtime config of the pipeline." }, "jobDetail": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1PipelineJobDetail", "description": "Output only. The details of pipeline run. Not available in the list view." } }, "id": "GoogleCloudAiplatformV1PipelineJob", "description": "An instance of a machine learning PipelineJob.", "type": "object" }, "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataTools": { "id": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentDataTools", "type": "object", "properties": { "tool": { "items": { "$ref": "GoogleCloudAiplatformV1Tool" }, "type": "array", "deprecated": true, "description": "Optional. List of tools: each tool can have multiple function declarations." } }, "description": "Deprecated: Use `agent_eval_data` instead. Represents a list of tools for an agent." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig": { "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.", "properties": { "strideLength": { "description": "Stride length used to generate input examples. Within one time series, every {$STRIDE_LENGTH} rows will be used to generate a sliding window.", "format": "int64", "type": "string" }, "maxCount": { "type": "string", "description": "Maximum number of windows that should be generated across all time series.", "format": "int64" }, "column": { "description": "Name of the column that should be used to generate sliding windows. The column should contain either booleans or string booleans; if the value of the row is True, generate a sliding window with the horizon starting at that row. The column will not be used as a feature in training.", "type": "string" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig", "type": "object" }, "GoogleCloudAiplatformV1SummarizationHelpfulnessSpec": { "id": "GoogleCloudAiplatformV1SummarizationHelpfulnessSpec", "properties": { "useReference": { "type": "boolean", "description": "Optional. Whether to use instance.reference to compute summarization helpfulness." }, "version": { "description": "Optional. Which version to use for evaluation.", "format": "int32", "type": "integer" } }, "type": "object", "description": "Spec for summarization helpfulness score metric." }, "GoogleCloudAiplatformV1RubricBasedInstructionFollowingInput": { "description": "Instance and metric spec for RubricBasedInstructionFollowing metric.", "properties": { "instance": { "$ref": "GoogleCloudAiplatformV1RubricBasedInstructionFollowingInstance", "description": "Required. Instance for RubricBasedInstructionFollowing metric." }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1RubricBasedInstructionFollowingSpec", "description": "Required. Spec for RubricBasedInstructionFollowing metric." } }, "type": "object", "id": "GoogleCloudAiplatformV1RubricBasedInstructionFollowingInput" }, "GoogleCloudAiplatformV1ToolNameMatchMetricValue": { "properties": { "score": { "type": "number", "description": "Output only. Tool name match score.", "format": "float", "readOnly": true } }, "description": "Tool name match metric value for an instance.", "id": "GoogleCloudAiplatformV1ToolNameMatchMetricValue", "type": "object" }, "GoogleCloudAiplatformV1FunctionCall": { "id": "GoogleCloudAiplatformV1FunctionCall", "properties": { "willContinue": { "type": "boolean", "description": "Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow." }, "id": { "description": "Optional. The unique id of the function call. If populated, the client to execute the `function_call` and return the response with the matching `id`.", "type": "string" }, "name": { "description": "Optional. The name of the function to call. Matches FunctionDeclaration.name.", "type": "string" }, "args": { "type": "object", "description": "Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "partialArgs": { "type": "array", "description": "Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.", "items": { "$ref": "GoogleCloudAiplatformV1PartialArg" } } }, "type": "object", "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." }, "GoogleCloudAiplatformV1CorroborateContentRequestParameters": { "properties": { "citationThreshold": { "description": "Optional. Only return claims with citation score larger than the threshold.", "format": "double", "type": "number" } }, "description": "Parameters that can be overrided per request.", "id": "GoogleCloudAiplatformV1CorroborateContentRequestParameters", "type": "object" }, "GoogleCloudAiplatformV1SandboxEnvironmentTemplateCustomContainerEnvironment": { "type": "object", "description": "The customized sandbox runtime environment for BYOC.", "id": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateCustomContainerEnvironment", "properties": { "ports": { "description": "Ports to expose from the container.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateNetworkPort" } }, "customContainerSpec": { "description": "The specification of the custom container environment.", "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateCustomContainerSpec" }, "resources": { "description": "Resource requests and limits for the container.", "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateResourceRequirements" } } }, "GoogleCloudAiplatformV1ResumeSandboxEnvironmentRequest": { "id": "GoogleCloudAiplatformV1ResumeSandboxEnvironmentRequest", "type": "object", "properties": {}, "description": "Request message for SandboxEnvironmentService.ResumeSandboxEnvironment." }, "GoogleCloudAiplatformV1PurgeMemoriesRequest": { "description": "Request message for MemoryBankService.PurgeMemories.", "id": "GoogleCloudAiplatformV1PurgeMemoriesRequest", "properties": { "filterGroups": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1MemoryConjunctionFilter" }, "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\"))`." }, "force": { "description": "Optional. If true, the memories will actually be purged. If false, the purge request will be validated but not executed.", "type": "boolean" }, "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" } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics": { "description": "Metrics for a single confidence threshold.", "properties": { "recall": { "format": "float", "description": "Recall under the given confidence threshold.", "type": "number" }, "confidenceThreshold": { "description": "The confidence threshold value used to compute the metrics.", "format": "float", "type": "number" }, "precision": { "description": "Precision under the given confidence threshold.", "format": "float", "type": "number" }, "f1Score": { "description": "The harmonic mean of recall and precision.", "format": "float", "type": "number" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation": { "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" }, "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.", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation" }, "GoogleCloudAiplatformV1PurgeContextsRequest": { "type": "object", "properties": { "force": { "type": "boolean", "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." }, "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" } }, "id": "GoogleCloudAiplatformV1PurgeContextsRequest", "description": "Request message for MetadataService.PurgeContexts." }, "GoogleCloudAiplatformV1ExportDataRequest": { "id": "GoogleCloudAiplatformV1ExportDataRequest", "description": "Request message for DatasetService.ExportData.", "properties": { "exportConfig": { "$ref": "GoogleCloudAiplatformV1ExportDataConfig", "description": "Required. The desired output location." } }, "type": "object" }, "GoogleCloudAiplatformV1Endpoint": { "id": "GoogleCloudAiplatformV1Endpoint", "type": "object", "properties": { "description": { "description": "The description of the Endpoint.", "type": "string" }, "modelDeploymentMonitoringJob": { "type": "string", "readOnly": true, "description": "Output only. Resource name of the Model Monitoring job associated with this Endpoint if monitoring is enabled by JobService.CreateModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`" }, "predictRequestResponseLoggingConfig": { "description": "Configures the request-response logging for online prediction.", "$ref": "GoogleCloudAiplatformV1PredictRequestResponseLoggingConfig" }, "gdcConfig": { "$ref": "GoogleCloudAiplatformV1GdcConfig", "description": "Configures the Google Distributed Cloud (GDC) environment for online prediction. Only set this field when the Endpoint is to be deployed in a GDC environment." }, "dedicatedEndpointEnabled": { "description": "If true, the endpoint will be exposed through a dedicated DNS [Endpoint.dedicated_endpoint_dns]. Your request to the dedicated DNS will be isolated from other users' traffic and will have better performance and reliability. Note: Once you enabled dedicated endpoint, you won't be able to send request to the shared DNS {region}-aiplatform.googleapis.com. The limitation will be removed soon.", "type": "boolean" }, "dedicatedEndpointDns": { "type": "string", "readOnly": true, "description": "Output only. DNS of the dedicated endpoint. Will only be populated if dedicated_endpoint_enabled is true. Depending on the features enabled, uid might be a random number or a string. For example, if fast_tryout is enabled, uid will be fasttryout. Format: `https://{endpoint_id}.{region}-{uid}.prediction.vertexai.goog`." }, "updateTime": { "format": "google-datetime", "description": "Output only. Timestamp when this Endpoint was last updated.", "type": "string", "readOnly": true }, "displayName": { "description": "Required. The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "etag": { "description": "Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "name": { "description": "Identifier. The resource name of the Endpoint.", "type": "string" }, "genAiAdvancedFeaturesConfig": { "$ref": "GoogleCloudAiplatformV1GenAiAdvancedFeaturesConfig", "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." }, "privateServiceConnectConfig": { "description": "Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive.", "$ref": "GoogleCloudAiplatformV1PrivateServiceConnectConfig" }, "deployedModels": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1DeployedModel" }, "description": "Output only. The models deployed in this Endpoint. To add or remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel respectively.", "readOnly": true }, "clientConnectionConfig": { "$ref": "GoogleCloudAiplatformV1ClientConnectionConfig", "description": "Configurations that are applied to the endpoint for online prediction." }, "satisfiesPzs": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1EncryptionSpec", "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." }, "labels": { "additionalProperties": { "type": "string" }, "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" }, "createTime": { "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when this Endpoint was created.", "readOnly": true }, "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" }, "satisfiesPzi": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "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" }, "trafficSplit": { "additionalProperties": { "type": "integer", "format": "int32" }, "type": "object", "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." } }, "description": "Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations." }, "GoogleCloudAiplatformV1SummarizationVerbosityResult": { "properties": { "explanation": { "readOnly": true, "description": "Output only. Explanation for summarization verbosity score.", "type": "string" }, "confidence": { "type": "number", "format": "float", "readOnly": true, "description": "Output only. Confidence for summarization verbosity score." }, "score": { "type": "number", "format": "float", "readOnly": true, "description": "Output only. Summarization Verbosity score." } }, "description": "Spec for summarization verbosity result.", "id": "GoogleCloudAiplatformV1SummarizationVerbosityResult", "type": "object" }, "GoogleCloudAiplatformV1SchemaPredictionResult": { "description": "Represents a line of JSONL in the batch prediction output file.", "properties": { "key": { "description": "Optional user-provided key from the input instance.", "type": "string" }, "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" }, "instance": { "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.", "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "type": "object" }, "error": { "description": "The error result. Do not set prediction if this is set.", "$ref": "GoogleCloudAiplatformV1SchemaPredictionResultError" } }, "id": "GoogleCloudAiplatformV1SchemaPredictionResult", "type": "object" }, "GoogleCloudAiplatformV1BatchMigrateResourcesOperationMetadata": { "description": "Runtime operation information for MigrationService.BatchMigrateResources.", "type": "object", "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" }, "partialResults": { "description": "Partial results that reflect the latest migration operation progress.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1BatchMigrateResourcesOperationMetadataPartialResult" } } }, "id": "GoogleCloudAiplatformV1BatchMigrateResourcesOperationMetadata" }, "GoogleCloudAiplatformV1GenerateSyntheticDataRequest": { "type": "object", "id": "GoogleCloudAiplatformV1GenerateSyntheticDataRequest", "description": "Request message for DataFoundryService.GenerateSyntheticData. It contains the settings and information needed to generate synthetic data.", "properties": { "outputFieldSpecs": { "description": "Required. Defines the schema of each synthetic example to be generated, defined by a list of fields.", "items": { "$ref": "GoogleCloudAiplatformV1OutputFieldSpec" }, "type": "array" }, "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." }, "taskDescription": { "$ref": "GoogleCloudAiplatformV1TaskDescriptionStrategy", "description": "Generates synthetic data based on a high-level description of the task or data you want." }, "examples": { "items": { "$ref": "GoogleCloudAiplatformV1SyntheticExample" }, "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.", "type": "array" } } }, "GoogleCloudAiplatformV1RetrievalConfig": { "id": "GoogleCloudAiplatformV1RetrievalConfig", "description": "Retrieval config.", "type": "object", "properties": { "languageCode": { "description": "The language code of the user.", "type": "string" }, "latLng": { "description": "The location of the user.", "$ref": "GoogleTypeLatLng" } } }, "GoogleCloudAiplatformV1BatchPredictionJob": { "id": "GoogleCloudAiplatformV1BatchPredictionJob", "description": "A job that uses a Model to produce predictions on multiple input instances. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.", "type": "object", "properties": { "generateExplanation": { "description": "Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.", "type": "boolean" }, "completionStats": { "$ref": "GoogleCloudAiplatformV1CompletionStats", "description": "Output only. Statistics on completed and failed prediction instances.", "readOnly": true }, "state": { "description": "Output only. The detailed state of the job.", "readOnly": true, "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." ] }, "satisfiesPzs": { "readOnly": true, "description": "Output only. Reserved for future use.", "type": "boolean" }, "serviceAccount": { "type": "string", "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." }, "endTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Time when the BatchPredictionJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`." }, "dedicatedResources": { "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.", "$ref": "GoogleCloudAiplatformV1BatchDedicatedResources" }, "outputConfig": { "description": "Required. The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.", "$ref": "GoogleCloudAiplatformV1BatchPredictionJobOutputConfig" }, "displayName": { "description": "Required. The user-defined name of this BatchPredictionJob.", "type": "string" }, "error": { "readOnly": true, "$ref": "GoogleRpcStatus", "description": "Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED." }, "inputConfig": { "description": "Required. Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.", "$ref": "GoogleCloudAiplatformV1BatchPredictionJobInputConfig" }, "createTime": { "type": "string", "format": "google-datetime", "readOnly": true, "description": "Output only. Time when the BatchPredictionJob was created." }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1EncryptionSpec", "description": "Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key." }, "resourcesConsumed": { "description": "Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models.", "$ref": "GoogleCloudAiplatformV1ResourcesConsumed", "readOnly": true }, "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).", "$ref": "GoogleCloudAiplatformV1ManualBatchTuningParameters" }, "modelVersionId": { "readOnly": true, "description": "Output only. The version ID of the Model that produces the predictions via this job.", "type": "string" }, "unmanagedContainerModel": { "$ref": "GoogleCloudAiplatformV1UnmanagedContainerModel", "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." }, "satisfiesPzi": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "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" }, "updateTime": { "type": "string", "description": "Output only. Time when the BatchPredictionJob was most recently updated.", "readOnly": true, "format": "google-datetime" }, "modelParameters": { "type": "any", "description": "The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri." }, "outputInfo": { "description": "Output only. Information further describing the output of this job.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1BatchPredictionJobOutputInfo" }, "name": { "type": "string", "readOnly": true, "description": "Output only. Resource name of the BatchPredictionJob." }, "startTime": { "readOnly": true, "description": "Output only. Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.", "format": "google-datetime", "type": "string" }, "model": { "description": "The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model, unmanaged_container_model, or endpoint must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "type": "string" }, "instanceConfig": { "$ref": "GoogleCloudAiplatformV1BatchPredictionJobInstanceConfig", "description": "Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model." }, "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.", "additionalProperties": { "type": "string" }, "type": "object" }, "explanationSpec": { "$ref": "GoogleCloudAiplatformV1ExplanationSpec", "description": "Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited." }, "partialFailures": { "items": { "$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.", "type": "array" } } }, "GoogleCloudAiplatformV1SpeechConfig": { "description": "Configuration for speech generation.", "properties": { "languageCode": { "description": "Optional. The language code (ISO 639-1) for the speech synthesis.", "type": "string" }, "multiSpeakerVoiceConfig": { "description": "The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.", "$ref": "GoogleCloudAiplatformV1MultiSpeakerVoiceConfig" }, "voiceConfig": { "$ref": "GoogleCloudAiplatformV1VoiceConfig", "description": "The configuration for the voice to use." } }, "id": "GoogleCloudAiplatformV1SpeechConfig", "type": "object" }, "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchSpec": { "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchSpec", "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." }, "GoogleCloudAiplatformV1Feature": { "type": "object", "id": "GoogleCloudAiplatformV1Feature", "properties": { "updateTime": { "type": "string", "readOnly": true, "format": "google-datetime", "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated." }, "description": { "description": "Description of the Feature.", "type": "string" }, "monitoringStatsAnomalies": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1FeatureMonitoringStatsAnomaly" }, "description": "Output only. Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.", "readOnly": true }, "valueType": { "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" ], "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." ], "type": "string" }, "etag": { "type": "string", "description": "Used to perform a consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." }, "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 }, "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" }, "pointOfContact": { "description": "Entity responsible for maintaining this feature. Can be comma separated list of email addresses or URIs.", "type": "string" }, "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" }, "versionColumnName": { "type": "string", "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." }, "labels": { "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.", "additionalProperties": { "type": "string" }, "type": "object" } }, "description": "Feature Metadata information. For example, color is a feature that describes an apple." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoClassification": { "description": "A TrainingJob that trains and uploads an AutoML Video Classification Model.", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoClassification" }, "GoogleCloudAiplatformV1ToolComputerUse": { "description": "A tool that enables the model to interact directly with a computer environment.", "properties": { "excludedPredefinedFunctions": { "description": "Optional. A list of predefined functions to explicitly exclude from the model call. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included. Excluding functions allows for a more restricted action space or custom definitions for predefined functions.", "items": { "type": "string" }, "type": "array" }, "environment": { "enum": [ "ENVIRONMENT_UNSPECIFIED", "ENVIRONMENT_BROWSER", "ENVIRONMENT_MOBILE", "ENVIRONMENT_DESKTOP" ], "description": "Required. The target environment where the computer use tool operates.", "type": "string", "enumDescriptions": [ "The environment is unspecified.", "The tool operates in a web browser.", "The tool operates in a mobile environment.", "The tool operates in a desktop environment." ] }, "disabledSafetyPolicies": { "items": { "enumDescriptions": [ "The safety policy is unspecified.", "Policy that restricts financial transactions.", "Policy that restricts modification of sensitive data.", "Policy that restricts the use of communication tools.", "Policy that restricts the creation of accounts.", "Policy that restricts general data modification.", "Policy that restricts user consent management.", "Policy that restricts interaction with legal terms and agreements." ], "enum": [ "SAFETY_POLICY_UNSPECIFIED", "FINANCIAL_TRANSACTIONS", "SENSITIVE_DATA_MODIFICATION", "COMMUNICATION_TOOL", "ACCOUNT_CREATION", "DATA_MODIFICATION", "USER_CONSENT_MANAGEMENT", "LEGAL_TERMS_AND_AGREEMENTS" ], "type": "string" }, "type": "array", "description": "Optional. A list of safety policies to disable for the computer use tool." }, "enablePromptInjectionDetection": { "description": "Optional. Whether to enable the prompt injection detection check on the computer use request.", "type": "boolean" } }, "type": "object", "id": "GoogleCloudAiplatformV1ToolComputerUse" }, "GoogleCloudAiplatformV1SchemaPredictInstanceImageObjectDetectionPredictionInstance": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaPredictInstanceImageObjectDetectionPredictionInstance", "description": "Prediction input format for Image Object Detection.", "properties": { "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" }, "content": { "description": "The image bytes or Cloud Storage URI to make the prediction on.", "type": "string" } } }, "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob": { "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.", "properties": { "error": { "readOnly": true, "description": "Output only. Only populated when the job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.", "$ref": "GoogleRpcStatus" }, "bigqueryTables": { "description": "Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum: 1. Training data logging predict request/response 2. Serving data logging predict request/response", "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTable" }, "type": "array" }, "modelMonitoringAlertConfig": { "$ref": "GoogleCloudAiplatformV1ModelMonitoringAlertConfig", "description": "Alert config for model monitoring." }, "loggingSamplingStrategy": { "description": "Required. Sample Strategy for logging.", "$ref": "GoogleCloudAiplatformV1SamplingStrategy" }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1EncryptionSpec", "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." }, "satisfiesPzs": { "type": "boolean", "readOnly": true, "description": "Output only. Reserved for future use." }, "updateTime": { "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.", "readOnly": true }, "state": { "readOnly": true, "type": "string", "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" ], "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." ], "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'." }, "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" }, "modelDeploymentMonitoringScheduleConfig": { "description": "Required. Schedule config for running the monitoring job.", "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig" }, "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.", "$ref": "GoogleCloudAiplatformV1GcsDestination" }, "latestMonitoringPipelineMetadata": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata", "description": "Output only. Latest triggered monitoring pipeline metadata." }, "nextScheduleTime": { "type": "string", "readOnly": true, "description": "Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.", "format": "google-datetime" }, "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.", "additionalProperties": { "type": "string" }, "type": "object" }, "name": { "type": "string", "description": "Output only. Resource name of a ModelDeploymentMonitoringJob.", "readOnly": true }, "createTime": { "description": "Output only. Timestamp when this ModelDeploymentMonitoringJob was created.", "type": "string", "format": "google-datetime", "readOnly": true }, "scheduleState": { "readOnly": true, "type": "string", "enum": [ "MONITORING_SCHEDULE_STATE_UNSPECIFIED", "PENDING", "OFFLINE", "RUNNING" ], "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." ], "description": "Output only. Schedule state when the monitoring job is in Running state." }, "logTtl": { "format": "google-duration", "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.", "type": "string" }, "satisfiesPzi": { "description": "Output only. Reserved for future use.", "type": "boolean", "readOnly": true }, "modelDeploymentMonitoringObjectiveConfigs": { "type": "array", "description": "Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.", "items": { "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfig" } }, "enableMonitoringPipelineLogs": { "type": "boolean", "description": "If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging#pricing)." }, "endpoint": { "type": "string", "description": "Required. Endpoint resource name. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" }, "displayName": { "description": "Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.", "type": "string" }, "predictInstanceSchemaUri": { "description": "YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.", "type": "string" } }, "id": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob", "type": "object" }, "GoogleCloudAiplatformV1PrebuiltVoiceConfig": { "id": "GoogleCloudAiplatformV1PrebuiltVoiceConfig", "type": "object", "properties": { "voiceName": { "type": "string", "description": "The name of the prebuilt voice to use." } }, "description": "Configuration for a prebuilt voice." }, "GoogleCloudAiplatformV1AgentData": { "description": "Represents data specific to multi-turn agent evaluations.", "properties": { "turns": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ConversationTurn" }, "description": "Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -\u003e Agent Response)." }, "agents": { "additionalProperties": { "$ref": "GoogleCloudAiplatformV1AgentConfig" }, "type": "object", "description": "Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent." } }, "type": "object", "id": "GoogleCloudAiplatformV1AgentData" }, "GoogleCloudAiplatformV1UpdateExplanationDatasetOperationMetadata": { "id": "GoogleCloudAiplatformV1UpdateExplanationDatasetOperationMetadata", "description": "Runtime operation information for ModelService.UpdateExplanationDataset.", "type": "object", "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpec": { "id": "GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpec", "properties": { "minValue": { "format": "double", "type": "number", "description": "Required. Inclusive minimum value of the parameter." }, "defaultValue": { "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.", "type": "number" }, "maxValue": { "type": "number", "description": "Required. Inclusive maximum value of the parameter.", "format": "double" } }, "description": "Value specification for a parameter in `DOUBLE` type.", "type": "object" }, "GoogleCloudAiplatformV1MetadataStoreMetadataStoreState": { "type": "object", "id": "GoogleCloudAiplatformV1MetadataStoreMetadataStoreState", "description": "Represents state information for a MetadataStore.", "properties": { "diskUtilizationBytes": { "format": "int64", "type": "string", "description": "The disk utilization of the MetadataStore in bytes." } } }, "GoogleCloudAiplatformV1AuthConfigOidcConfig": { "description": "Config for user OIDC auth.", "properties": { "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" }, "serviceAccount": { "type": "string", "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": "object", "id": "GoogleCloudAiplatformV1AuthConfigOidcConfig" }, "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerMonthUsageData": { "id": "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerMonthUsageData", "description": "Per month usage data", "properties": { "userUsageData": { "description": "Usage data for each user in the given month.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ReadTensorboardUsageResponsePerUserUsageData" } } }, "type": "object" }, "GoogleCloudAiplatformV1CompactionConfigLlmSummarizationConfig": { "id": "GoogleCloudAiplatformV1CompactionConfigLlmSummarizationConfig", "description": "Configuration for LLM summarization-based compaction. When set, the session context is summarized with an LLM once it exceeds the summarizer target threshold.", "properties": { "mode": { "enum": [ "MODE_UNSPECIFIED", "AUTO" ], "type": "string", "description": "Required. The summarization mode. Only `AUTO` is supported for MVP.", "enumDescriptions": [ "Unspecified. Requests must set an explicit mode.", "Platform-managed summarization with server-side defaults." ] } }, "type": "object" }, "GoogleCloudAiplatformV1PointwiseMetricSpec": { "description": "Spec for pointwise metric.", "properties": { "metricPromptTemplate": { "description": "Required. Metric prompt template for pointwise metric.", "type": "string" }, "customOutputFormatConfig": { "description": "Optional. CustomOutputFormatConfig allows customization of metric output. By default, metrics return a score and explanation. When this config is set, the default output is replaced with either: - The raw output string. - A parsed output based on a user-defined schema. If a custom format is chosen, the `score` and `explanation` fields in the corresponding metric result will be empty.", "$ref": "GoogleCloudAiplatformV1CustomOutputFormatConfig" }, "systemInstruction": { "description": "Optional. System instructions for pointwise metric.", "type": "string" } }, "id": "GoogleCloudAiplatformV1PointwiseMetricSpec", "type": "object" }, "GoogleCloudAiplatformV1CreateEntityTypeOperationMetadata": { "id": "GoogleCloudAiplatformV1CreateEntityTypeOperationMetadata", "properties": { "genericMetadata": { "description": "Operation metadata for EntityType.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "type": "object", "description": "Details of operations that perform create EntityType." }, "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequest": { "type": "object", "id": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequest", "properties": { "objectives": { "items": { "$ref": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective" }, "description": "Required. Objectives of the stats to retrieve.", "type": "array" }, "startTime": { "type": "string", "format": "google-datetime", "description": "The earliest timestamp of stats being generated. If not set, indicates fetching stats till the earliest 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" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "format": "int32" }, "pageToken": { "type": "string", "description": "A page token received from a previous JobService.SearchModelDeploymentMonitoringStatsAnomalies call." }, "deployedModelId": { "description": "Required. The DeployedModel ID of the [ModelDeploymentMonitoringObjectiveConfig.deployed_model_id].", "type": "string" }, "endTime": { "description": "The latest timestamp of stats being generated. If not set, indicates feching stats till the latest possible one.", "format": "google-datetime", "type": "string" } }, "description": "Request message for JobService.SearchModelDeploymentMonitoringStatsAnomalies." }, "GoogleCloudAiplatformV1AugmentPromptResponse": { "description": "Response message for AugmentPrompt.", "type": "object", "properties": { "facts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Fact" }, "description": "Retrieved facts from RAG data sources." }, "augmentedPrompt": { "items": { "$ref": "GoogleCloudAiplatformV1Content" }, "description": "Augmented prompt, only text format is supported for now.", "type": "array" } }, "id": "GoogleCloudAiplatformV1AugmentPromptResponse" }, "GoogleCloudAiplatformV1ObservabilityConfig": { "id": "GoogleCloudAiplatformV1ObservabilityConfig", "type": "object", "properties": { "observabilityEnabled": { "type": "boolean", "description": "Optional. Enables observability for this agent's sessions: OpenTelemetry span emission covering tool names, model names, token counts, latencies and status. If `false`, the other fields here are ignored." }, "sensitiveLoggingEnabled": { "type": "boolean", "description": "Optional. Enables sensitive logging. Sensitive logging includes customer core content (prompts, model completions, tool argument payloads and tool responses). If `false`, those are sanitized and only structural attributes are recorded. No effect unless `observability_enabled` is true. Settable and returned, but NOT YET ENFORCED. Nothing reads it at runtime, so `true` does not currently cause content to be captured, and `false` is not what keeps content from being captured. Treat it as a recorded intention that takes effect when enforcement lands." } }, "description": "Observability settings for one agent's sessions." }, "GoogleCloudAiplatformV1ApiAuthApiKeyConfig": { "id": "GoogleCloudAiplatformV1ApiAuthApiKeyConfig", "properties": { "apiKeySecretVersion": { "description": "Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}", "type": "string" }, "apiKeyString": { "type": "string", "description": "The API key string. Either this or `api_key_secret_version` must be set." } }, "description": "The API secret.", "type": "object" }, "GoogleCloudAiplatformV1CreateNotebookExecutionJobOperationMetadata": { "description": "Metadata information for NotebookService.CreateNotebookExecutionJob.", "properties": { "progressMessage": { "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime.", "type": "string" }, "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The operation generic information." } }, "id": "GoogleCloudAiplatformV1CreateNotebookExecutionJobOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetrics": { "properties": { "auRoc": { "description": "The Area Under Receiver Operating Characteristic curve metric. Micro-averaged for the overall evaluation.", "format": "float", "type": "number" }, "confusionMatrix": { "description": "Confusion matrix of the evaluation.", "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix" }, "logLoss": { "format": "float", "description": "The Log Loss metric.", "type": "number" }, "auPrc": { "type": "number", "description": "The Area Under Precision-Recall Curve metric. Micro-averaged for the overall evaluation.", "format": "float" }, "confidenceMetrics": { "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics" }, "type": "array", "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." } }, "description": "Metrics for classification evaluation results.", "type": "object", "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetrics" }, "GoogleCloudAiplatformV1ToolExaAiSearch": { "id": "GoogleCloudAiplatformV1ToolExaAiSearch", "properties": { "customConfigs": { "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "type": "object", "description": "Optional. This field can be used to pass any parameter from the Exa.ai Search API." }, "apiKey": { "type": "string", "description": "Required. The API key for ExaAiSearch." } }, "type": "object", "description": "ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding." }, "GoogleCloudAiplatformV1GoogleDriveSourceResourceId": { "id": "GoogleCloudAiplatformV1GoogleDriveSourceResourceId", "type": "object", "properties": { "resourceType": { "enum": [ "RESOURCE_TYPE_UNSPECIFIED", "RESOURCE_TYPE_FILE", "RESOURCE_TYPE_FOLDER" ], "type": "string", "description": "Required. The type of the Google Drive resource.", "enumDescriptions": [ "Unspecified resource type.", "File resource type.", "Folder resource type." ] }, "resourceId": { "type": "string", "description": "Required. The ID of the Google Drive resource." } }, "description": "The type and ID of the Google Drive resource." }, "GoogleCloudAiplatformV1ListDeploymentResourcePoolsResponse": { "type": "object", "id": "GoogleCloudAiplatformV1ListDeploymentResourcePoolsResponse", "description": "Response message for ListDeploymentResourcePools method.", "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": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1DeploymentResourcePool" }, "description": "The DeploymentResourcePools from the specified location." } } }, "GoogleCloudAiplatformV1CompactionConfig": { "type": "object", "id": "GoogleCloudAiplatformV1CompactionConfig", "description": "Configuration for session compaction. Compaction has two independent categories that may be enabled individually or together. When both are enabled they run as a stackable pipeline (deterministic event editing first, then summarization if the session is still above the target). At least one category must be enabled; a config with neither is rejected (enforced server-side). This message is standalone so it can be reused across surfaces (e.g. on the compact request today, and on session creation for a future reactive trigger).", "properties": { "summarization": { "$ref": "GoogleCloudAiplatformV1CompactionConfigLlmSummarizationConfig", "description": "Optional. LLM summarization compaction configuration. Set to enable summarization-based compaction. Can be combined with `event_editing`." }, "eventEditing": { "$ref": "GoogleCloudAiplatformV1CompactionConfigEventEditingConfig", "description": "Optional. Event-history editing compaction configuration. Set to enable deterministic event editing (e.g. masking oversized tool responses). Can be combined with `summarization`." } } }, "GoogleCloudAiplatformV1StartNotebookRuntimeRequest": { "id": "GoogleCloudAiplatformV1StartNotebookRuntimeRequest", "properties": {}, "description": "Request message for NotebookService.StartNotebookRuntime.", "type": "object" }, "GoogleCloudAiplatformV1ListEvaluationMetricsResponse": { "properties": { "evaluationMetrics": { "items": { "$ref": "GoogleCloudAiplatformV1EvaluationMetric" }, "type": "array", "description": "List of EvaluationMetrics in the requested page." }, "nextPageToken": { "type": "string", "description": "A token to retrieve the next page of results." } }, "description": "Response message for EvaluationMetricService.ListEvaluationMetrics.", "type": "object", "id": "GoogleCloudAiplatformV1ListEvaluationMetricsResponse" }, "GoogleCloudAiplatformV1ListModelEvaluationSlicesResponse": { "type": "object", "properties": { "nextPageToken": { "type": "string", "description": "A token to retrieve next page of results. Pass to ListModelEvaluationSlicesRequest.page_token to obtain that page." }, "modelEvaluationSlices": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ModelEvaluationSlice" }, "description": "List of ModelEvaluations in the requested page." } }, "id": "GoogleCloudAiplatformV1ListModelEvaluationSlicesResponse", "description": "Response message for ModelService.ListModelEvaluationSlices." }, "CloudAiLargeModelsVisionMedia": { "id": "CloudAiLargeModelsVisionMedia", "description": "Media.", "properties": { "image": { "$ref": "CloudAiLargeModelsVisionImage", "description": "Image." }, "video": { "$ref": "CloudAiLargeModelsVisionVideo", "description": "Video" } }, "type": "object" }, "GoogleCloudAiplatformV1EvaluationInstanceInstanceData": { "id": "GoogleCloudAiplatformV1EvaluationInstanceInstanceData", "type": "object", "description": "Instance data used to populate placeholders in a metric prompt template.", "properties": { "text": { "type": "string", "description": "Text data." }, "contents": { "$ref": "GoogleCloudAiplatformV1EvaluationInstanceInstanceDataContents", "description": "List of Gemini content data." } } }, "GoogleCloudAiplatformV1DeleteMetadataStoreOperationMetadata": { "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "Operation metadata for deleting a MetadataStore." } }, "type": "object", "description": "Details of operations that perform MetadataService.DeleteMetadataStore.", "id": "GoogleCloudAiplatformV1DeleteMetadataStoreOperationMetadata" }, "GoogleCloudAiplatformV1VertexMultimodalDatasetSource": { "type": "object", "id": "GoogleCloudAiplatformV1VertexMultimodalDatasetSource", "properties": { "datasetName": { "description": "Required. The resource name of the Vertex Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "type": "string" } }, "description": "The Vertex Multimodal Dataset for the input content." }, "GoogleCloudAiplatformV1SpeculativeDecodingSpecDraftModelSpeculation": { "properties": { "draftModel": { "type": "string", "description": "Required. The resource name of the draft model." } }, "type": "object", "id": "GoogleCloudAiplatformV1SpeculativeDecodingSpecDraftModelSpeculation", "description": "Draft model speculation works by using the smaller model to generate candidate tokens for speculative decoding." }, "GoogleCloudAiplatformV1SchemaPredictParamsImageObjectDetectionPredictionParams": { "type": "object", "description": "Prediction model parameters for Image Object Detection.", "properties": { "confidenceThreshold": { "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0", "format": "float", "type": "number" }, "maxPredictions": { "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.", "type": "integer", "format": "int32" } }, "id": "GoogleCloudAiplatformV1SchemaPredictParamsImageObjectDetectionPredictionParams" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation": { "properties": { "columnName": { "type": "string" } }, "description": "Training pipeline will infer the proper transformation based on the statistic of dataset.", "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation" }, "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilitySessionScope": { "properties": { "inactivityTrigger": { "description": "Session is considered ready for evaluation when there are no new traces for a specified period of inactivity.", "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilitySessionScopeInactivityTrigger" }, "filter": { "type": "array", "description": "Optional. A list of predicates to filter sessions. Multiple predicates are combined using AND. The maximum number of predicates is 10.", "items": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilitySessionScopePredicate" } } }, "id": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilitySessionScope", "description": "If chosen, the online evaluator will evaluate sessions matching specified `filter`. A session is a group of traces with a common `gen_ai.conversation.id`.", "type": "object" }, "GoogleCloudAiplatformV1ImportRagFilesRequest": { "properties": { "importRagFilesConfig": { "description": "Required. The config for the RagFiles to be synced and imported into the RagCorpus. VertexRagDataService.ImportRagFiles.", "$ref": "GoogleCloudAiplatformV1ImportRagFilesConfig" } }, "type": "object", "id": "GoogleCloudAiplatformV1ImportRagFilesRequest", "description": "Request message for VertexRagDataService.ImportRagFiles." }, "GoogleCloudAiplatformV1UserActionReference": { "id": "GoogleCloudAiplatformV1UserActionReference", "description": "References an API call. It contains more information about long running operation and Jobs that are triggered by the API call.", "type": "object", "properties": { "dataLabelingJob": { "type": "string", "description": "For API calls that start a LabelingJob. Resource name of the LabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`" }, "operation": { "description": "For API calls that return a long running operation. Resource name of the long running operation. Format: `projects/{project}/locations/{location}/operations/{operation}`", "type": "string" }, "method": { "description": "The method name of the API RPC call. For example, \"/google.cloud.aiplatform.{apiVersion}.DatasetService.CreateDataset\"", "type": "string" } } }, "GoogleCloudAiplatformV1SharePointSources": { "id": "GoogleCloudAiplatformV1SharePointSources", "description": "The SharePointSources to pass to ImportRagFiles.", "type": "object", "properties": { "sharePointSources": { "items": { "$ref": "GoogleCloudAiplatformV1SharePointSourcesSharePointSource" }, "description": "The SharePoint sources.", "type": "array" } } }, "GenaiVertexV1PlaceCitation": { "description": "A place citation annotation.", "properties": { "name": { "description": "Title of the place.", "type": "string" }, "reviewSnippets": { "items": { "$ref": "GenaiVertexV1ReviewSnippet" }, "description": "Snippets of reviews that are used to generate answers about the features of a given place in Google Maps.", "type": "array" }, "url": { "description": "URI reference of the place.", "type": "string" }, "placeId": { "type": "string", "description": "The ID of the place, in `places/{place_id}` format." } }, "type": "object", "id": "GenaiVertexV1PlaceCitation" }, "GoogleCloudAiplatformV1GenerationConfigRoutingConfigAutoRoutingMode": { "description": "The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference.", "id": "GoogleCloudAiplatformV1GenerationConfigRoutingConfigAutoRoutingMode", "properties": { "modelRoutingPreference": { "enumDescriptions": [ "Unspecified model routing preference.", "The model will be selected to prioritize the quality of the response.", "The model will be selected to balance quality and cost.", "The model will be selected to prioritize the cost of the request." ], "description": "The model routing preference.", "enum": [ "UNKNOWN", "PRIORITIZE_QUALITY", "BALANCED", "PRIORITIZE_COST" ], "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1ExplanationParameters": { "type": "object", "id": "GoogleCloudAiplatformV1ExplanationParameters", "properties": { "sampledShapleyAttribution": { "description": "An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265.", "$ref": "GoogleCloudAiplatformV1SampledShapleyAttribution" }, "xraiAttribution": { "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.", "$ref": "GoogleCloudAiplatformV1XraiAttribution" }, "topK": { "format": "int32", "description": "If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.", "type": "integer" }, "integratedGradientsAttribution": { "$ref": "GoogleCloudAiplatformV1IntegratedGradientsAttribution", "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" }, "outputIndices": { "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).", "type": "array" }, "examples": { "description": "Example-based explanations that returns the nearest neighbors from the provided dataset.", "$ref": "GoogleCloudAiplatformV1Examples" } }, "description": "Parameters to configure explaining for Model's predictions." }, "GoogleCloudAiplatformV1RagFileChunkingConfig": { "id": "GoogleCloudAiplatformV1RagFileChunkingConfig", "description": "Specifies the size and overlap of chunks for RagFiles.", "type": "object", "properties": { "fixedLengthChunking": { "description": "Specifies the fixed length chunking config.", "$ref": "GoogleCloudAiplatformV1RagFileChunkingConfigFixedLengthChunking" } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs", "properties": { "multiLabel": { "type": "boolean" } }, "type": "object" }, "GoogleCloudAiplatformV1ExportFeatureValuesRequest": { "description": "Request message for FeaturestoreService.ExportFeatureValues.", "type": "object", "id": "GoogleCloudAiplatformV1ExportFeatureValuesRequest", "properties": { "featureSelector": { "$ref": "GoogleCloudAiplatformV1FeatureSelector", "description": "Required. Selects Features to export values of." }, "destination": { "description": "Required. Specifies destination location and format.", "$ref": "GoogleCloudAiplatformV1FeatureValueDestination" }, "settings": { "items": { "$ref": "GoogleCloudAiplatformV1DestinationFeatureSetting" }, "description": "Per-Feature export settings.", "type": "array" }, "fullExport": { "description": "Exports all historical values of all entities of the EntityType within a time range", "$ref": "GoogleCloudAiplatformV1ExportFeatureValuesRequestFullExport" }, "snapshotExport": { "description": "Exports the latest Feature values of all entities of the EntityType within a time range.", "$ref": "GoogleCloudAiplatformV1ExportFeatureValuesRequestSnapshotExport" } } }, "GoogleCloudAiplatformV1UrlMetadata": { "id": "GoogleCloudAiplatformV1UrlMetadata", "properties": { "urlRetrievalStatus": { "enum": [ "URL_RETRIEVAL_STATUS_UNSPECIFIED", "URL_RETRIEVAL_STATUS_SUCCESS", "URL_RETRIEVAL_STATUS_ERROR" ], "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "The URL was retrieved successfully.", "The URL retrieval failed." ], "description": "The status of the URL retrieval." }, "retrievedUrl": { "description": "The URL retrieved by the tool.", "type": "string" } }, "description": "The metadata for a single URL retrieval.", "type": "object" }, "GoogleCloudAiplatformV1EvaluationRunEvaluationConfig": { "description": "The Evalution configuration used for the evaluation run.", "properties": { "rubricConfigs": { "type": "array", "description": "Optional. The rubric configs for the evaluation run. They are used to generate rubrics which can be used by rubric-based metrics. Multiple rubric configs can be specified for rubric generation but only one rubric config can be used for a rubric-based metric. If more than one rubric config is provided, the evaluation metric must specify a rubric group key. Note that if a generation spec is specified on both a rubric config and an evaluation metric, the rubrics generated for the metric will be used for evaluation.", "items": { "$ref": "GoogleCloudAiplatformV1EvaluationRubricConfig" } }, "allowCrossRegionModel": { "description": "Optional. Allows the evaluation run 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 run location is provided elsewhere in the run config, this flag must be set to true or the request will fail.", "type": "boolean" }, "autoraterConfig": { "$ref": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigAutoraterConfig", "description": "Optional. The autorater config for the evaluation run." }, "metrics": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1EvaluationRunMetric" }, "description": "Optional. The metrics to be calculated in the evaluation run. Required when analysis_configs is not set." }, "promptTemplate": { "description": "The prompt template used for inference. The values for variables in the prompt template are defined in EvaluationItem.EvaluationPrompt.PromptTemplateData.values.", "$ref": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigPromptTemplate" }, "outputConfig": { "$ref": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfigOutputConfig", "description": "Optional. The output config for the evaluation run." }, "cloudLoggingConfig": { "description": "Optional. Configuration for exporting evaluation results to Cloud Logging.", "$ref": "GoogleCloudAiplatformV1CloudLoggingConfig" }, "datasetCustomMetrics": { "type": "array", "description": "Optional. Specifications for custom dataset-level aggregations.", "items": { "$ref": "GoogleCloudAiplatformV1DatasetCustomMetric" } }, "lossAnalysisConfig": { "description": "Optional. Specifications for loss analysis. Each config can be specified for one metric.", "items": { "$ref": "GoogleCloudAiplatformV1LossAnalysisConfig" }, "type": "array" } }, "type": "object", "id": "GoogleCloudAiplatformV1EvaluationRunEvaluationConfig" }, "GoogleCloudAiplatformV1CountTokensRequest": { "description": "Request message for PredictionService.CountTokens.", "properties": { "model": { "type": "string", "description": "Optional. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`" }, "instances": { "type": "array", "items": { "type": "any" }, "description": "Optional. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model." }, "contents": { "items": { "$ref": "GoogleCloudAiplatformV1Content" }, "type": "array", "description": "Optional. Input content." }, "generationConfig": { "$ref": "GoogleCloudAiplatformV1GenerationConfig", "description": "Optional. Generation config that the model will use to generate the response." }, "systemInstruction": { "$ref": "GoogleCloudAiplatformV1Content", "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." }, "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": { "$ref": "GoogleCloudAiplatformV1Tool" } } }, "id": "GoogleCloudAiplatformV1CountTokensRequest", "type": "object" }, "GenaiVertexV1CreateInteractionHttpRequest": { "description": "Request message for [InteractionsService.CreateInteractionHttp].", "type": "object", "id": "GenaiVertexV1CreateInteractionHttpRequest", "properties": { "httpBody": { "description": "Required. The interaction to create.", "$ref": "GoogleApiHttpBody" } } }, "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpec": { "id": "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpec", "description": "The specification of a Reasoning Engine deployment.", "type": "object", "properties": { "resourceLimits": { "additionalProperties": { "type": "string" }, "type": "object", "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" }, "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": { "$ref": "GoogleCloudAiplatformV1SecretEnvVar" } }, "keepAliveProbe": { "description": "Optional. Specifies the configuration for keep-alive probe. Contains configuration on a specified endpoint that a deployment host should use to keep the container alive based on the probe settings.", "$ref": "GoogleCloudAiplatformV1KeepAliveProbe" }, "maxInstances": { "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].", "type": "integer", "format": "int32" }, "containerConcurrency": { "description": "Optional. Concurrency for each container and agent server. Recommended value: 2 * cpu + 1. Defaults to 9.", "type": "integer", "format": "int32" }, "agentGatewayConfig": { "description": "Optional. Agent Gateway configuration for the Reasoning Engine deployment.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpecAgentGatewayConfig" }, "env": { "items": { "$ref": "GoogleCloudAiplatformV1EnvVar" }, "type": "array", "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].", "type": "integer", "format": "int32" }, "pscInterfaceConfig": { "description": "Optional. Configuration for PSC-I.", "$ref": "GoogleCloudAiplatformV1PscInterfaceConfig" } } }, "GoogleCloudAiplatformV1MetricxSpec": { "type": "object", "id": "GoogleCloudAiplatformV1MetricxSpec", "properties": { "targetLanguage": { "description": "Optional. Target language in BCP-47 format. Covers both prediction and reference.", "type": "string" }, "version": { "enumDescriptions": [ "MetricX version unspecified.", "MetricX 2024 (2.6) for translation + reference (reference-based).", "MetricX 2024 (2.6) for translation + source (QE).", "MetricX 2024 (2.6) for translation + source + reference (source-reference-combined)." ], "enum": [ "METRICX_VERSION_UNSPECIFIED", "METRICX_24_REF", "METRICX_24_SRC", "METRICX_24_SRC_REF" ], "description": "Required. Which version to use for evaluation.", "type": "string" }, "sourceLanguage": { "description": "Optional. Source language in BCP-47 format.", "type": "string" } }, "description": "Spec for MetricX metric." }, "GenaiVertexV1ThoughtStep": { "description": "A thought step.", "properties": { "summary": { "type": "array", "description": "A summary of the thought.", "items": { "$ref": "GenaiVertexV1Content" } }, "signature": { "format": "byte", "type": "string", "description": "A signature hash for backend validation." } }, "id": "GenaiVertexV1ThoughtStep", "type": "object" }, "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairList": { "type": "object", "properties": { "features": { "description": "List of feature names and values.", "items": { "$ref": "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair" }, "type": "array" } }, "id": "GoogleCloudAiplatformV1FetchFeatureValuesResponseFeatureNameValuePairList", "description": "Response structure in the format of key (feature name) and (feature) value pair." }, "GoogleCloudAiplatformV1RougeInput": { "properties": { "instances": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1RougeInstance" }, "description": "Required. Repeated rouge instances." }, "metricSpec": { "description": "Required. Spec for rouge score metric.", "$ref": "GoogleCloudAiplatformV1RougeSpec" } }, "type": "object", "id": "GoogleCloudAiplatformV1RougeInput", "description": "Input for rouge metric." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTables": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTables", "description": "A TrainingJob that trains and uploads an AutoML Tables Model.", "type": "object", "properties": { "metadata": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesMetadata", "description": "The metadata information." }, "inputs": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputs", "description": "The input parameters of this TrainingJob." } } }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageObjectDetectionEvaluationMetrics": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageObjectDetectionEvaluationMetrics", "properties": { "boundingBoxMeanAveragePrecision": { "type": "number", "description": "The single metric for bounding boxes evaluation: the `meanAveragePrecision` averaged over all `boundingBoxMetricsEntries`.", "format": "float" }, "boundingBoxMetrics": { "items": { "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsBoundingBoxMetrics" }, "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.", "type": "array" }, "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" } }, "description": "Metrics for image object detection evaluation results." }, "GoogleCloudAiplatformV1NotebookIdleShutdownConfig": { "properties": { "idleTimeout": { "type": "string", "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.", "format": "google-duration" }, "idleShutdownDisabled": { "description": "Whether Idle Shutdown is disabled in this NotebookRuntimeTemplate.", "type": "boolean" } }, "type": "object", "id": "GoogleCloudAiplatformV1NotebookIdleShutdownConfig", "description": "The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field." }, "GoogleCloudAiplatformV1BatchImportModelEvaluationSlicesRequest": { "properties": { "modelEvaluationSlices": { "description": "Required. Model evaluation slice resource to be imported.", "items": { "$ref": "GoogleCloudAiplatformV1ModelEvaluationSlice" }, "type": "array" } }, "id": "GoogleCloudAiplatformV1BatchImportModelEvaluationSlicesRequest", "type": "object", "description": "Request message for ModelService.BatchImportModelEvaluationSlices" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics", "properties": { "f1Score": { "description": "Harmonic mean of precision and recall.", "type": "number", "format": "float" }, "falseNegativeCount": { "description": "Number of examples where the autorater chose the baseline model, but humans preferred the model.", "type": "string", "format": "int64" }, "humanPreferenceModelWinRate": { "description": "Percentage of time humans decided the model had the better response.", "type": "number", "format": "float" }, "precision": { "type": "number", "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" }, "falsePositiveCount": { "format": "int64", "type": "string", "description": "Number of examples where the autorater chose the model, but humans preferred the baseline model." }, "recall": { "type": "number", "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." }, "cohensKappa": { "format": "float", "description": "A measurement of agreement between the autorater and human raters that takes the likelihood of random agreement into account.", "type": "number" }, "trueNegativeCount": { "type": "string", "description": "Number of examples where both the autorater and humans decided that the model had the worse response.", "format": "int64" }, "modelWinRate": { "format": "float", "type": "number", "description": "Percentage of time the autorater decided the model had the better response." }, "truePositiveCount": { "description": "Number of examples where both the autorater and humans decided that the model had the better response.", "format": "int64", "type": "string" }, "humanPreferenceBaselineModelWinRate": { "type": "number", "format": "float", "description": "Percentage of time humans decided the baseline model had the better response." }, "accuracy": { "type": "number", "description": "Fraction of cases where the autorater agreed with the human raters.", "format": "float" }, "baselineModelWinRate": { "description": "Percentage of time the autorater decided the baseline model had the better response.", "format": "float", "type": "number" } }, "type": "object", "description": "Metrics for general pairwise text generation evaluation results." }, "GoogleCloudAiplatformV1ListArtifactsResponse": { "id": "GoogleCloudAiplatformV1ListArtifactsResponse", "properties": { "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" }, "artifacts": { "items": { "$ref": "GoogleCloudAiplatformV1Artifact" }, "type": "array", "description": "The Artifacts retrieved from the MetadataStore." } }, "description": "Response message for MetadataService.ListArtifacts.", "type": "object" }, "GoogleCloudAiplatformV1ListModelVersionCheckpointsResponse": { "type": "object", "id": "GoogleCloudAiplatformV1ListModelVersionCheckpointsResponse", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListModelVersionCheckpointsRequest.page_token to obtain that page.", "type": "string" }, "checkpoints": { "description": "List of Model Version checkpoints.", "items": { "$ref": "GoogleCloudAiplatformV1ModelVersionCheckpoint" }, "type": "array" } }, "description": "Response message for ModelService.ListModelVersionCheckpoints" }, "GoogleCloudAiplatformV1ProbeHttpGetAction": { "properties": { "path": { "description": "Path to access on the HTTP server.", "type": "string" }, "port": { "format": "int32", "type": "integer", "description": "Number of the port to access on the container. Number must be in the range 1 to 65535." }, "scheme": { "description": "Scheme to use for connecting to the host. Defaults to HTTP. Acceptable values are \"HTTP\" or \"HTTPS\".", "type": "string" }, "httpHeaders": { "type": "array", "description": "Custom headers to set in the request. HTTP allows repeated headers.", "items": { "$ref": "GoogleCloudAiplatformV1ProbeHttpHeader" } }, "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" } }, "description": "HttpGetAction describes an action based on HTTP Get requests.", "type": "object", "id": "GoogleCloudAiplatformV1ProbeHttpGetAction" }, "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecImageSpec": { "id": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecImageSpec", "type": "object", "properties": { "buildArgs": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. Build arguments to be used. They will be passed through --build-arg flags." } }, "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." }, "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentConfigTools": { "type": "object", "description": "Represents a list of tools for an agent.", "id": "GoogleCloudAiplatformV1EvaluationInstanceDeprecatedAgentConfigTools", "properties": { "tool": { "items": { "$ref": "GoogleCloudAiplatformV1Tool" }, "description": "Optional. List of tools: each tool can have multiple function declarations.", "type": "array" } } }, "GoogleCloudAiplatformV1CodeExecutionResult": { "id": "GoogleCloudAiplatformV1CodeExecutionResult", "type": "object", "properties": { "outcome": { "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": "Required. Outcome of the code execution.", "enum": [ "OUTCOME_UNSPECIFIED", "OUTCOME_OK", "OUTCOME_FAILED", "OUTCOME_DEADLINE_EXCEEDED" ], "type": "string" }, "output": { "type": "string", "description": "Optional. Contains stdout when code execution is successful, stderr or other description otherwise." }, "id": { "type": "string", "description": "Optional. The identifier of the `ExecutableCode` part this result is for. Only populated if the corresponding `ExecutableCode` has an id." } }, "description": "Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used." }, "GoogleCloudAiplatformV1PauseScheduleRequest": { "description": "Request message for ScheduleService.PauseSchedule.", "properties": {}, "id": "GoogleCloudAiplatformV1PauseScheduleRequest", "type": "object" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics": { "description": "Model evaluation metrics for text sentiment problems.", "properties": { "f1Score": { "description": "The harmonic mean of recall and precision.", "type": "number", "format": "float" }, "meanSquaredError": { "format": "float", "type": "number", "description": "Mean squared error. Only set for ModelEvaluations, not for ModelEvaluationSlices." }, "quadraticKappa": { "description": "Quadratic weighted kappa. Only set for ModelEvaluations, not for ModelEvaluationSlices.", "format": "float", "type": "number" }, "confusionMatrix": { "description": "Confusion matrix of the evaluation. Only set for ModelEvaluations, not for ModelEvaluationSlices.", "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix" }, "meanAbsoluteError": { "description": "Mean absolute error. Only set for ModelEvaluations, not for ModelEvaluationSlices.", "type": "number", "format": "float" }, "precision": { "type": "number", "format": "float", "description": "Precision." }, "recall": { "type": "number", "description": "Recall.", "format": "float" }, "linearKappa": { "format": "float", "type": "number", "description": "Linear weighted kappa. Only set for ModelEvaluations, not for ModelEvaluationSlices." } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics" }, "GoogleCloudAiplatformV1KeepAliveProbeHttpGet": { "description": "Specifies the HTTP GET configuration for the probe.", "id": "GoogleCloudAiplatformV1KeepAliveProbeHttpGet", "properties": { "path": { "description": "Required. Specifies the path of the HTTP GET request (e.g., `\"/is_busy\"`).", "type": "string" }, "port": { "type": "integer", "description": "Optional. Specifies the port number on the container to which the request is sent.", "format": "int32" } }, "type": "object" }, "GenaiVertexV1RetrievalCallStep": { "id": "GenaiVertexV1RetrievalCallStep", "type": "object", "properties": { "retrievalType": { "description": "The type of retrieval tools.", "enum": [ "RETRIEVAL_TYPE_UNSPECIFIED", "RETRIEVAL_TYPE_VERTEX_AI_SEARCH", "RETRIEVAL_TYPE_RAG_STORE", "RETRIEVAL_TYPE_EXA_AI_SEARCH", "RETRIEVAL_TYPE_PARALLEL_AI_SEARCH" ], "enumDescriptions": [ "", "", "", "", "" ], "type": "string" }, "arguments": { "$ref": "GenaiVertexV1RetrievalCallStepRetrievalStepArguments", "description": "Required. The arguments to pass to the retrieval tool." } }, "description": "Retrieval call step. Used by Vertex Retrieval tools such as Parallel AI, Exa AI, Vertex AI Search, etc. RetrievalType decides which tool is used." }, "GoogleCloudAiplatformV1SandboxEnvironmentTemplateCustomContainerSpec": { "id": "GoogleCloudAiplatformV1SandboxEnvironmentTemplateCustomContainerSpec", "description": "Specification for deploying from a custom container image.", "properties": { "imageUri": { "description": "Required. The Artifact Registry Docker image URI (e.g., us-central1-docker.pkg.dev/my-project/my-repo/my-image:tag) of the container image that is to be run on each worker replica.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1IngestEventsRequest": { "type": "object", "description": "Request message for MemoryBankService.IngestEvents.", "properties": { "generationTriggerConfig": { "$ref": "GoogleCloudAiplatformV1MemoryGenerationTriggerConfig", "description": "Optional. Configuration for triggering memory generation from this ingestion. If not set, then the stream will be force flushed immediately." }, "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" }, "metadata": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1MemoryMetadataValue" }, "description": "Optional. User-provided metadata for the generated memories. This is not generated by Memory Bank." }, "revisionTtl": { "format": "google-duration", "type": "string", "description": "Optional. The TTL for the revision. The expiration time is computed: now + TTL." }, "directContentsSource": { "$ref": "GoogleCloudAiplatformV1IngestionDirectContentsSource", "description": "Ingest events directly from the request." }, "disableMemoryRevisions": { "type": "boolean", "description": "Optional. If true, no revisions will be created for this request." }, "revisionExpireTime": { "description": "Optional. Timestamp of when the revision is considered expired. If not set, the memory revision will be kept until manually deleted.", "format": "google-datetime", "type": "string" }, "metadataMergeStrategy": { "type": "string", "enum": [ "METADATA_MERGE_STRATEGY_UNSPECIFIED", "OVERWRITE", "MERGE", "REQUIRE_EXACT_MATCH" ], "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." ], "description": "Optional. The strategy to use when applying metadata to existing memories." }, "streamId": { "type": "string", "description": "Optional. The ID of the stream to ingest events into. If not provided, a new one will be created." }, "scope": { "additionalProperties": { "type": "string" }, "type": "object", "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 '*'." }, "revisionLabels": { "additionalProperties": { "type": "string" }, "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" } }, "id": "GoogleCloudAiplatformV1IngestEventsRequest" }, "GoogleCloudAiplatformV1GroundingChunkMapsPlaceAnswerSources": { "type": "object", "id": "GoogleCloudAiplatformV1GroundingChunkMapsPlaceAnswerSources", "properties": { "reviewSnippets": { "items": { "$ref": "GoogleCloudAiplatformV1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet" }, "type": "array", "description": "Snippets of reviews that were used to generate the answer." } }, "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." }, "GoogleCloudAiplatformV1Featurestore": { "properties": { "state": { "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." ], "type": "string", "readOnly": true, "enum": [ "STATE_UNSPECIFIED", "STABLE", "UPDATING" ], "description": "Output only. State of the featurestore." }, "updateTime": { "description": "Output only. Timestamp when this Featurestore was last updated.", "readOnly": true, "format": "google-datetime", "type": "string" }, "name": { "readOnly": true, "type": "string", "description": "Output only. Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "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." }, "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "satisfiesPzs": { "type": "boolean", "description": "Output only. Reserved for future use.", "readOnly": true }, "onlineStorageTtlDays": { "format": "int32", "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" }, "encryptionSpec": { "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.", "$ref": "GoogleCloudAiplatformV1EncryptionSpec" }, "onlineServingConfig": { "$ref": "GoogleCloudAiplatformV1FeaturestoreOnlineServingConfig", "description": "Optional. Config for online storage resources. The field should not co-exist with the field of `OnlineStoreReplicationConfig`. If both of it and OnlineStoreReplicationConfig are unset, the feature store will not have an online store and cannot be used for online serving." }, "satisfiesPzi": { "readOnly": true, "type": "boolean", "description": "Output only. Reserved for future use." }, "createTime": { "description": "Output only. Timestamp when this Featurestore was created.", "format": "google-datetime", "type": "string", "readOnly": true } }, "id": "GoogleCloudAiplatformV1Featurestore", "description": "Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values.", "type": "object" }, "GoogleCloudAiplatformV1EvaluateInstancesRequest": { "id": "GoogleCloudAiplatformV1EvaluateInstancesRequest", "description": "Request message for EvaluationService.EvaluateInstances.", "type": "object", "properties": { "bleuInput": { "description": "Instances and metric spec for bleu metric.", "$ref": "GoogleCloudAiplatformV1BleuInput" }, "rubricBasedInstructionFollowingInput": { "description": "Rubric Based Instruction Following metric.", "$ref": "GoogleCloudAiplatformV1RubricBasedInstructionFollowingInput" }, "summarizationQualityInput": { "description": "Input for summarization quality metric.", "$ref": "GoogleCloudAiplatformV1SummarizationQualityInput" }, "toolCallValidInput": { "description": "Tool call metric instances. Input for tool call valid metric.", "$ref": "GoogleCloudAiplatformV1ToolCallValidInput" }, "cometInput": { "description": "Translation metrics. Input for Comet metric.", "$ref": "GoogleCloudAiplatformV1CometInput" }, "rougeInput": { "description": "Instances and metric spec for rouge metric.", "$ref": "GoogleCloudAiplatformV1RougeInput" }, "questionAnsweringQualityInput": { "$ref": "GoogleCloudAiplatformV1QuestionAnsweringQualityInput", "description": "Input for question answering quality metric." }, "questionAnsweringRelevanceInput": { "$ref": "GoogleCloudAiplatformV1QuestionAnsweringRelevanceInput", "description": "Input for question answering relevance metric." }, "pairwiseMetricInput": { "$ref": "GoogleCloudAiplatformV1PairwiseMetricInput", "description": "Input for pairwise metric." }, "summarizationHelpfulnessInput": { "$ref": "GoogleCloudAiplatformV1SummarizationHelpfulnessInput", "description": "Input for summarization helpfulness metric." }, "instance": { "description": "The instance to be evaluated.", "$ref": "GoogleCloudAiplatformV1EvaluationInstance" }, "trajectoryRecallInput": { "$ref": "GoogleCloudAiplatformV1TrajectoryRecallInput", "description": "Input for trajectory recall metric." }, "toolNameMatchInput": { "description": "Input for tool name match metric.", "$ref": "GoogleCloudAiplatformV1ToolNameMatchInput" }, "trajectoryAnyOrderMatchInput": { "description": "Input for trajectory match any order metric.", "$ref": "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchInput" }, "pairwiseQuestionAnsweringQualityInput": { "$ref": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualityInput", "description": "Input for pairwise question answering quality metric." }, "safetyInput": { "description": "Input for safety metric.", "$ref": "GoogleCloudAiplatformV1SafetyInput" }, "questionAnsweringCorrectnessInput": { "description": "Input for question answering correctness metric.", "$ref": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessInput" }, "autoraterConfig": { "$ref": "GoogleCloudAiplatformV1AutoraterConfig", "description": "Optional. Autorater config used for evaluation. Not applicable for predefined metrics (PredefinedMetricSpec); the server uses its own model configuration for predefined metrics and this field is ignored." }, "metricxInput": { "description": "Input for Metricx metric.", "$ref": "GoogleCloudAiplatformV1MetricxInput" }, "questionAnsweringHelpfulnessInput": { "description": "Input for question answering helpfulness metric.", "$ref": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessInput" }, "fulfillmentInput": { "description": "Input for fulfillment metric.", "$ref": "GoogleCloudAiplatformV1FulfillmentInput" }, "trajectoryExactMatchInput": { "description": "Input for trajectory exact match metric.", "$ref": "GoogleCloudAiplatformV1TrajectoryExactMatchInput" }, "exactMatchInput": { "description": "Auto metric instances. Instances and metric spec for exact match metric.", "$ref": "GoogleCloudAiplatformV1ExactMatchInput" }, "pairwiseSummarizationQualityInput": { "$ref": "GoogleCloudAiplatformV1PairwiseSummarizationQualityInput", "description": "Input for pairwise summarization quality metric." }, "fluencyInput": { "description": "LLM-based metric instance. General text generation metrics, applicable to other categories. Input for fluency metric.", "$ref": "GoogleCloudAiplatformV1FluencyInput" }, "summarizationVerbosityInput": { "description": "Input for summarization verbosity metric.", "$ref": "GoogleCloudAiplatformV1SummarizationVerbosityInput" }, "trajectoryPrecisionInput": { "description": "Input for trajectory precision metric.", "$ref": "GoogleCloudAiplatformV1TrajectoryPrecisionInput" }, "coherenceInput": { "description": "Input for coherence metric.", "$ref": "GoogleCloudAiplatformV1CoherenceInput" }, "metricSources": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1MetricSource" }, "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." }, "groundednessInput": { "description": "Input for groundedness metric.", "$ref": "GoogleCloudAiplatformV1GroundednessInput" }, "pointwiseMetricInput": { "$ref": "GoogleCloudAiplatformV1PointwiseMetricInput", "description": "Input for pointwise metric." }, "location": { "description": "Required. The resource name of the Location to evaluate the instances. Format: `projects/{project}/locations/{location}`", "type": "string" }, "trajectorySingleToolUseInput": { "$ref": "GoogleCloudAiplatformV1TrajectorySingleToolUseInput", "description": "Input for trajectory single tool use metric." }, "toolParameterKeyMatchInput": { "description": "Input for tool parameter key match metric.", "$ref": "GoogleCloudAiplatformV1ToolParameterKeyMatchInput" }, "trajectoryInOrderMatchInput": { "$ref": "GoogleCloudAiplatformV1TrajectoryInOrderMatchInput", "description": "Input for trajectory in order match metric." }, "toolParameterKvMatchInput": { "description": "Input for tool parameter key value match metric.", "$ref": "GoogleCloudAiplatformV1ToolParameterKVMatchInput" }, "metrics": { "items": { "$ref": "GoogleCloudAiplatformV1Metric" }, "type": "array", "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." } } }, "GoogleCloudAiplatformV1SavedQuery": { "type": "object", "properties": { "displayName": { "type": "string", "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." }, "annotationSpecCount": { "type": "integer", "description": "Output only. Number of AnnotationSpecs in the context of the SavedQuery.", "readOnly": true, "format": "int32" }, "metadata": { "type": "any", "description": "Some additional information about the SavedQuery." }, "createTime": { "readOnly": true, "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when this SavedQuery was created." }, "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" }, "etag": { "description": "Used to perform a consistent read-modify-write update. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "annotationFilter": { "description": "Output only. Filters on the Annotations in the dataset.", "type": "string", "readOnly": true }, "updateTime": { "readOnly": true, "format": "google-datetime", "type": "string", "description": "Output only. Timestamp when SavedQuery was last updated." }, "name": { "description": "Output only. Resource name of the SavedQuery.", "readOnly": true, "type": "string" }, "supportAutomlTraining": { "type": "boolean", "readOnly": true, "description": "Output only. If the Annotations belonging to the SavedQuery can be used for AutoML training." } }, "id": "GoogleCloudAiplatformV1SavedQuery", "description": "A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters." }, "GoogleCloudAiplatformV1UnmanagedContainerModel": { "description": "Contains model information necessary to perform batch prediction without requiring a full model import.", "properties": { "predictSchemata": { "description": "Contains the schemata used in Model's predictions and explanations", "$ref": "GoogleCloudAiplatformV1PredictSchemata" }, "containerSpec": { "description": "Input only. The specification of the container that is to be used when deploying this Model.", "$ref": "GoogleCloudAiplatformV1ModelContainerSpec" }, "artifactUri": { "type": "string", "description": "The path to the directory containing the Model artifact and any of its supporting files." } }, "id": "GoogleCloudAiplatformV1UnmanagedContainerModel", "type": "object" }, "GoogleCloudAiplatformV1VideoMetadata": { "type": "object", "description": "Provides metadata for a video, including the start and end offsets for clipping and the frame rate.", "properties": { "endOffset": { "format": "google-duration", "type": "string", "description": "Optional. The end offset of the video." }, "fps": { "format": "double", "description": "Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].", "type": "number" }, "startOffset": { "format": "google-duration", "description": "Optional. The start offset of the video.", "type": "string" } }, "id": "GoogleCloudAiplatformV1VideoMetadata" }, "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadata": { "properties": { "timeColumn": { "type": "string", "description": "The column name of the time column that identifies time order in the time series." }, "timeSeriesIdentifierColumn": { "description": "The column name of the time series identifier column that identifies the time series.", "type": "string" }, "inputConfig": { "$ref": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadataInputConfig" } }, "type": "object", "description": "The metadata of Datasets that contain time series data.", "id": "GoogleCloudAiplatformV1SchemaTimeSeriesDatasetMetadata" }, "GoogleCloudAiplatformV1AudioResponseFormat": { "description": "Configuration for audio-specific output formatting.", "id": "GoogleCloudAiplatformV1AudioResponseFormat", "properties": { "sampleRate": { "description": "Optional. Sample rate for the generated audio in Hertz.", "format": "int32", "type": "integer" }, "mimeType": { "description": "Optional. The MIME type of the audio output.", "enum": [ "MIME_TYPE_UNSPECIFIED", "AUDIO_MP3", "AUDIO_OGG_OPUS", "AUDIO_L16", "AUDIO_WAV", "AUDIO_ALAW", "AUDIO_MULAW" ], "enumDescriptions": [ "Default value. This value is unused.", "MP3 audio format.", "OGG Opus audio format.", "Raw PCM (L16) audio format.", "WAV audio format.", "A-law audio format.", "Mu-law audio format." ], "type": "string" }, "bitRate": { "format": "int32", "description": "Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).", "type": "integer" }, "delivery": { "type": "string", "description": "Optional. Delivery mode for the generated content.", "enum": [ "DELIVERY_UNSPECIFIED", "INLINE", "URI" ], "enumDescriptions": [ "Default value. This value is unused.", "Generated bytes are returned inline in the response.", "Generated content is stored and a URI is returned." ] } }, "type": "object" }, "GoogleCloudAiplatformV1PublisherModelCallToActionDeployDeployMetadata": { "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.", "type": "object", "id": "GoogleCloudAiplatformV1PublisherModelCallToActionDeployDeployMetadata" }, "GenaiVertexV1AgentInteraction": { "properties": { "dynamicConfig": { "$ref": "GenaiVertexV1DynamicAgentConfig" }, "codeMenderConfig": { "$ref": "GenaiVertexV1CodeMenderAgentConfig" }, "antigravityConfig": { "description": "Antigravity agent configuration. This configuration is session-level settings that are passed to the agent runtime on a per-request basis.", "$ref": "GenaiVertexV1AntigravityAgentConfig" }, "deepResearchConfig": { "$ref": "GenaiVertexV1DeepResearchAgentConfig" }, "agent": { "description": "The name of the `Agent` used for generating the completion.", "type": "string" } }, "type": "object", "description": "Interaction for generating the completion using agents.", "id": "GenaiVertexV1AgentInteraction" }, "GoogleRpcStatus": { "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).", "properties": { "code": { "description": "The status code, which should be an enum value of google.rpc.Code.", "type": "integer", "format": "int32" }, "message": { "type": "string", "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." }, "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." } } } }, "type": "object", "id": "GoogleRpcStatus" }, "GoogleCloudAiplatformV1QueryReasoningEngineResponse": { "description": "Response message for ReasoningEngineExecutionService.QueryReasoningEngine.", "type": "object", "properties": { "output": { "type": "any", "description": "Response provided by users in JSON object format." } }, "id": "GoogleCloudAiplatformV1QueryReasoningEngineResponse" }, "GoogleCloudAiplatformV1ListNotebookRuntimesResponse": { "properties": { "notebookRuntimes": { "description": "List of NotebookRuntimes in the requested page.", "items": { "$ref": "GoogleCloudAiplatformV1NotebookRuntime" }, "type": "array" }, "nextPageToken": { "description": "A token to retrieve next page of results. Pass to ListNotebookRuntimesRequest.page_token to obtain that page.", "type": "string" } }, "description": "Response message for NotebookService.ListNotebookRuntimes.", "type": "object", "id": "GoogleCloudAiplatformV1ListNotebookRuntimesResponse" }, "GoogleCloudAiplatformV1AudioTranscriptionWordInfo": { "type": "object", "properties": { "endOffset": { "type": "string", "format": "google-duration", "description": "Optional. End offset in time of the word relative to the start of the audio." }, "word": { "type": "string", "description": "Required. Transcript of the word." }, "startOffset": { "format": "google-duration", "type": "string", "description": "Optional. Start offset in time of the word relative to the start of the audio." } }, "description": "Information about a single recognized word.", "id": "GoogleCloudAiplatformV1AudioTranscriptionWordInfo" }, "GoogleCloudAiplatformV1FunctionResponseBlob": { "id": "GoogleCloudAiplatformV1FunctionResponseBlob", "description": "Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field.", "properties": { "displayName": { "type": "string", "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." }, "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" }, "data": { "format": "byte", "type": "string", "description": "Required. Raw bytes." } }, "type": "object" }, "GoogleCloudAiplatformV1TunedModelCheckpoint": { "properties": { "endpoint": { "type": "string", "description": "The Endpoint resource name that the checkpoint is deployed to. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`." }, "checkpointId": { "description": "The ID of the checkpoint.", "type": "string" }, "epoch": { "format": "int64", "type": "string", "description": "The epoch of the checkpoint." }, "step": { "format": "int64", "description": "The step of the checkpoint.", "type": "string" } }, "description": "TunedModelCheckpoint for the Tuned Model of a Tuning Job.", "id": "GoogleCloudAiplatformV1TunedModelCheckpoint", "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs", "properties": { "modelType": { "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." ], "type": "string", "enum": [ "MODEL_TYPE_UNSPECIFIED", "CLOUD", "MOBILE_VERSATILE_1", "MOBILE_JETSON_VERSATILE_1" ] } } }, "GoogleCloudAiplatformV1TunedModelRef": { "type": "object", "description": "TunedModel Reference for legacy model migration.", "properties": { "pipelineJob": { "description": "Support migration from tuning job list page, from bison model to gemini model.", "type": "string" }, "tuningJob": { "type": "string", "description": "Support migration from tuning job list page, from gemini-1.0-pro-002 to 1.5 and above." }, "tunedModel": { "description": "Support migration from model registry.", "type": "string" } }, "id": "GoogleCloudAiplatformV1TunedModelRef" }, "GoogleCloudAiplatformV1CreateNotebookExecutionJobRequest": { "description": "Request message for [NotebookService.CreateNotebookExecutionJob]", "type": "object", "id": "GoogleCloudAiplatformV1CreateNotebookExecutionJobRequest", "properties": { "notebookExecutionJobId": { "type": "string", "description": "Optional. User specified ID for the NotebookExecutionJob." }, "parent": { "description": "Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`", "type": "string" }, "notebookExecutionJob": { "description": "Required. The NotebookExecutionJob to create.", "$ref": "GoogleCloudAiplatformV1NotebookExecutionJob" } } }, "GoogleCloudAiplatformV1RagVectorDbConfigVertexVectorSearch": { "description": "The config for the Vertex Vector Search.", "properties": { "indexEndpoint": { "type": "string", "description": "The resource name of the Index Endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`" }, "index": { "description": "The resource name of the Index. Format: `projects/{project}/locations/{location}/indexes/{index}`", "type": "string" } }, "id": "GoogleCloudAiplatformV1RagVectorDbConfigVertexVectorSearch", "type": "object" }, "GoogleCloudAiplatformV1UserScenarioGenerationConfig": { "type": "object", "properties": { "userScenarioCount": { "format": "int64", "description": "Required. The number of user scenarios to generate. The maximum number of scenarios that can be generated is 100.", "type": "string" }, "environmentData": { "type": "string", "description": "Optional. Environment data in string type." }, "modelName": { "type": "string", "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}`" }, "simulationInstruction": { "description": "Optional. Simulation instruction to guide the user scenario generation.", "type": "string" } }, "id": "GoogleCloudAiplatformV1UserScenarioGenerationConfig", "description": "User scenario generation configuration." }, "GenaiVertexV1WordInfo": { "id": "GenaiVertexV1WordInfo", "description": "Word-level ASR annotation for transcription output. Carries the word text, optional timing, and optional speaker attribution.", "type": "object", "properties": { "speaker": { "description": "Optional. Speaker label for this word (e.g. \"spk_1\", \"spk_2\"). Present when diarization_mode is set in TranscriptionConfig.", "type": "string" }, "text": { "type": "string", "description": "The transcribed word." }, "startOffset": { "format": "google-duration", "type": "string", "description": "Start offset in time of the word relative to the start of the audio. Present when timestamp_granularities contains \"word\"." }, "endOffset": { "type": "string", "description": "End offset in time of the word relative to the start of the audio. Present when timestamp_granularities contains \"word\".", "format": "google-duration" } } }, "GoogleCloudAiplatformV1Tensor": { "id": "GoogleCloudAiplatformV1Tensor", "properties": { "dtype": { "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.", "", "", "", "", "", "", "", "", "", "", "" ], "type": "string", "description": "The data type of tensor.", "enum": [ "DATA_TYPE_UNSPECIFIED", "BOOL", "STRING", "FLOAT", "DOUBLE", "INT8", "INT16", "INT32", "INT64", "UINT8", "UINT16", "UINT32", "UINT64" ] }, "uint64Val": { "type": "array", "description": "UINT64", "items": { "type": "string", "format": "uint64" } }, "stringVal": { "type": "array", "items": { "type": "string" }, "description": "STRING" }, "tensorVal": { "format": "byte", "description": "Serialized raw tensor content.", "type": "string" }, "floatVal": { "items": { "type": "number", "format": "float" }, "description": "FLOAT", "type": "array" }, "uintVal": { "type": "array", "items": { "type": "integer", "format": "uint32" }, "description": "UINT8 UINT16 UINT32" }, "structVal": { "additionalProperties": { "$ref": "GoogleCloudAiplatformV1Tensor" }, "description": "A map of string to tensor.", "type": "object" }, "boolVal": { "type": "array", "items": { "type": "boolean" }, "description": "Type specific representations that make it easy to create tensor protos in all languages. Only the representation corresponding to \"dtype\" can be set. The values hold the flattened representation of the tensor in row major order. BOOL" }, "doubleVal": { "type": "array", "items": { "format": "double", "type": "number" }, "description": "DOUBLE" }, "shape": { "description": "Shape of the tensor.", "items": { "format": "int64", "type": "string" }, "type": "array" }, "intVal": { "type": "array", "items": { "type": "integer", "format": "int32" }, "description": "INT_8 INT_16 INT_32" }, "listVal": { "description": "A list of tensor values.", "items": { "$ref": "GoogleCloudAiplatformV1Tensor" }, "type": "array" }, "int64Val": { "items": { "type": "string", "format": "int64" }, "description": "INT64", "type": "array" }, "bytesVal": { "description": "STRING", "items": { "format": "byte", "type": "string" }, "type": "array" } }, "description": "A tensor value type.", "type": "object" }, "GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfig": { "type": "object", "id": "GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfig", "description": "ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.", "properties": { "deployedModelId": { "description": "The DeployedModel ID of the objective config.", "type": "string" }, "objectiveConfig": { "description": "The objective config of for the modelmonitoring job of this deployed model.", "$ref": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig" } } }, "GoogleCloudAiplatformV1DedicatedResources": { "type": "object", "id": "GoogleCloudAiplatformV1DedicatedResources", "properties": { "spot": { "type": "boolean", "description": "Optional. If true, schedule the deployment workload on [spot VMs](https://cloud.google.com/kubernetes-engine/docs/concepts/spot-vms)." }, "minReplicaCount": { "type": "integer", "format": "int32", "description": "Required. Immutable. The minimum number of machine replicas that will be always deployed on. This value must be greater than or equal to 1. If traffic increases, it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed." }, "machineSpec": { "description": "Required. Immutable. The specification of a single machine being used.", "$ref": "GoogleCloudAiplatformV1MachineSpec" }, "autoscalingMetricSpecs": { "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`.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1AutoscalingMetricSpec" } }, "requiredReplicaCount": { "format": "int32", "type": "integer", "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." }, "maxReplicaCount": { "format": "int32", "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, will use min_replica_count as the default value. The value of this field impacts the charge against Agent Platform 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)." } }, "description": "A description of resources that are dedicated to a DeployedModel or DeployedIndex, and that need a higher degree of manual configuration." }, "GoogleCloudAiplatformV1CreatePipelineJobRequest": { "description": "Request message for PipelineService.CreatePipelineJob.", "properties": { "parent": { "type": "string", "description": "Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`" }, "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" }, "pipelineJob": { "description": "Required. The PipelineJob to create.", "$ref": "GoogleCloudAiplatformV1PipelineJob" } }, "type": "object", "id": "GoogleCloudAiplatformV1CreatePipelineJobRequest" }, "GoogleCloudAiplatformV1CompleteTrialRequest": { "type": "object", "properties": { "trialInfeasible": { "description": "Optional. True if the Trial cannot be run with the given Parameter, and final_measurement will be ignored.", "type": "boolean" }, "finalMeasurement": { "$ref": "GoogleCloudAiplatformV1Measurement", "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" }, "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": "GoogleCloudAiplatformV1CompleteTrialRequest" }, "GenaiVertexV1SafetySetting": { "description": "A safety setting that affects the safety-blocking behavior. A SafetySetting consists of a harm category and a threshold for that category.", "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." }, "type": { "description": "Required. The type of harm category to be blocked.", "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." ], "type": "string", "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" ] }, "threshold": { "enum": [ "HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF" ], "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." ], "type": "string", "description": "Required. The threshold for blocking content. If the harm probability exceeds this threshold, the content will be blocked." } }, "type": "object", "id": "GenaiVertexV1SafetySetting" }, "GoogleCloudAiplatformV1ToolNameMatchInput": { "type": "object", "properties": { "instances": { "description": "Required. Repeated tool name match instances.", "items": { "$ref": "GoogleCloudAiplatformV1ToolNameMatchInstance" }, "type": "array" }, "metricSpec": { "$ref": "GoogleCloudAiplatformV1ToolNameMatchSpec", "description": "Required. Spec for tool name match metric." } }, "description": "Input for tool name match metric.", "id": "GoogleCloudAiplatformV1ToolNameMatchInput" }, "GoogleCloudAiplatformV1WriteTensorboardRunDataRequest": { "id": "GoogleCloudAiplatformV1WriteTensorboardRunDataRequest", "type": "object", "properties": { "tensorboardRun": { "type": "string", "description": "Required. The resource name of the TensorboardRun to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`" }, "timeSeriesData": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1TimeSeriesData" }, "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." } }, "description": "Request message for TensorboardService.WriteTensorboardRunData." }, "GenaiVertexV1Step": { "id": "GenaiVertexV1Step", "description": "A step in the interaction.", "type": "object", "properties": { "thought": { "$ref": "GenaiVertexV1ThoughtStep" }, "toolResult": { "$ref": "GenaiVertexV1ToolResultStep" }, "userInput": { "description": "DO NOT USE -- These are for 3P JSON only", "$ref": "GenaiVertexV1UserInputStep" }, "modelOutput": { "$ref": "GenaiVertexV1ModelOutputStep" }, "toolCall": { "$ref": "GenaiVertexV1ToolCallStep" } } }, "GenaiVertexV1SpeakerConfig": { "description": "Configuration for multi-speaker and speech generation.", "properties": { "speakers": { "items": { "$ref": "GenaiVertexV1SpeechConfig" }, "description": "Individual speaker configurations.", "type": "array" } }, "type": "object", "id": "GenaiVertexV1SpeakerConfig" }, "GoogleCloudAiplatformV1StartNotebookRuntimeOperationMetadata": { "description": "Metadata information for NotebookService.StartNotebookRuntime.", "properties": { "genericMetadata": { "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata", "description": "The operation generic information." }, "progressMessage": { "type": "string", "description": "A human-readable message that shows the intermediate progress details of NotebookRuntime." } }, "id": "GoogleCloudAiplatformV1StartNotebookRuntimeOperationMetadata", "type": "object" }, "GoogleCloudAiplatformV1RemoveDatapointsResponse": { "description": "Response message for IndexService.RemoveDatapoints", "properties": {}, "id": "GoogleCloudAiplatformV1RemoveDatapointsResponse", "type": "object" }, "GoogleCloudAiplatformV1DeployedIndexAuthConfig": { "id": "GoogleCloudAiplatformV1DeployedIndexAuthConfig", "description": "Used to set up the auth on the DeployedIndex's private endpoint.", "type": "object", "properties": { "authProvider": { "description": "Defines the authentication provider that the DeployedIndex uses.", "$ref": "GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProvider" } } }, "GoogleCloudAiplatformV1EvaluationParserConfig": { "type": "object", "properties": { "customCodeParserConfig": { "description": "Optional. Use custom code to parse the LLM response.", "$ref": "GoogleCloudAiplatformV1EvaluationParserConfigCustomCodeParserConfig" } }, "id": "GoogleCloudAiplatformV1EvaluationParserConfig", "description": "Config for parsing LLM responses. It can be used to parse the LLM response to be evaluated, or the LLM response from LLM-based metrics/Autoraters." }, "GoogleCloudAiplatformV1SchemaPredictParamsImageClassificationPredictionParams": { "description": "Prediction model parameters for Image Classification.", "properties": { "maxPredictions": { "type": "integer", "format": "int32", "description": "The Model only returns up to that many top, by confidence score, predictions per instance. If this number is very high, the Model may return fewer predictions. Default value is 10." }, "confidenceThreshold": { "format": "float", "type": "number", "description": "The Model only returns predictions with at least this confidence score. Default value is 0.0" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaPredictParamsImageClassificationPredictionParams" }, "GoogleCloudAiplatformV1TrajectoryInOrderMatchInput": { "id": "GoogleCloudAiplatformV1TrajectoryInOrderMatchInput", "type": "object", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1TrajectoryInOrderMatchSpec", "description": "Required. Spec for TrajectoryInOrderMatch metric." }, "instances": { "items": { "$ref": "GoogleCloudAiplatformV1TrajectoryInOrderMatchInstance" }, "type": "array", "description": "Required. Repeated TrajectoryInOrderMatch instance." } }, "description": "Instances and metric spec for TrajectoryInOrderMatch metric." }, "GoogleCloudAiplatformV1ResourceRuntime": { "properties": { "accessUris": { "type": "object", "description": "Output only. URIs for user to connect to the Cluster. Example: { \"RAY_HEAD_NODE_INTERNAL_IP\": \"head-node-IP:10001\" \"RAY_DASHBOARD_URI\": \"ray-dashboard-address:8888\" }", "readOnly": true, "additionalProperties": { "type": "string" } } }, "description": "Persistent Cluster runtime information as output", "id": "GoogleCloudAiplatformV1ResourceRuntime", "type": "object" }, "GoogleCloudAiplatformV1ListSandboxEnvironmentsResponse": { "type": "object", "id": "GoogleCloudAiplatformV1ListSandboxEnvironmentsResponse", "properties": { "nextPageToken": { "description": "A token, which can be sent as ListSandboxEnvironmentsRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages.", "type": "string" }, "sandboxEnvironments": { "items": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironment" }, "description": "The SandboxEnvironments matching the request.", "type": "array" } }, "description": "Response message for SandboxEnvironmentService.ListSandboxEnvironments." }, "GoogleCloudAiplatformV1CancelEvaluationRunRequest": { "properties": {}, "id": "GoogleCloudAiplatformV1CancelEvaluationRunRequest", "type": "object", "description": "Request message for EvaluationManagementService.CancelEvaluationRun." }, "GoogleCloudAiplatformV1RawOutput": { "description": "Raw output.", "id": "GoogleCloudAiplatformV1RawOutput", "type": "object", "properties": { "rawOutput": { "description": "Output only. Raw output string.", "items": { "type": "string" }, "readOnly": true, "type": "array" } } }, "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec": { "description": "Represent spec for train trials.", "properties": { "frequency": { "type": "integer", "format": "int32", "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." }, "maxParallelTrialCount": { "description": "Required. The maximum number of trials to run in parallel.", "type": "integer", "format": "int32" }, "trainTrialJobSpec": { "description": "Required. The spec of a train trial job. The same spec applies to all train trials.", "$ref": "GoogleCloudAiplatformV1CustomJobSpec" } }, "type": "object", "id": "GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec" }, "GoogleCloudAiplatformV1OnlineEvaluatorStateDetails": { "type": "object", "id": "GoogleCloudAiplatformV1OnlineEvaluatorStateDetails", "description": "Contains additional information about the state of the OnlineEvaluator.", "properties": { "message": { "description": "Output only. Human-readable message describing the state of the OnlineEvaluator.", "type": "string", "readOnly": true } } }, "GoogleCloudAiplatformV1CreateFeatureOperationMetadata": { "id": "GoogleCloudAiplatformV1CreateFeatureOperationMetadata", "properties": { "genericMetadata": { "description": "Operation metadata for Feature.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "description": "Details of operations that perform create Feature.", "type": "object" }, "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpecAgentGatewayConfig": { "properties": { "agentToAnywhereConfig": { "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigAgentToAnywhereConfig", "description": "Optional. Configuration for traffic originating from the Reasoning Engine. When unset, outgoing traffic is not routed through an Agent Gateway." }, "clientToAgentConfig": { "description": "Optional. Configuration for traffic targeting the Reasoning Engine. When unset, incoming traffic is not routed through an Agent Gateway.", "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigClientToAgentConfig" } }, "description": "Agent Gateway configuration for a Reasoning Engine deployment.", "id": "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpecAgentGatewayConfig", "type": "object" }, "GoogleCloudAiplatformV1SchemaPromptSpecReferenceSentencePairList": { "properties": { "referenceSentencePairs": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SchemaPromptSpecReferenceSentencePair" }, "description": "Reference sentence pairs." } }, "id": "GoogleCloudAiplatformV1SchemaPromptSpecReferenceSentencePairList", "description": "A list of reference sentence pairs.", "type": "object" }, "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig": { "description": "The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.", "type": "object", "properties": { "defaultSkewThreshold": { "$ref": "GoogleCloudAiplatformV1ThresholdConfig", "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." }, "skewThresholds": { "additionalProperties": { "$ref": "GoogleCloudAiplatformV1ThresholdConfig" }, "type": "object", "description": "Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature." }, "attributionScoreSkewThresholds": { "description": "Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1ThresholdConfig" } } }, "id": "GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig" }, "GoogleCloudAiplatformV1UpdateModelDeploymentMonitoringJobOperationMetadata": { "type": "object", "id": "GoogleCloudAiplatformV1UpdateModelDeploymentMonitoringJobOperationMetadata", "description": "Runtime operation information for JobService.UpdateModelDeploymentMonitoringJob.", "properties": { "genericMetadata": { "description": "The operation generic information.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } } }, "GoogleCloudAiplatformV1GeminiAgentConfig": { "type": "object", "properties": { "geminiAgent": { "description": "Required. The resource name of the Gemini Agent. Format: `projects/{project}/locations/{location}/agents/{agent}`. For example: `projects/123/locations/us-central1/agents/my-agent`.", "type": "string" } }, "description": "Config for scraping a Gemini Agent (a Vertex AI Agent resource scraped via the Vertex Interactions API).", "id": "GoogleCloudAiplatformV1GeminiAgentConfig" }, "GoogleCloudAiplatformV1SearchEntryPoint": { "type": "object", "id": "GoogleCloudAiplatformV1SearchEntryPoint", "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.", "properties": { "sdkBlob": { "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.", "type": "string", "format": "byte" }, "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" } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation": { "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation", "properties": { "columnName": { "type": "string" }, "timeFormat": { "type": "string", "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)" } }, "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." }, "GoogleCloudAiplatformV1RayMetricSpec": { "id": "GoogleCloudAiplatformV1RayMetricSpec", "type": "object", "description": "Configuration for the Ray metrics.", "properties": { "enableUsageStatsCollection": { "description": "Optional. Flag to enable the Ray usage stats collection by Anyscale. https://docs.ray.io/en/latest/cluster/usage-stats.html#usage-stats-collection Disable by default.", "type": "boolean" }, "disabled": { "type": "boolean", "description": "Optional. Flag to disable the Ray metrics collection." } } }, "GoogleCloudAiplatformV1MetricMetadata": { "type": "object", "id": "GoogleCloudAiplatformV1MetricMetadata", "description": "Metadata about the metric, used for visualization and organization.", "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" }, "otherMetadata": { "description": "Optional. Flexible metadata for user-defined attributes.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "scoreRange": { "description": "Optional. The range of possible scores for this metric, used for plotting.", "$ref": "GoogleCloudAiplatformV1MetricMetadataScoreRange" } } }, "GoogleCloudAiplatformV1PointwiseMetricResult": { "description": "Spec for pointwise metric result.", "properties": { "customOutput": { "description": "Output only. Spec for custom output.", "$ref": "GoogleCloudAiplatformV1CustomOutput", "readOnly": true }, "score": { "readOnly": true, "type": "number", "description": "Output only. Pointwise metric score.", "format": "float" }, "explanation": { "readOnly": true, "description": "Output only. Explanation for pointwise metric score.", "type": "string" } }, "id": "GoogleCloudAiplatformV1PointwiseMetricResult", "type": "object" }, "GoogleCloudAiplatformV1TrajectoryPrecisionInstance": { "properties": { "predictedTrajectory": { "description": "Required. Spec for predicted tool call trajectory.", "$ref": "GoogleCloudAiplatformV1Trajectory" }, "referenceTrajectory": { "description": "Required. Spec for reference tool call trajectory.", "$ref": "GoogleCloudAiplatformV1Trajectory" } }, "id": "GoogleCloudAiplatformV1TrajectoryPrecisionInstance", "type": "object", "description": "Spec for TrajectoryPrecision instance." }, "GoogleCloudAiplatformV1EvaluationRunInferenceConfigAgentRunConfigUserSimulatorConfig": { "id": "GoogleCloudAiplatformV1EvaluationRunInferenceConfigAgentRunConfigUserSimulatorConfig", "properties": { "maxTurn": { "type": "integer", "format": "int32", "description": "Maximum number of invocations allowed by the multi-turn agent scraping. This property allows us to stop a run-off conversation, where the agent and the user simulator get into a never ending loop. The initial fixed prompt is also counted as an invocation." }, "modelConfig": { "description": "The configuration for the model.", "$ref": "GoogleCloudAiplatformV1GenerationConfig" }, "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" } }, "type": "object", "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." }, "GenaiVertexV1CodeMenderAgentConfigFixRequest": { "description": "Request parameters specific to FIX sessions, used for generating and validating security patches.", "id": "GenaiVertexV1CodeMenderAgentConfigFixRequest", "properties": { "description": { "type": "string", "description": "Additional context or custom instructions provided by the user to guide the patch generation process." }, "sourceFiles": { "items": { "$ref": "GenaiVertexV1CodeMenderAgentConfigFileContent" }, "type": "array", "description": "A list of source files providing context for the remediation. These files are typically the ones containing the identified vulnerability." }, "findingId": { "description": "The identifier of the specific security finding to be remediated. This ID maps to a previously discovered vulnerability.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1TrainingPipeline": { "properties": { "trainingTaskDefinition": { "type": "string", "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." }, "updateTime": { "description": "Output only. Time when the TrainingPipeline was most recently updated.", "format": "google-datetime", "type": "string", "readOnly": true }, "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.", "type": "any", "readOnly": true }, "labels": { "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.", "type": "object" }, "startTime": { "description": "Output only. Time when the TrainingPipeline for the first time entered the `PIPELINE_STATE_RUNNING` state.", "type": "string", "format": "google-datetime", "readOnly": true }, "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" }, "endTime": { "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", "type": "string" }, "modelToUpload": { "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.", "$ref": "GoogleCloudAiplatformV1Model" }, "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" ], "type": "string", "readOnly": true, "description": "Output only. The detailed state of the pipeline.", "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." ] }, "name": { "readOnly": true, "type": "string", "description": "Output only. Resource name of the TrainingPipeline." }, "inputDataConfig": { "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.", "$ref": "GoogleCloudAiplatformV1InputDataConfig" }, "trainingTaskInputs": { "description": "Required. The training task's parameter(s), as specified in the training_task_definition's `inputs`.", "type": "any" }, "parentModel": { "type": "string", "description": "Optional. When specify this field, the `model_to_upload` will not be uploaded as a new model, instead, it will become a new version of this `parent_model`." }, "displayName": { "type": "string", "description": "Required. The user-defined name of this TrainingPipeline." }, "error": { "$ref": "GoogleRpcStatus", "description": "Output only. Only populated when the pipeline's state is `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.", "readOnly": true }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1EncryptionSpec", "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." }, "createTime": { "type": "string", "description": "Output only. Time when the TrainingPipeline was created.", "format": "google-datetime", "readOnly": true } }, "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.", "type": "object", "id": "GoogleCloudAiplatformV1TrainingPipeline" }, "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectTimeRangeAndFeature": { "id": "GoogleCloudAiplatformV1DeleteFeatureValuesResponseSelectTimeRangeAndFeature", "description": "Response message if the request uses the SelectTimeRangeAndFeature option.", "properties": { "impactedFeatureCount": { "type": "string", "description": "The count of the features or columns impacted. This is the same as the feature count in the request.", "format": "int64" }, "offlineStorageModifiedEntityRowCount": { "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.", "type": "string", "format": "int64" }, "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" } }, "type": "object" }, "GoogleCloudAiplatformV1PipelineTaskDetail": { "description": "The runtime detail of a task execution.", "properties": { "taskUniqueName": { "readOnly": true, "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\".", "type": "string" }, "createTime": { "format": "google-datetime", "description": "Output only. Task create time.", "type": "string", "readOnly": true }, "outputs": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1PipelineTaskDetailArtifactList" }, "readOnly": true, "description": "Output only. The runtime output artifacts of the task." }, "pipelineTaskStatus": { "items": { "$ref": "GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatus" }, "description": "Output only. A list of task status. This field keeps a record of task status evolving over time.", "readOnly": true, "type": "array" }, "endTime": { "readOnly": true, "description": "Output only. Task end time.", "type": "string", "format": "google-datetime" }, "parentTaskId": { "type": "string", "description": "Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.", "format": "int64", "readOnly": true }, "error": { "$ref": "GoogleRpcStatus", "description": "Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.", "readOnly": true }, "execution": { "description": "Output only. The execution metadata of the task.", "$ref": "GoogleCloudAiplatformV1Execution", "readOnly": true }, "executorDetail": { "$ref": "GoogleCloudAiplatformV1PipelineTaskExecutorDetail", "description": "Output only. The detailed execution info.", "readOnly": true }, "startTime": { "format": "google-datetime", "type": "string", "readOnly": true, "description": "Output only. Task start time." }, "taskName": { "readOnly": true, "type": "string", "description": "Output only. The user specified name of the task that is defined in pipeline_spec." }, "state": { "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." ], "type": "string", "readOnly": true, "enum": [ "STATE_UNSPECIFIED", "PENDING", "RUNNING", "SUCCEEDED", "CANCEL_PENDING", "CANCELLING", "CANCELLED", "FAILED", "SKIPPED", "NOT_TRIGGERED" ], "description": "Output only. State of the task." }, "taskId": { "readOnly": true, "type": "string", "format": "int64", "description": "Output only. The system generated ID of the task." }, "inputs": { "type": "object", "description": "Output only. The runtime input artifacts of the task.", "readOnly": true, "additionalProperties": { "$ref": "GoogleCloudAiplatformV1PipelineTaskDetailArtifactList" } } }, "id": "GoogleCloudAiplatformV1PipelineTaskDetail", "type": "object" }, "GoogleCloudAiplatformV1ListTrialsResponse": { "id": "GoogleCloudAiplatformV1ListTrialsResponse", "type": "object", "properties": { "trials": { "description": "The Trials associated with the Study.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Trial" } }, "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" } }, "description": "Response message for VizierService.ListTrials." }, "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessSpec": { "type": "object", "id": "GoogleCloudAiplatformV1QuestionAnsweringCorrectnessSpec", "properties": { "version": { "description": "Optional. Which version to use for evaluation.", "type": "integer", "format": "int32" }, "useReference": { "description": "Optional. Whether to use instance.reference to compute question answering correctness.", "type": "boolean" } }, "description": "Spec for question answering correctness metric." }, "GoogleCloudAiplatformV1ListCachedContentsResponse": { "description": "Response with a list of CachedContents.", "type": "object", "properties": { "cachedContents": { "description": "List of cached contents.", "items": { "$ref": "GoogleCloudAiplatformV1CachedContent" }, "type": "array" }, "nextPageToken": { "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } }, "id": "GoogleCloudAiplatformV1ListCachedContentsResponse" }, "GoogleCloudAiplatformV1GroundingSupport": { "type": "object", "description": "A collection of supporting references for a segment or part of the model's response.", "properties": { "groundingChunkIndices": { "items": { "format": "int32", "type": "integer" }, "type": "array", "description": "A list of indices into the `grounding_chunks` field of the `GroundingMetadata` message. These indices specify which grounding chunks support the claim made in the content segment. For example, if this field has the values `[1, 3]`, it means that `grounding_chunks[1]` and `grounding_chunks[3]` are the sources for the claim in the content segment." }, "renderedParts": { "items": { "type": "integer", "format": "int32" }, "description": "Indices into the `rendered_parts` field of the `GroundingMetadata` message. These indices specify which rendered parts are associated with this support message.", "type": "array" }, "segment": { "description": "The content segment that this support message applies to.", "$ref": "GoogleCloudAiplatformV1Segment" }, "confidenceScores": { "type": "array", "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.", "items": { "format": "float", "type": "number" } } }, "id": "GoogleCloudAiplatformV1GroundingSupport" }, "GoogleCloudAiplatformV1RayLogsSpec": { "id": "GoogleCloudAiplatformV1RayLogsSpec", "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.", "type": "object" }, "GoogleCloudAiplatformV1IndexDatapoint": { "properties": { "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]." }, "embeddingMetadata": { "description": "Optional. The key-value map of additional metadata for the datapoint.", "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "type": "object" }, "sparseEmbedding": { "$ref": "GoogleCloudAiplatformV1IndexDatapointSparseEmbedding", "description": "Optional. Feature embedding vector for sparse index." }, "restricts": { "items": { "$ref": "GoogleCloudAiplatformV1IndexDatapointRestriction" }, "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" }, "datapointId": { "description": "Required. Unique identifier of the datapoint.", "type": "string" }, "numericRestricts": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1IndexDatapointNumericRestriction" }, "description": "Optional. List of Restrict of the datapoint, used to perform \"restricted searches\" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons." }, "crowdingTag": { "description": "Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.", "$ref": "GoogleCloudAiplatformV1IndexDatapointCrowdingTag" } }, "type": "object", "id": "GoogleCloudAiplatformV1IndexDatapoint", "description": "A datapoint of Index." }, "GoogleCloudAiplatformV1SchemaPredictPredictionVideoObjectTrackingPredictionResult": { "description": "Prediction output format for Video Object Tracking.", "properties": { "id": { "description": "The resource ID of the AnnotationSpec that had been identified.", "type": "string" }, "frames": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame" }, "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." }, "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." }, "timeSegmentStart": { "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.", "type": "string" }, "confidence": { "description": "The Model's confidence in correction of this prediction, higher value means higher confidence.", "type": "number", "format": "float" }, "displayName": { "type": "string", "description": "The display name of the AnnotationSpec that had been identified." } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaPredictPredictionVideoObjectTrackingPredictionResult" }, "GoogleCloudAiplatformV1AddExecutionEventsResponse": { "properties": {}, "type": "object", "id": "GoogleCloudAiplatformV1AddExecutionEventsResponse", "description": "Response message for MetadataService.AddExecutionEvents." }, "GoogleCloudAiplatformV1ManualBatchTuningParameters": { "id": "GoogleCloudAiplatformV1ManualBatchTuningParameters", "description": "Manual batch tuning parameters.", "type": "object", "properties": { "batchSize": { "type": "integer", "format": "int32", "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." } } }, "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigClientToAgentConfig": { "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" } }, "id": "GoogleCloudAiplatformV1ReasoningEngineSpecDeploymentSpecAgentGatewayConfigClientToAgentConfig", "description": "Configuration for traffic targeting a Reasoning Engine.", "type": "object" }, "GoogleCloudAiplatformV1TrajectorySingleToolUseMetricValue": { "type": "object", "description": "TrajectorySingleToolUse metric value for an instance.", "id": "GoogleCloudAiplatformV1TrajectorySingleToolUseMetricValue", "properties": { "score": { "readOnly": true, "description": "Output only. TrajectorySingleToolUse score.", "format": "float", "type": "number" } } }, "GoogleCloudAiplatformV1ImportFeatureValuesResponse": { "properties": { "importedEntityCount": { "format": "int64", "type": "string", "description": "Number of entities that have been imported by the operation." }, "importedFeatureValueCount": { "description": "Number of Feature values that have been imported by the operation.", "format": "int64", "type": "string" }, "timestampOutsideRetentionRowsCount": { "type": "string", "format": "int64", "description": "The number rows that weren't ingested due to having feature timestamps outside the retention boundary." }, "invalidRowCount": { "format": "int64", "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)." } }, "type": "object", "id": "GoogleCloudAiplatformV1ImportFeatureValuesResponse", "description": "Response message for FeaturestoreService.ImportFeatureValues." }, "GoogleCloudAiplatformV1ListEntityTypesResponse": { "properties": { "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" }, "entityTypes": { "description": "The EntityTypes matching the request.", "items": { "$ref": "GoogleCloudAiplatformV1EntityType" }, "type": "array" } }, "type": "object", "description": "Response message for FeaturestoreService.ListEntityTypes.", "id": "GoogleCloudAiplatformV1ListEntityTypesResponse" }, "GoogleCloudAiplatformV1Examples": { "type": "object", "properties": { "neighborCount": { "description": "The number of neighbors to return when querying for examples.", "format": "int32", "type": "integer" }, "exampleGcsSource": { "description": "The Cloud Storage input instances.", "$ref": "GoogleCloudAiplatformV1ExamplesExampleGcsSource" }, "nearestNeighborSearchConfig": { "description": "The full configuration for the generated index, the semantics are the same as metadata and should match [NearestNeighborSearchConfig](https://cloud.google.com/vertex-ai/docs/explainable-ai/configuring-explanations-example-based#nearest-neighbor-search-config).", "type": "any" }, "presets": { "$ref": "GoogleCloudAiplatformV1Presets", "description": "Simplified preset configuration, which automatically sets configuration values based on the desired query speed-precision trade-off and modality." } }, "id": "GoogleCloudAiplatformV1Examples", "description": "Example-based explainability that returns the nearest neighbors from the provided dataset." }, "GoogleCloudAiplatformV1ToolCallValidResults": { "properties": { "toolCallValidMetricValues": { "readOnly": true, "items": { "$ref": "GoogleCloudAiplatformV1ToolCallValidMetricValue" }, "description": "Output only. Tool call valid metric values.", "type": "array" } }, "description": "Results for tool call valid metric.", "id": "GoogleCloudAiplatformV1ToolCallValidResults", "type": "object" }, "GoogleCloudAiplatformV1SchemaPromptSpecContentMetadata": { "type": "object", "description": "Metadata the model returned alongside the content it generated.", "id": "GoogleCloudAiplatformV1SchemaPromptSpecContentMetadata", "properties": { "citationMetadata": { "description": "Optional. Citations that apply to the content.", "$ref": "GoogleCloudAiplatformV1CitationMetadata" }, "groundingMetadata": { "$ref": "GoogleCloudAiplatformV1GroundingMetadata", "description": "Optional. Sources used to ground the content." } } }, "GoogleCloudAiplatformV1FulfillmentInstance": { "id": "GoogleCloudAiplatformV1FulfillmentInstance", "properties": { "instruction": { "type": "string", "description": "Required. Inference instruction prompt to compare prediction with." }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" } }, "description": "Spec for fulfillment instance.", "type": "object" }, "GoogleCloudAiplatformV1RubricGroup": { "properties": { "groupId": { "description": "Unique identifier for the group.", "type": "string" }, "rubrics": { "description": "Rubrics that are part of this group.", "items": { "$ref": "GoogleCloudAiplatformV1Rubric" }, "type": "array" }, "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" } }, "id": "GoogleCloudAiplatformV1RubricGroup", "type": "object", "description": "A group of rubrics, used for grouping rubrics based on a metric or a version." }, "GoogleCloudAiplatformV1Annotation": { "type": "object", "description": "Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem.", "properties": { "etag": { "description": "Optional. Used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens.", "type": "string" }, "payloadSchemaUri": { "type": "string", "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." }, "createTime": { "readOnly": true, "format": "google-datetime", "description": "Output only. Timestamp when this Annotation was created.", "type": "string" }, "labels": { "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.", "additionalProperties": { "type": "string" }, "type": "object" }, "annotationSource": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1UserActionReference", "description": "Output only. The source of the Annotation." }, "name": { "description": "Output only. Resource name of the Annotation.", "type": "string", "readOnly": true }, "payload": { "type": "any", "description": "Required. The schema of the payload can be found in payload_schema." }, "updateTime": { "type": "string", "description": "Output only. Timestamp when this Annotation was last updated.", "readOnly": true, "format": "google-datetime" } }, "id": "GoogleCloudAiplatformV1Annotation" }, "GoogleCloudAiplatformV1ErrorAnalysisAnnotation": { "description": "Model error analysis for each annotation.", "type": "object", "id": "GoogleCloudAiplatformV1ErrorAnalysisAnnotation", "properties": { "outlierThreshold": { "format": "double", "type": "number", "description": "The threshold used to determine if this annotation is an outlier or not." }, "queryType": { "description": "The query type used for finding the attributed items.", "type": "string", "enum": [ "QUERY_TYPE_UNSPECIFIED", "ALL_SIMILAR", "SAME_CLASS_SIMILAR", "SAME_CLASS_DISSIMILAR" ], "enumDescriptions": [ "Unspecified query type for model error analysis.", "Query similar samples across all classes in the dataset.", "Query similar samples from the same class of the input sample.", "Query dissimilar samples from the same class of the input sample." ] }, "attributedItems": { "description": "Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1ErrorAnalysisAnnotationAttributedItem" } }, "outlierScore": { "description": "The outlier score of this annotated item. Usually defined as the min of all distances from attributed items.", "type": "number", "format": "double" } } }, "GoogleCloudAiplatformV1SyncFeatureViewRequest": { "id": "GoogleCloudAiplatformV1SyncFeatureViewRequest", "properties": {}, "description": "Request message for FeatureOnlineStoreAdminService.SyncFeatureView.", "type": "object" }, "GoogleCloudAiplatformV1ListEndpointsResponse": { "id": "GoogleCloudAiplatformV1ListEndpointsResponse", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListEndpointsRequest.page_token to obtain that page.", "type": "string" }, "endpoints": { "items": { "$ref": "GoogleCloudAiplatformV1Endpoint" }, "description": "List of Endpoints in the requested page.", "type": "array" } }, "type": "object", "description": "Response message for EndpointService.ListEndpoints." }, "GoogleCloudAiplatformV1CacheConfigRetentionConfig": { "description": "Configures the retention behavior of GenAI implicit (automatic) context caching for this project.", "type": "object", "properties": { "retentionType": { "enumDescriptions": [ "Unspecified. Treated the same as `DURABLE`.", "Restricts implicit caching to ephemeral, volatile-memory-backed retention only.", "Allows implicit caching to use long-lived, durable-storage-backed retention." ], "description": "Optional. Retention type applied to implicit cache traffic for this project.", "enum": [ "RETENTION_TYPE_UNSPECIFIED", "EPHEMERAL", "DURABLE" ], "type": "string" } }, "id": "GoogleCloudAiplatformV1CacheConfigRetentionConfig" }, "GoogleCloudAiplatformV1RagFile": { "type": "object", "description": "A RagFile contains user data for chunking, embedding and indexing.", "properties": { "description": { "description": "Optional. The description of the RagFile.", "type": "string" }, "updateTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. Timestamp when this RagFile was last updated." }, "googleDriveSource": { "readOnly": true, "description": "Output only. Google Drive location. Supports importing individual files as well as Google Drive folders.", "$ref": "GoogleCloudAiplatformV1GoogleDriveSource" }, "gcsSource": { "$ref": "GoogleCloudAiplatformV1GcsSource", "readOnly": true, "description": "Output only. Google Cloud Storage location of the RagFile. It does not support wildcards in the Cloud Storage uri for now." }, "sharePointSources": { "$ref": "GoogleCloudAiplatformV1SharePointSources", "description": "The RagFile is imported from a SharePoint source." }, "userMetadata": { "description": "Output only. The metadata for metadata search. The user_metadata Needs to be in JSON format.", "readOnly": true, "type": "string" }, "directUploadSource": { "readOnly": true, "$ref": "GoogleCloudAiplatformV1DirectUploadSource", "description": "Output only. The RagFile is encapsulated and uploaded in the UploadRagFile request." }, "displayName": { "description": "Required. The display name of the RagFile. The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "jiraSource": { "$ref": "GoogleCloudAiplatformV1JiraSource", "description": "The RagFile is imported from a Jira query." }, "createTime": { "description": "Output only. Timestamp when this RagFile was created.", "format": "google-datetime", "type": "string", "readOnly": true }, "name": { "readOnly": true, "description": "Output only. The resource name of the RagFile.", "type": "string" }, "slackSource": { "description": "The RagFile is imported from a Slack channel.", "$ref": "GoogleCloudAiplatformV1SlackSource" }, "fileStatus": { "$ref": "GoogleCloudAiplatformV1FileStatus", "description": "Output only. State of the RagFile.", "readOnly": true } }, "id": "GoogleCloudAiplatformV1RagFile" }, "GoogleCloudAiplatformV1Context": { "description": "Instance of a general context.", "type": "object", "properties": { "displayName": { "description": "User provided display name of the Context. May be up to 128 Unicode characters.", "type": "string" }, "schemaTitle": { "type": "string", "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." }, "labels": { "type": "object", "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).", "additionalProperties": { "type": "string" } }, "updateTime": { "description": "Output only. Timestamp when this Context was last updated.", "format": "google-datetime", "readOnly": true, "type": "string" }, "schemaVersion": { "type": "string", "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." }, "description": { "type": "string", "description": "Description of the Context" }, "etag": { "type": "string", "description": "An eTag used to perform consistent read-modify-write updates. If not set, a blind \"overwrite\" update happens." }, "createTime": { "format": "google-datetime", "type": "string", "readOnly": true, "description": "Output only. Timestamp when this Context was created." }, "parentContexts": { "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.", "type": "array", "items": { "type": "string" }, "readOnly": true }, "metadata": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "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." }, "name": { "description": "Immutable. The resource name of the Context.", "type": "string" } }, "id": "GoogleCloudAiplatformV1Context" }, "GoogleCloudAiplatformV1ReadTensorboardBlobDataResponse": { "type": "object", "id": "GoogleCloudAiplatformV1ReadTensorboardBlobDataResponse", "properties": { "blobs": { "description": "Blob messages containing blob bytes.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1TensorboardBlob" } } }, "description": "Response message for TensorboardService.ReadTensorboardBlobData." }, "GoogleCloudAiplatformV1CancelTuningJobRequest": { "description": "Request message for GenAiTuningService.CancelTuningJob.", "properties": {}, "type": "object", "id": "GoogleCloudAiplatformV1CancelTuningJobRequest" }, "GenaiVertexV1CodeExecutionCallDelta": { "type": "object", "id": "GenaiVertexV1CodeExecutionCallDelta", "properties": { "arguments": { "$ref": "GenaiVertexV1CodeExecutionCallContentCodeExecutionCallArguments" } } }, "GoogleCloudAiplatformV1SchemaPromptSpecPartList": { "description": "A list of elements and information that make up a portion of prompt.", "properties": { "parts": { "items": { "$ref": "GoogleCloudAiplatformV1Part" }, "type": "array", "description": "A list of elements that can be part of a prompt." } }, "id": "GoogleCloudAiplatformV1SchemaPromptSpecPartList", "type": "object" }, "GoogleCloudAiplatformV1VertexAiSearchConfig": { "id": "GoogleCloudAiplatformV1VertexAiSearchConfig", "properties": { "servingConfig": { "description": "Vertex AI Search Serving Config resource full name. For example, `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}/servingConfigs/{serving_config}` or `projects/{project}/locations/{location}/collections/{collection}/dataStores/{data_store}/servingConfigs/{serving_config}`.", "type": "string" } }, "description": "Config for the Vertex AI Search.", "type": "object" }, "GoogleCloudAiplatformV1FeatureViewDataKeyCompositeKey": { "description": "ID that is comprised from several parts (columns).", "id": "GoogleCloudAiplatformV1FeatureViewDataKeyCompositeKey", "type": "object", "properties": { "parts": { "type": "array", "description": "Parts to construct Entity ID. Should match with the same ID columns as defined in FeatureView in the same order.", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1AvroSource": { "id": "GoogleCloudAiplatformV1AvroSource", "description": "The storage details for Avro input content.", "type": "object", "properties": { "gcsSource": { "$ref": "GoogleCloudAiplatformV1GcsSource", "description": "Required. Google Cloud Storage location." } } }, "GoogleCloudAiplatformV1GenerateInstanceRubricsResponse": { "type": "object", "properties": { "generatedRubrics": { "readOnly": true, "type": "array", "description": "Output only. A list of generated rubrics.", "items": { "$ref": "GoogleCloudAiplatformV1Rubric" } } }, "id": "GoogleCloudAiplatformV1GenerateInstanceRubricsResponse", "description": "Response message for EvaluationService.GenerateInstanceRubrics." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecasting": { "description": "A TrainingJob that trains and uploads an AutoML Forecasting Model.", "properties": { "metadata": { "description": "The metadata information.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingMetadata" }, "inputs": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecastingInputs", "description": "The input parameters of this TrainingJob." } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlForecasting", "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation": { "type": "object", "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.", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation", "properties": { "columnName": { "type": "string" } } }, "GoogleCloudAiplatformV1ProbeHttpHeader": { "description": "HttpHeader describes a custom header to be used in HTTP probes", "type": "object", "id": "GoogleCloudAiplatformV1ProbeHttpHeader", "properties": { "value": { "description": "The header field value", "type": "string" }, "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" } } }, "GoogleCloudAiplatformV1NotebookExecutionJob": { "description": "NotebookExecutionJob represents an instance of a notebook execution.", "properties": { "name": { "type": "string", "description": "Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`", "readOnly": true }, "jobState": { "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" ], "type": "string", "readOnly": true, "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." ] }, "executionUser": { "type": "string", "description": "The user email to run the execution as. Only supported by Colab runtimes." }, "kernelName": { "description": "The name of the kernel to use during notebook execution. If unset, the default kernel is used.", "type": "string" }, "dataformRepositorySource": { "$ref": "GoogleCloudAiplatformV1NotebookExecutionJobDataformRepositorySource", "description": "The Dataform Repository pointing to a single file notebook repository." }, "encryptionSpec": { "$ref": "GoogleCloudAiplatformV1EncryptionSpec", "description": "Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookRuntimeTemplate has an encryption spec." }, "workbenchRuntime": { "$ref": "GoogleCloudAiplatformV1NotebookExecutionJobWorkbenchRuntime", "description": "The Workbench runtime configuration to use for the notebook execution." }, "gcsOutputUri": { "description": "The Cloud Storage location to upload the result to. Format: `gs://bucket-name`", "type": "string" }, "updateTime": { "type": "string", "format": "google-datetime", "readOnly": true, "description": "Output only. Timestamp when this NotebookExecutionJob was most recently updated." }, "status": { "$ref": "GoogleRpcStatus", "description": "Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.", "readOnly": true }, "customEnvironmentSpec": { "description": "The custom compute configuration for an execution job.", "$ref": "GoogleCloudAiplatformV1NotebookExecutionJobCustomEnvironmentSpec" }, "notebookRuntimeTemplateResourceName": { "description": "The NotebookRuntimeTemplate to source compute configuration from.", "type": "string" }, "createTime": { "type": "string", "description": "Output only. Timestamp when this NotebookExecutionJob was created.", "readOnly": true, "format": "google-datetime" }, "labels": { "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.", "type": "object" }, "displayName": { "type": "string", "description": "The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters." }, "serviceAccount": { "type": "string", "description": "The service account to run the execution as." }, "gcsNotebookSource": { "description": "The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`", "$ref": "GoogleCloudAiplatformV1NotebookExecutionJobGcsNotebookSource" }, "directNotebookSource": { "$ref": "GoogleCloudAiplatformV1NotebookExecutionJobDirectNotebookSource", "description": "The contents of an input notebook file." }, "scheduleResourceName": { "type": "string", "description": "The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`" }, "executionTimeout": { "description": "Max running time of the execution job in seconds (default 86400s / 24 hrs).", "type": "string", "format": "google-duration" } }, "type": "object", "id": "GoogleCloudAiplatformV1NotebookExecutionJob" }, "GoogleCloudAiplatformV1ToolParameterKVMatchSpec": { "id": "GoogleCloudAiplatformV1ToolParameterKVMatchSpec", "description": "Spec for tool parameter key value match metric.", "type": "object", "properties": { "useStrictStringMatch": { "type": "boolean", "description": "Optional. Whether to use STRICT string match on parameter values." } } }, "CloudAiLargeModelsVisionGenerateVideoExperimentsLoraConfig": { "description": "Configuration for Multi-LoRA adaptation.", "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsLoraConfig", "type": "object", "properties": { "adapters": { "type": "array", "description": "List of LoRA adapters to apply.", "items": { "$ref": "CloudAiLargeModelsVisionGenerateVideoExperimentsLoraConfigAdapter" } } } }, "GoogleCloudAiplatformV1ListTuningJobsResponse": { "type": "object", "description": "Response message for GenAiTuningService.ListTuningJobs", "id": "GoogleCloudAiplatformV1ListTuningJobsResponse", "properties": { "nextPageToken": { "type": "string", "description": "A token to retrieve the next page of results. Pass this token in a subsequent [GenAiTuningService.ListTuningJobs] call to retrieve the next page of results." }, "tuningJobs": { "type": "array", "description": "The tuning jobs that match the request.", "items": { "$ref": "GoogleCloudAiplatformV1TuningJob" } } } }, "GoogleCloudAiplatformV1SearchNearestEntitiesResponse": { "type": "object", "properties": { "nearestNeighbors": { "description": "The nearest neighbors of the query entity.", "$ref": "GoogleCloudAiplatformV1NearestNeighbors" } }, "id": "GoogleCloudAiplatformV1SearchNearestEntitiesResponse", "description": "Response message for FeatureOnlineStoreService.SearchNearestEntities" }, "GoogleCloudAiplatformV1RemoveContextChildrenResponse": { "properties": {}, "description": "Response message for MetadataService.RemoveContextChildren.", "type": "object", "id": "GoogleCloudAiplatformV1RemoveContextChildrenResponse" }, "GoogleCloudAiplatformV1TrajectorySingleToolUseInstance": { "description": "Spec for TrajectorySingleToolUse instance.", "properties": { "predictedTrajectory": { "description": "Required. Spec for predicted tool call trajectory.", "$ref": "GoogleCloudAiplatformV1Trajectory" } }, "type": "object", "id": "GoogleCloudAiplatformV1TrajectorySingleToolUseInstance" }, "GoogleCloudAiplatformV1ListRagFilesResponse": { "description": "Response message for VertexRagDataService.ListRagFiles.", "type": "object", "properties": { "nextPageToken": { "type": "string", "description": "A token to retrieve the next page of results. Pass to ListRagFilesRequest.page_token to obtain that page." }, "ragFiles": { "type": "array", "description": "List of RagFiles in the requested page.", "items": { "$ref": "GoogleCloudAiplatformV1RagFile" } } }, "id": "GoogleCloudAiplatformV1ListRagFilesResponse" }, "GoogleCloudAiplatformV1SummarizationHelpfulnessInstance": { "properties": { "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" }, "context": { "description": "Required. Text to be summarized.", "type": "string" }, "instruction": { "type": "string", "description": "Optional. Summarization prompt for LLM." }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" } }, "description": "Spec for summarization helpfulness instance.", "type": "object", "id": "GoogleCloudAiplatformV1SummarizationHelpfulnessInstance" }, "CloudAiLargeModelsVisionGenerateVideoExperimentsSuperResConfig": { "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsSuperResConfig", "properties": { "mode": { "enumDescriptions": [ "", "Single-pass 4K UDiT.", "Single-pass 8K UDiT.", "\"8K UDiT, downsampled 2x in the decoder." ], "enum": [ "MODE_UNSPECIFIED", "MODE_4K", "MODE_8K", "MODE_4K_PRO" ], "description": "Super Res mode. Required.", "type": "string" }, "tileSmoothing": { "type": "boolean", "description": "Smooths the seams between the tiles the model upscales separately." } }, "description": "Config for the Pro Super Res upsampling task.", "type": "object" }, "CloudAiLargeModelsVisionGenerateVideoRequestVideo": { "id": "CloudAiLargeModelsVisionGenerateVideoRequestVideo", "properties": { "gcsUri": { "type": "string" }, "blobId": { "type": "string", "description": "Blob ID of the video. This is used for storing large videos in the request." }, "mimeType": { "description": "The MIME type of the content of the video. Only the video in the below listed MIME types are supported. - video/mp4", "type": "string" }, "bytesBase64Encoded": { "type": "string", "description": "Base64 encoded bytes string representing the video." } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation": { "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": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation", "type": "object" }, "GoogleCloudAiplatformV1RetrieveContextsRequest": { "description": "Request message for VertexRagService.RetrieveContexts.", "properties": { "vertexRagStore": { "description": "The data source for Vertex RagStore.", "$ref": "GoogleCloudAiplatformV1RetrieveContextsRequestVertexRagStore" }, "query": { "description": "Required. Single RAG retrieve query.", "$ref": "GoogleCloudAiplatformV1RagQuery" } }, "type": "object", "id": "GoogleCloudAiplatformV1RetrieveContextsRequest" }, "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityView": { "description": "Entity view with Feature values.", "properties": { "entityId": { "description": "ID of the requested entity.", "type": "string" }, "data": { "items": { "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityViewData" }, "type": "array", "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": "object", "id": "GoogleCloudAiplatformV1ReadFeatureValuesResponseEntityView" }, "GoogleCloudAiplatformV1GroundingChunkMaps": { "type": "object", "properties": { "text": { "type": "string", "description": "The text of the place answer." }, "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" }, "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.", "$ref": "GoogleCloudAiplatformV1GroundingChunkMapsPlaceAnswerSources" }, "route": { "$ref": "GoogleCloudAiplatformV1GroundingChunkMapsRoute", "readOnly": true, "description": "Output only. Route information." }, "uri": { "type": "string", "description": "The URI of the place." } }, "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": "GoogleCloudAiplatformV1GroundingChunkMaps" }, "GoogleCloudAiplatformV1SchemaPredictInstanceImageClassificationPredictionInstance": { "description": "Prediction input format for Image Classification.", "id": "GoogleCloudAiplatformV1SchemaPredictInstanceImageClassificationPredictionInstance", "type": "object", "properties": { "mimeType": { "type": "string", "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" }, "content": { "description": "The image bytes or Cloud Storage URI to make the prediction on.", "type": "string" } } }, "GenaiVertexV1RagStoreConfigRagRetrievalConfig": { "properties": { "filter": { "description": "Optional. Config for filters.", "$ref": "GenaiVertexV1RagStoreConfigRagRetrievalConfigFilter" }, "hybridSearch": { "description": "Optional. Config for Hybrid Search.", "$ref": "GenaiVertexV1RagStoreConfigRagRetrievalConfigHybridSearch" }, "ranking": { "$ref": "GenaiVertexV1RagStoreConfigRagRetrievalConfigRanking", "description": "Optional. Config for ranking and reranking." }, "topK": { "format": "int32", "description": "Optional. The number of contexts to retrieve.", "type": "integer" } }, "type": "object", "id": "GenaiVertexV1RagStoreConfigRagRetrievalConfig", "description": "Specifies the context retrieval config." }, "GoogleCloudAiplatformV1PurgeArtifactsResponse": { "description": "Response message for MetadataService.PurgeArtifacts.", "type": "object", "id": "GoogleCloudAiplatformV1PurgeArtifactsResponse", "properties": { "purgeSample": { "type": "array", "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).", "items": { "type": "string" } }, "purgeCount": { "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", "type": "string" } } }, "GoogleCloudAiplatformV1ExternalApiElasticSearchParams": { "properties": { "numHits": { "format": "int32", "description": "Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.", "type": "integer" }, "index": { "description": "The ElasticSearch index to use.", "type": "string" }, "searchTemplate": { "type": "string", "description": "The ElasticSearch search template to use." } }, "id": "GoogleCloudAiplatformV1ExternalApiElasticSearchParams", "type": "object", "description": "The search parameters to use for the ELASTIC_SEARCH spec." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation": { "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.", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation", "properties": { "columnName": { "type": "string" } } }, "GoogleCloudAiplatformV1SummarizationQualityInstance": { "description": "Spec for summarization quality instance.", "id": "GoogleCloudAiplatformV1SummarizationQualityInstance", "type": "object", "properties": { "context": { "description": "Required. Text to be summarized.", "type": "string" }, "reference": { "description": "Optional. Ground truth used to compare against the prediction.", "type": "string" }, "prediction": { "description": "Required. Output of the evaluated model.", "type": "string" }, "instruction": { "type": "string", "description": "Required. Summarization prompt for LLM." } } }, "GoogleCloudAiplatformV1MemoryGenerationTriggerConfigGenerationTriggerRule": { "type": "object", "description": "Represents the active rule that determines when to flush the buffer.", "id": "GoogleCloudAiplatformV1MemoryGenerationTriggerConfigGenerationTriggerRule", "properties": { "fixedInterval": { "format": "google-duration", "description": "Optional. Specifies to trigger generation at a fixed interval. The duration must have a minute-level granularity.", "type": "string" }, "idleDuration": { "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.", "type": "string" }, "eventCount": { "format": "int32", "type": "integer", "description": "Optional. Specifies to trigger generation when the event count reaches this limit." }, "overlapEventCount": { "description": "Optional. Re-include the last N already-processed events in the next window.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1FunctionResponseFileData": { "description": "URI based data for function response.", "properties": { "mimeType": { "type": "string", "description": "Required. The IANA standard MIME type of the source data." }, "fileUri": { "description": "Required. URI.", "type": "string" }, "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" } }, "id": "GoogleCloudAiplatformV1FunctionResponseFileData", "type": "object" }, "GoogleCloudAiplatformV1AutomaticResources": { "description": "A description of resources that to large degree are decided by Agent Platform, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines.", "properties": { "minReplicaCount": { "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", "type": "integer" }, "maxReplicaCount": { "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, a no upper bound for scaling under heavy traffic will be assume, though Agent Platform may be unable to scale beyond certain replica number.", "type": "integer" } }, "type": "object", "id": "GoogleCloudAiplatformV1AutomaticResources" }, "GoogleCloudAiplatformV1CoherenceResult": { "description": "Spec for coherence result.", "type": "object", "properties": { "confidence": { "format": "float", "description": "Output only. Confidence for coherence score.", "readOnly": true, "type": "number" }, "explanation": { "readOnly": true, "type": "string", "description": "Output only. Explanation for coherence score." }, "score": { "type": "number", "readOnly": true, "description": "Output only. Coherence score.", "format": "float" } }, "id": "GoogleCloudAiplatformV1CoherenceResult" }, "GoogleCloudAiplatformV1TrajectoryInOrderMatchInstance": { "type": "object", "properties": { "predictedTrajectory": { "$ref": "GoogleCloudAiplatformV1Trajectory", "description": "Required. Spec for predicted tool call trajectory." }, "referenceTrajectory": { "description": "Required. Spec for reference tool call trajectory.", "$ref": "GoogleCloudAiplatformV1Trajectory" } }, "id": "GoogleCloudAiplatformV1TrajectoryInOrderMatchInstance", "description": "Spec for TrajectoryInOrderMatch instance." }, "GoogleCloudAiplatformV1LossAnalysisConfig": { "properties": { "metric": { "description": "Required. The metric to analyze (e.g., \"tool_use_quality\"). This filters the EvaluationItems in the EvalSet to only those where EvaluationResult.metric matches this value.", "type": "string" }, "candidate": { "type": "string", "description": "Required. The candidate model/agent to analyze (e.g., \"gemini-3.0-pro\"). This targets the specific CandidateResult within the EvaluationResult." } }, "description": "Configuration for the loss analysis job.", "type": "object", "id": "GoogleCloudAiplatformV1LossAnalysisConfig" }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry", "type": "object", "properties": { "diceScoreCoefficient": { "type": "number", "format": "float", "description": "DSC or the F1 score, The harmonic mean of recall and precision." }, "recall": { "type": "number", "description": "Recall (True Positive Rate) for the given confidence threshold.", "format": "float" }, "iouScore": { "format": "float", "type": "number", "description": "The intersection-over-union score. The measure of overlap of the annotation's category mask with ground truth category mask on the DataItem." }, "confidenceThreshold": { "description": "Metrics are computed with an assumption that the model never returns predictions with score lower than this value.", "type": "number", "format": "float" }, "precision": { "description": "Precision for the given confidence threshold.", "format": "float", "type": "number" }, "confusionMatrix": { "description": "Confusion matrix for the given confidence threshold.", "$ref": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix" } } }, "GoogleCloudAiplatformV1SchemaTextSentimentAnnotation": { "id": "GoogleCloudAiplatformV1SchemaTextSentimentAnnotation", "description": "Annotation details specific to text sentiment.", "type": "object", "properties": { "sentimentMax": { "format": "int32", "type": "integer", "description": "The sentiment max score for text." }, "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" }, "sentiment": { "description": "The sentiment score for text.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchInput": { "type": "object", "properties": { "metricSpec": { "$ref": "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchSpec", "description": "Required. Spec for TrajectoryAnyOrderMatch metric." }, "instances": { "items": { "$ref": "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchInstance" }, "description": "Required. Repeated TrajectoryAnyOrderMatch instance.", "type": "array" } }, "id": "GoogleCloudAiplatformV1TrajectoryAnyOrderMatchInput", "description": "Instances and metric spec for TrajectoryAnyOrderMatch metric." }, "GoogleCloudAiplatformV1Scheduling": { "type": "object", "id": "GoogleCloudAiplatformV1Scheduling", "properties": { "maxWaitDuration": { "type": "string", "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" }, "strategy": { "enum": [ "STRATEGY_UNSPECIFIED", "ON_DEMAND", "LOW_COST", "STANDARD", "SPOT", "FLEX_START" ], "type": "string", "description": "Optional. This determines which type of scheduling strategy to use.", "enumDeprecated": [ false, true, true, false, false, false ], "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." ] }, "timeout": { "description": "Optional. The maximum job running time. The default is 7 days.", "type": "string", "format": "google-duration" }, "disableRetries": { "type": "boolean", "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." }, "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" } }, "description": "All parameters related to queuing and scheduling of custom jobs." }, "GoogleCloudAiplatformV1MigratableResourceDataLabelingDataset": { "type": "object", "description": "Represents one Dataset in datalabeling.googleapis.com.", "id": "GoogleCloudAiplatformV1MigratableResourceDataLabelingDataset", "properties": { "datasetDisplayName": { "description": "The Dataset's display name in datalabeling.googleapis.com.", "type": "string" }, "dataset": { "type": "string", "description": "Full resource name of data labeling Dataset. Format: `projects/{project}/datasets/{dataset}`." }, "dataLabelingAnnotatedDatasets": { "description": "The migratable AnnotatedDataset in datalabeling.googleapis.com belongs to the data labeling Dataset.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset" } } } }, "GoogleCloudAiplatformV1StudySpecParameterSpec": { "id": "GoogleCloudAiplatformV1StudySpecParameterSpec", "properties": { "categoricalValueSpec": { "description": "The value spec for a 'CATEGORICAL' parameter.", "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpec" }, "discreteValueSpec": { "description": "The value spec for a 'DISCRETE' parameter.", "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpec" }, "scaleType": { "enum": [ "SCALE_TYPE_UNSPECIFIED", "UNIT_LINEAR_SCALE", "UNIT_LOG_SCALE", "UNIT_REVERSE_LOG_SCALE" ], "description": "How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters.", "enumDescriptions": [ "By default, no scaling is applied.", "Scales the feasible space to (0, 1) linearly.", "Scales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.", "Scales the feasible space \"reverse\" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive." ], "type": "string" }, "doubleValueSpec": { "description": "The value spec for a 'DOUBLE' parameter.", "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpec" }, "parameterId": { "description": "Required. The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs.", "type": "string" }, "integerValueSpec": { "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpec", "description": "The value spec for an 'INTEGER' parameter." }, "conditionalParameterSpecs": { "type": "array", "description": "A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition. If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition.", "items": { "$ref": "GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpec" } } }, "type": "object", "description": "Represents a single parameter to optimize." }, "GoogleCloudAiplatformV1CoherenceInstance": { "id": "GoogleCloudAiplatformV1CoherenceInstance", "type": "object", "description": "Spec for coherence instance.", "properties": { "prediction": { "type": "string", "description": "Required. Output of the evaluated model." } } }, "GoogleCloudAiplatformV1CustomOutputFormatConfig": { "id": "GoogleCloudAiplatformV1CustomOutputFormatConfig", "type": "object", "properties": { "returnRawOutput": { "type": "boolean", "description": "Optional. Whether to return raw output." } }, "description": "Spec for custom output format configuration." }, "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualitySpec": { "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.", "type": "integer", "format": "int32" } }, "type": "object", "id": "GoogleCloudAiplatformV1PairwiseQuestionAnsweringQualitySpec", "description": "Spec for pairwise question answering quality score metric." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs": { "properties": { "baseModelId": { "type": "string", "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." }, "modelType": { "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." ], "enum": [ "MODEL_TYPE_UNSPECIFIED", "CLOUD_HIGH_ACCURACY_1", "CLOUD_LOW_ACCURACY_1", "MOBILE_TF_LOW_LATENCY_1" ], "type": "string" }, "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)." } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs", "type": "object" }, "GoogleCloudAiplatformV1Int64Array": { "id": "GoogleCloudAiplatformV1Int64Array", "type": "object", "description": "A list of int64 values.", "properties": { "values": { "description": "A list of int64 values.", "type": "array", "items": { "format": "int64", "type": "string" } } } }, "GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProvider": { "type": "object", "id": "GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProvider", "properties": { "allowedIssuers": { "items": { "type": "string" }, "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" }, "audiences": { "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.", "type": "array" } }, "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)." }, "GoogleCloudAiplatformV1GeminiPreferenceExampleCompletion": { "id": "GoogleCloudAiplatformV1GeminiPreferenceExampleCompletion", "type": "object", "description": "Completion and its preference score.", "properties": { "completion": { "$ref": "GoogleCloudAiplatformV1Content", "description": "Single turn completion for the given prompt." }, "score": { "type": "number", "format": "float", "description": "The score for the given completion." } } }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation", "properties": { "categorical": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation" }, "text": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation" }, "numeric": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation" }, "timestamp": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation" }, "auto": { "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation" } }, "type": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextClassification": { "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextClassification", "type": "object", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs" } }, "description": "A TrainingJob that trains and uploads an AutoML Text Classification Model." }, "GoogleCloudAiplatformV1SchemaModelevaluationMetricsGeneralTextGenerationEvaluationMetrics": { "id": "GoogleCloudAiplatformV1SchemaModelevaluationMetricsGeneralTextGenerationEvaluationMetrics", "type": "object", "properties": { "bleu": { "type": "number", "description": "BLEU (bilingual evaluation understudy) scores based on sacrebleu implementation.", "format": "float" }, "rougeLSum": { "type": "number", "description": "ROUGE-L (Longest Common Subsequence) scoring at summary level.", "format": "float" } } }, "CloudAiLargeModelsVisionGenerateVideoExperimentsVESchedulingConfig": { "properties": { "enableRetry": { "type": "boolean", "description": "Optional. If true, enable retries on transient errors with default backoff." } }, "id": "CloudAiLargeModelsVisionGenerateVideoExperimentsVESchedulingConfig", "type": "object", "description": "Scheduling configuration for Veo Experimental." }, "GoogleCloudAiplatformV1PurgeExecutionsResponse": { "description": "Response message for MetadataService.PurgeExecutions.", "properties": { "purgeCount": { "format": "int64", "description": "The number of Executions that this request deleted (or, if `force` is false, the number of Executions that will be deleted). This can be an estimate.", "type": "string" }, "purgeSample": { "items": { "type": "string" }, "type": "array", "description": "A sample of the Execution names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer)." } }, "type": "object", "id": "GoogleCloudAiplatformV1PurgeExecutionsResponse" }, "GoogleCloudAiplatformV1AddExecutionEventsRequest": { "id": "GoogleCloudAiplatformV1AddExecutionEventsRequest", "properties": { "events": { "description": "The Events to create and add.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Event" } } }, "type": "object", "description": "Request message for MetadataService.AddExecutionEvents." }, "GenaiVertexV1ServerToolCallDelta": { "properties": { "googleMapsCall": { "$ref": "GenaiVertexV1GoogleMapsCallDelta" }, "googleSearchCall": { "$ref": "GenaiVertexV1GoogleSearchCallDelta" }, "retrievalCall": { "$ref": "GenaiVertexV1RetrievalCallDelta" }, "urlContextCall": { "$ref": "GenaiVertexV1UrlContextCallDelta" }, "processingCall": { "$ref": "GenaiVertexV1ProcessingCallDelta" }, "codeExecutionCall": { "$ref": "GenaiVertexV1CodeExecutionCallDelta" }, "fileSearchCall": { "$ref": "GenaiVertexV1FileSearchCallDelta" }, "signature": { "description": "A signature hash for backend validation.", "format": "byte", "type": "string" } }, "id": "GenaiVertexV1ServerToolCallDelta", "type": "object" }, "GenaiVertexV1InteractionCreatedSseEvent": { "properties": { "interaction": { "description": "Required. Partial interaction resource emitted when the stream is created.", "$ref": "GenaiVertexV1Interaction" } }, "description": "Server response confirming that a new interaction was created.", "id": "GenaiVertexV1InteractionCreatedSseEvent", "type": "object" }, "GoogleCloudAiplatformV1RagRetrievalConfigRanking": { "type": "object", "properties": { "llmRanker": { "description": "Optional. Config for LlmRanker.", "$ref": "GoogleCloudAiplatformV1RagRetrievalConfigRankingLlmRanker" }, "rankService": { "description": "Optional. Config for Rank Service.", "$ref": "GoogleCloudAiplatformV1RagRetrievalConfigRankingRankService" } }, "id": "GoogleCloudAiplatformV1RagRetrievalConfigRanking", "description": "Config for ranking and reranking." }, "GoogleCloudAiplatformV1SandboxEnvironmentSpecShellEnvironment": { "description": "The shell environment.", "properties": {}, "type": "object", "id": "GoogleCloudAiplatformV1SandboxEnvironmentSpecShellEnvironment" }, "GenaiVertexV1SpeechConfig": { "id": "GenaiVertexV1SpeechConfig", "type": "object", "description": "The configuration for speech interaction.", "properties": { "voice": { "description": "The voice of the speaker.", "type": "string" }, "language": { "description": "The language of the speech.", "type": "string" }, "speaker": { "description": "The speaker's name, it should match the speaker name given in the prompt.", "type": "string" } } }, "GoogleCloudAiplatformV1ListOptimalTrialsRequest": { "type": "object", "properties": {}, "description": "Request message for VizierService.ListOptimalTrials.", "id": "GoogleCloudAiplatformV1ListOptimalTrialsRequest" }, "GoogleCloudAiplatformV1SchemaPredictPredictionVideoActionRecognitionPredictionResult": { "id": "GoogleCloudAiplatformV1SchemaPredictPredictionVideoActionRecognitionPredictionResult", "properties": { "confidence": { "description": "The Model's confidence in correction of this prediction, higher value means higher confidence.", "type": "number", "format": "float" }, "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." }, "displayName": { "description": "The display name of the AnnotationSpec that had been identified.", "type": "string" }, "id": { "type": "string", "description": "The resource ID of the AnnotationSpec that had been identified." }, "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" } }, "type": "object", "description": "Prediction output format for Video Action Recognition." }, "GoogleCloudAiplatformV1SandboxEnvironment": { "id": "GoogleCloudAiplatformV1SandboxEnvironment", "description": "SandboxEnvironment is a containerized environment that provides a customizable secure execution runtime for AI agents.", "properties": { "displayName": { "description": "Required. The display name of the SandboxEnvironment.", "type": "string" }, "owner": { "type": "string", "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." }, "expireTime": { "type": "string", "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.", "format": "google-datetime" }, "ttl": { "format": "google-duration", "type": "string", "description": "Optional. Input only. The TTL for the sandbox environment. The expiration time is computed: now + TTL." }, "updateTime": { "format": "google-datetime", "description": "Output only. The timestamp when this SandboxEnvironment was most recently updated.", "readOnly": true, "type": "string" }, "latestSandboxEnvironmentSnapshot": { "readOnly": true, "description": "Output only. The resource name of the latest snapshot taken for this SandboxEnvironment.", "type": "string" }, "spec": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentSpec", "description": "Optional. The configuration of the SandboxEnvironment." }, "state": { "description": "Output only. The runtime state of the SandboxEnvironment.", "enum": [ "STATE_UNSPECIFIED", "STATE_PROVISIONING", "STATE_RUNNING", "STATE_DEPROVISIONING", "STATE_TERMINATED", "STATE_DELETED", "STATE_PAUSED", "STATE_PAUSING", "STATE_RESUMING", "STATE_STOPPING" ], "type": "string", "readOnly": true, "enumDescriptions": [ "The default value. This value is unused.", "Runtime resources are being allocated for the sandbox environment.", "Sandbox runtime is ready for serving.", "Sandbox runtime is halted, performing tear down tasks.", "Sandbox has terminated with underlying runtime failure.", "Sandbox runtime has been deleted.", "Sandbox runtime is paused.", "Sandbox runtime is pausing.", "Sandbox runtime is resuming.", "Sandbox runtime is stopping." ] }, "connectionInfo": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentConnectionInfo", "readOnly": true, "description": "Output only. The connection information of the SandboxEnvironment." }, "name": { "type": "string", "description": "Identifier. The name of the SandboxEnvironment." }, "createTime": { "type": "string", "description": "Output only. The timestamp when this SandboxEnvironment was created.", "format": "google-datetime", "readOnly": true }, "sandboxEnvironmentTemplate": { "description": "Optional. The name of the SandboxEnvironmentTemplate specified in the parent Agent Engine resource that this SandboxEnvironment is created from.", "type": "string" }, "sandboxEnvironmentSnapshot": { "type": "string", "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": "object" }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextExtraction": { "description": "A TrainingJob that trains and uploads an AutoML Text Extraction Model.", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs" } }, "type": "object", "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTextExtraction" }, "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecDeveloperConnectSource": { "type": "object", "id": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecDeveloperConnectSource", "description": "Specifies source code to be fetched from a Git repository managed through the Developer Connect service.", "properties": { "config": { "$ref": "GoogleCloudAiplatformV1ReasoningEngineSpecSourceCodeSpecDeveloperConnectConfig", "description": "Required. The Developer Connect configuration that defines the specific repository, revision, and directory to use as the source code root." } } }, "GoogleCloudAiplatformV1StopTrialRequest": { "properties": {}, "description": "Request message for VizierService.StopTrial.", "id": "GoogleCloudAiplatformV1StopTrialRequest", "type": "object" }, "CloudAiLargeModelsVisionGenerateVideoResponseVideo": { "type": "object", "properties": { "experimentsResponse": { "description": "Optional response returned from experimental requests.", "$ref": "CloudAiLargeModelsVisionExperimentsResponse" }, "bytesBase64Encoded": { "type": "string", "description": "Base64 encoded bytes string representing the video." }, "experimentsMetadata": { "deprecated": true, "$ref": "CloudAiLargeModelsVisionGenerateVideoExperiments", "description": "Optional metadata returned from experimental requests. Likely only includes the rewritten prompt chunks." }, "gcsUri": { "description": "Cloud Storage URI where the generated video is written.", "type": "string" }, "mimeType": { "description": "The MIME type of the content of the video. - video/mp4", "type": "string" } }, "id": "CloudAiLargeModelsVisionGenerateVideoResponseVideo" }, "GoogleCloudAiplatformV1MeasurementMetric": { "properties": { "metricId": { "description": "Output only. The ID of the Metric. The Metric should be defined in StudySpec's Metrics.", "readOnly": true, "type": "string" }, "value": { "type": "number", "readOnly": true, "format": "double", "description": "Output only. The value for this metric." } }, "description": "A message representing a metric in the measurement.", "type": "object", "id": "GoogleCloudAiplatformV1MeasurementMetric" }, "GoogleCloudAiplatformV1RebaseTunedModelRequest": { "type": "object", "description": "Request message for GenAiTuningService.RebaseTunedModel.", "properties": { "artifactDestination": { "description": "Optional. The Google Cloud Storage location to write the artifacts to.", "$ref": "GoogleCloudAiplatformV1GcsDestination" }, "tunedModelRef": { "$ref": "GoogleCloudAiplatformV1TunedModelRef", "description": "Required. A reference to the tuned model to rebase." }, "tuningJob": { "description": "Optional. The tuning job to be updated. Users can use this field to overwrite tuning configs.", "$ref": "GoogleCloudAiplatformV1TuningJob" }, "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" } }, "id": "GoogleCloudAiplatformV1RebaseTunedModelRequest" }, "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis": { "id": "GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis", "type": "object", "properties": { "monitoringIntervalDays": { "format": "int32", "type": "integer", "description": "Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days." }, "disabled": { "type": "boolean", "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." }, "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" } }, "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." }, "GoogleCloudAiplatformV1LLMBasedMetricSpec": { "properties": { "resultParserConfig": { "description": "Optional. The parser config for the metric result.", "$ref": "GoogleCloudAiplatformV1EvaluationParserConfig" }, "rubricGroupKey": { "type": "string", "description": "Use a pre-defined group of rubrics associated with the input. Refers to a key in the rubric_groups map of EvaluationInstance." }, "metricPromptTemplate": { "type": "string", "description": "Required. Template for the prompt sent to the judge model." }, "judgeAutoraterConfig": { "description": "Optional. Optional configuration for the judge LLM (Autorater).", "$ref": "GoogleCloudAiplatformV1AutoraterConfig" }, "rubricGenerationSpec": { "description": "Dynamically generate rubrics using this specification.", "$ref": "GoogleCloudAiplatformV1RubricGenerationSpec" }, "additionalConfig": { "type": "object", "description": "Optional. Optional additional configuration for the metric.", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "systemInstruction": { "description": "Optional. System instructions for the judge model.", "type": "string" }, "predefinedRubricGenerationSpec": { "description": "Dynamically generate rubrics using a predefined spec.", "$ref": "GoogleCloudAiplatformV1PredefinedMetricSpec" } }, "description": "Specification for an LLM based metric.", "type": "object", "id": "GoogleCloudAiplatformV1LLMBasedMetricSpec" }, "GoogleCloudAiplatformV1ListSavedQueriesResponse": { "id": "GoogleCloudAiplatformV1ListSavedQueriesResponse", "properties": { "nextPageToken": { "type": "string", "description": "The standard List next-page token." }, "savedQueries": { "type": "array", "description": "A list of SavedQueries that match the specified filter in the request.", "items": { "$ref": "GoogleCloudAiplatformV1SavedQuery" } } }, "type": "object", "description": "Response message for DatasetService.ListSavedQueries." }, "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassification": { "type": "object", "properties": { "inputs": { "description": "The input parameters of this TrainingJob.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs" }, "metadata": { "description": "The metadata information.", "$ref": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata" } }, "id": "GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlImageClassification", "description": "A TrainingJob that trains and uploads an AutoML Image Classification Model." }, "GoogleCloudAiplatformV1StratifiedSplit": { "type": "object", "id": "GoogleCloudAiplatformV1StratifiedSplit", "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": { "testFraction": { "format": "double", "description": "The fraction of the input data that is to be used to evaluate the Model.", "type": "number" }, "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": { "description": "The fraction of the input data that is to be used to train the Model.", "type": "number", "format": "double" }, "validationFraction": { "format": "double", "type": "number", "description": "The fraction of the input data that is to be used to validate the Model." } } }, "GenaiVertexV1ModelOutputStep": { "type": "object", "properties": { "error": { "description": "The error result of the operation in case of failure or cancellation.", "deprecated": true, "$ref": "GoogleRpcStatus" }, "content": { "type": "array", "items": { "$ref": "GenaiVertexV1Content" } } }, "description": "Output generated by the model.", "id": "GenaiVertexV1ModelOutputStep" }, "GoogleCloudAiplatformV1FractionSplit": { "type": "object", "properties": { "testFraction": { "format": "double", "description": "The fraction of the input data that is to be used to evaluate 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" }, "trainingFraction": { "type": "number", "format": "double", "description": "The fraction of the input data that is to be used to train the Model." } }, "id": "GoogleCloudAiplatformV1FractionSplit", "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." }, "GoogleCloudAiplatformV1AssignNotebookRuntimeRequest": { "description": "Request message for NotebookService.AssignNotebookRuntime.", "type": "object", "id": "GoogleCloudAiplatformV1AssignNotebookRuntimeRequest", "properties": { "notebookRuntimeTemplate": { "type": "string", "description": "Required. The resource name of the NotebookRuntimeTemplate based on which a NotebookRuntime will be assigned (reuse or create a new one)." }, "notebookRuntimeId": { "type": "string", "description": "Optional. User specified ID for the notebook runtime." }, "notebookRuntime": { "description": "Required. Provide runtime specific information (e.g. runtime owner, notebook id) used for NotebookRuntime assignment.", "$ref": "GoogleCloudAiplatformV1NotebookRuntime" } } }, "GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfig": { "id": "GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfig", "properties": { "sampleRate": { "description": "Sample rate (0, 1]", "type": "number", "format": "double" } }, "type": "object", "description": "Requests are randomly selected." }, "GoogleCloudAiplatformV1BatchReadFeatureValuesRequest": { "properties": { "bigqueryReadInstances": { "$ref": "GoogleCloudAiplatformV1BigQuerySource", "description": "Similar to csv_read_instances, but from BigQuery source." }, "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.", "type": "string", "format": "google-datetime" }, "passThroughFields": { "type": "array", "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.", "items": { "$ref": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestPassThroughField" } }, "csvReadInstances": { "description": "Each read instance consists of exactly one read timestamp and one or more entity IDs identifying entities of the corresponding EntityTypes whose Features are requested. Each output instance contains Feature values of requested entities concatenated together as of the read time. An example read instance may be `foo_entity_id, bar_entity_id, 2020-01-01T10:00:00.123Z`. An example output instance may be `foo_entity_id, bar_entity_id, 2020-01-01T10:00:00.123Z, foo_entity_feature1_value, bar_entity_feature2_value`. Timestamp in each read instance must be millisecond-aligned. `csv_read_instances` are read instances stored in a plain-text CSV file. The header should be: [ENTITY_TYPE_ID1], [ENTITY_TYPE_ID2], ..., timestamp The columns can be in any order. Values in the timestamp column must use the RFC 3339 format, e.g. `2012-07-30T10:43:17.123Z`.", "$ref": "GoogleCloudAiplatformV1CsvSource" }, "entityTypeSpecs": { "description": "Required. Specifies EntityType grouping Features to read values of and settings.", "items": { "$ref": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequestEntityTypeSpec" }, "type": "array" }, "destination": { "description": "Required. Specifies output location and format.", "$ref": "GoogleCloudAiplatformV1FeatureValueDestination" } }, "description": "Request message for FeaturestoreService.BatchReadFeatureValues.", "id": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequest", "type": "object" }, "GoogleCloudAiplatformV1EnvVar": { "id": "GoogleCloudAiplatformV1EnvVar", "properties": { "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" }, "name": { "description": "Required. Name of the environment variable. Must be a valid C identifier.", "type": "string" } }, "type": "object", "description": "Represents an environment variable present in a Container or Python Module." }, "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityNumericPredicate": { "type": "object", "properties": { "comparisonOperator": { "type": "string", "enum": [ "COMPARISON_OPERATOR_UNSPECIFIED", "LESS", "LESS_OR_EQUAL", "EQUAL", "NOT_EQUAL", "GREATER_OR_EQUAL", "GREATER" ], "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." ], "description": "Required. The comparison operator to apply." }, "value": { "type": "number", "format": "float", "description": "Required. The value to compare against." } }, "description": "Defines a predicate for filtering based on a numeric value.", "id": "GoogleCloudAiplatformV1OnlineEvaluatorCloudObservabilityNumericPredicate" }, "GoogleCloudAiplatformV1ListPipelineJobsResponse": { "type": "object", "description": "Response message for PipelineService.ListPipelineJobs", "id": "GoogleCloudAiplatformV1ListPipelineJobsResponse", "properties": { "nextPageToken": { "description": "A token to retrieve the next page of results. Pass to ListPipelineJobsRequest.page_token to obtain that page.", "type": "string" }, "pipelineJobs": { "items": { "$ref": "GoogleCloudAiplatformV1PipelineJob" }, "type": "array", "description": "List of PipelineJobs in the requested page." } } }, "GoogleCloudAiplatformV1ListFeatureViewSyncsResponse": { "id": "GoogleCloudAiplatformV1ListFeatureViewSyncsResponse", "type": "object", "properties": { "nextPageToken": { "type": "string", "description": "A token, which can be sent as ListFeatureViewSyncsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages." }, "featureViewSyncs": { "description": "The FeatureViewSyncs matching the request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1FeatureViewSync" } } }, "description": "Response message for FeatureOnlineStoreAdminService.ListFeatureViewSyncs." }, "GoogleCloudAiplatformV1SchemaTextDatasetMetadata": { "description": "The metadata of Datasets that contain Text DataItems.", "id": "GoogleCloudAiplatformV1SchemaTextDatasetMetadata", "type": "object", "properties": { "dataItemSchemaUri": { "type": "string", "description": "Points to a YAML file stored on Google Cloud Storage describing payload of the Text DataItems that belong to this Dataset." }, "gcsBucket": { "type": "string", "description": "Google Cloud Storage Bucket name that contains the blob data of this Dataset." } } }, "GoogleCloudAiplatformV1EntityIdSelector": { "description": "Selector for entityId. Getting ids from the given source.", "id": "GoogleCloudAiplatformV1EntityIdSelector", "properties": { "entityIdField": { "type": "string", "description": "Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id." }, "csvSource": { "$ref": "GoogleCloudAiplatformV1CsvSource", "description": "Source of Csv" } }, "type": "object" }, "GoogleCloudAiplatformV1FetchFeatureValuesRequest": { "id": "GoogleCloudAiplatformV1FetchFeatureValuesRequest", "type": "object", "properties": { "dataKey": { "description": "Optional. The request key to fetch feature values for.", "$ref": "GoogleCloudAiplatformV1FeatureViewDataKey" }, "dataFormat": { "enum": [ "FEATURE_VIEW_DATA_FORMAT_UNSPECIFIED", "KEY_VALUE", "PROTO_STRUCT" ], "description": "Optional. Response data format. If not set, FeatureViewDataFormat.KEY_VALUE 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.FetchFeatureValues. All the features under the requested feature view will be returned." }, "GoogleCloudAiplatformV1CreateDeploymentResourcePoolRequest": { "type": "object", "id": "GoogleCloudAiplatformV1CreateDeploymentResourcePoolRequest", "description": "Request message for CreateDeploymentResourcePool method.", "properties": { "deploymentResourcePool": { "description": "Required. The DeploymentResourcePool to create.", "$ref": "GoogleCloudAiplatformV1DeploymentResourcePool" }, "deploymentResourcePoolId": { "type": "string", "description": "Required. The ID to use for the DeploymentResourcePool, which will become the final component of the DeploymentResourcePool's resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`." } } }, "GoogleCloudAiplatformV1EncryptionSpec": { "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" } }, "id": "GoogleCloudAiplatformV1EncryptionSpec", "description": "Represents a customer-managed encryption key specification that can be applied to a Vertex AI resource.", "type": "object" }, "GoogleCloudAiplatformV1GdcConfig": { "description": "Google Distributed Cloud (GDC) config.", "id": "GoogleCloudAiplatformV1GdcConfig", "properties": { "zone": { "description": "GDC zone. A cluster will be designated for the Vertex AI workload in this zone.", "type": "string" } }, "type": "object" }, "GoogleCloudAiplatformV1UploadModelOperationMetadata": { "description": "Details of ModelService.UploadModel operation.", "type": "object", "properties": { "genericMetadata": { "description": "The common part of the operation metadata.", "$ref": "GoogleCloudAiplatformV1GenericOperationMetadata" } }, "id": "GoogleCloudAiplatformV1UploadModelOperationMetadata" }, "GoogleCloudAiplatformV1StructFieldValue": { "id": "GoogleCloudAiplatformV1StructFieldValue", "properties": { "value": { "$ref": "GoogleCloudAiplatformV1FeatureValue", "description": "The value for this field." }, "name": { "description": "Name of the field in the struct feature.", "type": "string" } }, "type": "object", "description": "One field of a Struct (or object) type feature value." }, "GoogleCloudAiplatformV1ToolGoogleSearchWebSearch": { "properties": {}, "id": "GoogleCloudAiplatformV1ToolGoogleSearchWebSearch", "description": "Standard web search for grounding and related configurations. Only text results are returned.", "type": "object" }, "GoogleCloudAiplatformV1ResourceRuntimeSpec": { "id": "GoogleCloudAiplatformV1ResourceRuntimeSpec", "type": "object", "properties": { "raySpec": { "$ref": "GoogleCloudAiplatformV1RaySpec", "description": "Optional. Ray cluster configuration. Required when creating a dedicated RayCluster on the PersistentResource." }, "serviceAccountSpec": { "$ref": "GoogleCloudAiplatformV1ServiceAccountSpec", "description": "Optional. Configure the use of workload identity on the PersistentResource" } }, "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." }, "GoogleCloudAiplatformV1ListMetadataStoresResponse": { "type": "object", "properties": { "metadataStores": { "type": "array", "description": "The MetadataStores found for the Location.", "items": { "$ref": "GoogleCloudAiplatformV1MetadataStore" } }, "nextPageToken": { "type": "string", "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." } }, "description": "Response message for MetadataService.ListMetadataStores.", "id": "GoogleCloudAiplatformV1ListMetadataStoresResponse" }, "GoogleCloudAiplatformV1Presets": { "properties": { "modality": { "enumDescriptions": [ "Should not be set. Added as a recommended best practice for enums", "IMAGE modality", "TEXT modality", "TABULAR 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" }, "query": { "description": "Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`.", "enumDescriptions": [ "More precise neighbors as a trade-off against slower response.", "Faster response as a trade-off against less precise neighbors." ], "type": "string", "enum": [ "PRECISE", "FAST" ] } }, "type": "object", "description": "Preset configuration for example-based explanations", "id": "GoogleCloudAiplatformV1Presets" }, "GoogleCloudAiplatformV1RubricBasedInstructionFollowingSpec": { "type": "object", "id": "GoogleCloudAiplatformV1RubricBasedInstructionFollowingSpec", "properties": {}, "description": "Spec for RubricBasedInstructionFollowing metric - returns rubrics and verdicts corresponding to rubrics along with overall score." }, "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessSpec": { "description": "Spec for question answering helpfulness metric.", "properties": { "useReference": { "type": "boolean", "description": "Optional. Whether to use instance.reference to compute question answering helpfulness." }, "version": { "type": "integer", "format": "int32", "description": "Optional. Which version to use for evaluation." } }, "type": "object", "id": "GoogleCloudAiplatformV1QuestionAnsweringHelpfulnessSpec" }, "GoogleCloudAiplatformV1SchemaTimeSegment": { "properties": { "startTimeOffset": { "format": "google-duration", "type": "string", "description": "Start of the time segment (inclusive), represented as the duration since the start of the DataItem." }, "endTimeOffset": { "type": "string", "format": "google-duration", "description": "End of the time segment (exclusive), represented as the duration since the start of the DataItem." } }, "description": "A time period inside of a DataItem that has a time dimension (e.g. video).", "id": "GoogleCloudAiplatformV1SchemaTimeSegment", "type": "object" }, "GoogleCloudAiplatformV1NotebookExecutionJobGcsNotebookSource": { "description": "The Cloud Storage uri for the input notebook.", "properties": { "uri": { "type": "string", "description": "The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`" }, "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" } }, "id": "GoogleCloudAiplatformV1NotebookExecutionJobGcsNotebookSource", "type": "object" }, "GoogleCloudAiplatformV1PostStartupScriptConfig": { "id": "GoogleCloudAiplatformV1PostStartupScriptConfig", "description": "Post startup script config.", "properties": { "postStartupScriptBehavior": { "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." ], "description": "Optional. Post startup script behavior that defines download and execution behavior." }, "postStartupScript": { "type": "string", "description": "Optional. Post startup script to run after runtime is started." }, "postStartupScriptUrl": { "type": "string", "description": "Optional. Post startup script url to download. Example: `gs://bucket/script.sh`" } }, "type": "object" }, "GoogleCloudAiplatformV1RagVectorDbConfigRagManagedDbANN": { "properties": { "leafCount": { "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", "format": "int32" }, "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" } }, "type": "object", "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": "GoogleCloudAiplatformV1RagVectorDbConfigRagManagedDbANN" }, "GoogleCloudAiplatformV1SchemaPromptSpecPromptMessage": { "id": "GoogleCloudAiplatformV1SchemaPromptSpecPromptMessage", "description": "The prompt message that aligns with the prompt message in google.cloud.aiplatform.master.GenerateContentRequest.", "properties": { "tools": { "type": "array", "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.", "items": { "$ref": "GoogleCloudAiplatformV1Tool" } }, "generationConfig": { "$ref": "GoogleCloudAiplatformV1GenerationConfig", "description": "Generation config." }, "safetySettings": { "description": "Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1SafetySetting" } }, "toolConfig": { "description": "Tool config. This config is shared for all tools provided in the request.", "$ref": "GoogleCloudAiplatformV1ToolConfig" }, "systemInstruction": { "$ref": "GoogleCloudAiplatformV1Content", "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." }, "model": { "type": "string", "description": "The model name." }, "contents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1Content" }, "description": "The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request." } }, "type": "object" }, "GoogleCloudAiplatformV1SummarizationHelpfulnessInput": { "description": "Input for summarization helpfulness metric.", "id": "GoogleCloudAiplatformV1SummarizationHelpfulnessInput", "type": "object", "properties": { "metricSpec": { "description": "Required. Spec for summarization helpfulness score metric.", "$ref": "GoogleCloudAiplatformV1SummarizationHelpfulnessSpec" }, "instance": { "$ref": "GoogleCloudAiplatformV1SummarizationHelpfulnessInstance", "description": "Required. Summarization helpfulness instance." } } }, "GenaiVertexV1ProcessingCallDelta": { "type": "object", "properties": {}, "id": "GenaiVertexV1ProcessingCallDelta", "description": "Streaming delta for a server-initiated media processing step." }, "GoogleCloudAiplatformV1Event": { "id": "GoogleCloudAiplatformV1Event", "type": "object", "properties": { "eventTime": { "readOnly": true, "description": "Output only. Time the Event occurred.", "type": "string", "format": "google-datetime" }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "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." }, "execution": { "description": "Output only. The relative resource name of the Execution in the Event.", "readOnly": true, "type": "string" }, "artifact": { "type": "string", "description": "Required. The relative resource name of the Artifact in the Event." }, "type": { "enumDescriptions": [ "Unspecified whether input or output of the Execution.", "An input of the Execution.", "An output of the Execution." ], "type": "string", "enum": [ "TYPE_UNSPECIFIED", "INPUT", "OUTPUT" ], "description": "Required. The type of the Event." } }, "description": "An edge describing the relationship between an Artifact and an Execution in a lineage graph." }, "GoogleCloudAiplatformV1DiskSpec": { "type": "object", "description": "Represents the spec of disk options.", "id": "GoogleCloudAiplatformV1DiskSpec", "properties": { "bootDiskType": { "type": "string", "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\"." }, "bootDiskSizeGb": { "format": "int32", "type": "integer", "description": "Size in GB of the boot disk (default is 100GB)." } } }, "GoogleCloudAiplatformV1SemanticGovernancePolicyEngine": { "id": "GoogleCloudAiplatformV1SemanticGovernancePolicyEngine", "properties": { "updateTime": { "description": "Output only. Timestamp when this SemanticGovernancePolicyEngine was last updated.", "readOnly": true, "format": "google-datetime", "type": "string" }, "pscForwardingRule": { "description": "Output only. The URI of the PSC endpoint resource created in customer project. Format: projects/{project}/regions/{region}/forwardingRules/{forwarding_rule}", "type": "string", "readOnly": true }, "pscServiceAttachment": { "type": "string", "description": "Output only. URI of the PSC attachment resource provided by SGP. Format: projects/{project}/regions/{region}/serviceAttachments/{service_attachment}", "readOnly": true }, "gatewayConfigs": { "description": "Optional. Configurations for gateways. The keys are user-defined names for each gateway. At most 5 gateway configurations are allowed.", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1GatewayConfig" }, "type": "object" }, "createTime": { "readOnly": true, "description": "Output only. Timestamp when this SemanticGovernancePolicyEngine was created.", "type": "string", "format": "google-datetime" }, "ipAddress": { "readOnly": true, "description": "Output only. The private IPv4 address of the PSC endpoint.", "type": "string" }, "name": { "description": "Identifier. The resource name of the SemanticGovernancePolicyEngine. Format: projects/{project}/locations/{location}/semanticGovernancePolicyEngine", "type": "string" }, "state": { "readOnly": true, "enum": [ "STATE_UNSPECIFIED", "PROVISIONING", "ACTIVE", "DEPROVISIONING", "INACTIVE", "FAILED" ], "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "A provisioning operation is in progress. The engine will transition to ACTIVE on success or FAILED on failure.", "The engine and all of its gateway configurations are provisioned and ready to serve traffic.", "A deprovisioning operation is in progress. The engine will transition to INACTIVE on success or FAILED on failure.", "The engine has no provisioned infrastructure: either never provisioned, or successfully deprovisioned.", "The most recent provisioning or deprovisioning operation failed. The engine may have partial infrastructure that needs explicit deprovision; the engine may be either re-provisioned or deprovisioned to recover." ], "description": "Output only. The state of the SemanticGovernancePolicyEngine." } }, "description": "Define a singleton SemanticGovernancePolicyEngine resource under a project and location.", "type": "object" }, "GoogleIamV1Binding": { "properties": { "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" }, "members": { "items": { "type": "string" }, "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" }, "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)." } }, "id": "GoogleIamV1Binding", "description": "Associates `members`, or principals, with a `role`.", "type": "object" }, "GoogleCloudAiplatformV1CopyModelResponse": { "properties": { "modelVersionId": { "type": "string", "description": "Output only. The version ID of the model that is copied.", "readOnly": true }, "model": { "type": "string", "description": "The name of the copied Model resource. Format: `projects/{project}/locations/{location}/models/{model}`" } }, "id": "GoogleCloudAiplatformV1CopyModelResponse", "description": "Response message of ModelService.CopyModel operation.", "type": "object" }, "GoogleCloudAiplatformV1AudioTranscriptionConfigLanguageAuto": { "properties": {}, "type": "object", "id": "GoogleCloudAiplatformV1AudioTranscriptionConfigLanguageAuto", "deprecated": true, "description": "Deprecated: Use top-level `language_codes` instead. Indicates the language of the audio should be automatically detected." }, "GoogleCloudAiplatformV1SupervisedHyperParameters": { "type": "object", "properties": { "learningRateMultiplier": { "format": "double", "type": "number", "description": "Optional. Multiplier for adjusting the default learning rate. Mutually exclusive with `learning_rate`. This feature is only available for 1P models." }, "epochCount": { "type": "string", "format": "int64", "description": "Optional. Number of complete passes the model makes over the entire training dataset during training." }, "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." ] } }, "description": "Hyperparameters for SFT.", "id": "GoogleCloudAiplatformV1SupervisedHyperParameters" }, "GenaiVertexV1ImageDelta": { "id": "GenaiVertexV1ImageDelta", "type": "object", "properties": { "data": { "type": "string", "format": "byte" }, "mimeType": { "type": "string", "enum": [ "TYPE_UNSPECIFIED", "TYPE_PNG", "TYPE_JPEG", "TYPE_WEBP", "TYPE_HEIC", "TYPE_HEIF", "TYPE_GIF", "TYPE_BMP", "TYPE_TIFF" ], "enumDescriptions": [ "", "PNG image format", "JPEG image format", "WebP image format", "HEIC image format", "HEIF image format", "GIF image format", "BMP image format", "TIFF image format" ] }, "uri": { "type": "string" }, "resolution": { "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "Low resolution.", "Medium resolution.", "High resolution.", "Ultra high resolution." ], "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "LOW", "MEDIUM", "HIGH", "ULTRA_HIGH" ], "description": "The resolution of the media." } } } }, "resources": { "featurestores": { "resources": { "operations": { "methods": { "delete": { "path": "v1/{+name}", "id": "aiplatform.featurestores.operations.delete", "httpMethod": "DELETE", "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": "v1/featurestores/{featurestoresId}/operations/{operationsId}", "parameters": { "name": { "required": true, "pattern": "^featurestores/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string" } } }, "cancel": { "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^featurestores/[^/]+/operations/[^/]+$" } }, "id": "aiplatform.featurestores.operations.cancel", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}:cancel", "flatPath": "v1/featurestores/{featurestoresId}/operations/{operationsId}:cancel", "httpMethod": "POST" }, "list": { "flatPath": "v1/featurestores/{featurestoresId}/operations", "parameterOrder": [ "name" ], "parameters": { "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "format": "int32", "description": "The standard list page size.", "location": "query", "type": "integer" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "required": true, "pattern": "^featurestores/[^/]+$" } }, "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "aiplatform.featurestores.operations.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET" }, "wait": { "parameterOrder": [ "name" ], "parameters": { "timeout": { "format": "google-duration", "location": "query", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." }, "name": { "required": true, "type": "string", "pattern": "^featurestores/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "location": "path" } }, "path": "v1/{+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.", "id": "aiplatform.featurestores.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/featurestores/{featurestoresId}/operations/{operationsId}:wait", "httpMethod": "POST" }, "get": { "flatPath": "v1/featurestores/{featurestoresId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation resource.", "pattern": "^featurestores/[^/]+/operations/[^/]+$", "location": "path" } }, "id": "aiplatform.featurestores.operations.get", "path": "v1/{+name}" } } }, "entityTypes": { "resources": { "features": { "resources": { "operations": { "methods": { "get": { "path": "v1/{+name}", "id": "aiplatform.featurestores.entityTypes.features.operations.get", "parameterOrder": [ "name" ], "parameters": { "name": { "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "httpMethod": "GET", "flatPath": "v1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" } }, "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "location": "path" }, "timeout": { "type": "string", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query" } }, "flatPath": "v1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameterOrder": [ "name" ], "path": "v1/{+name}:wait", "id": "aiplatform.featurestores.entityTypes.features.operations.wait", "httpMethod": "POST" }, "cancel": { "response": { "$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`.", "flatPath": "v1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:cancel", "id": "aiplatform.featurestores.entityTypes.features.operations.cancel", "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "path": "v1/{+name}:cancel" }, "list": { "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.featurestores.entityTypes.features.operations.list", "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", "type": "integer", "format": "int32" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", "type": "string", "required": true }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1/{+name}/operations" }, "delete": { "parameters": { "name": { "required": true, "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string" } }, "id": "aiplatform.featurestores.entityTypes.features.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`.", "path": "v1/{+name}", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}", "httpMethod": "DELETE", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "operations": { "methods": { "list": { "id": "aiplatform.featurestores.entityTypes.operations.list", "httpMethod": "GET", "parameters": { "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "pageSize": { "format": "int32", "type": "integer", "description": "The standard list page size.", "location": "query" }, "name": { "required": true, "description": "The name of the operation's parent resource.", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+$", "type": "string", "location": "path" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations", "flatPath": "v1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "delete": { "flatPath": "v1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.featurestores.entityTypes.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`.", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource to be deleted.", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "httpMethod": "DELETE" }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "POST", "flatPath": "v1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:cancel", "id": "aiplatform.featurestores.entityTypes.operations.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`.", "path": "v1/{+name}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true, "type": "string" } } }, "get": { "parameters": { "name": { "type": "string", "required": true, "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource." } }, "id": "aiplatform.featurestores.entityTypes.operations.get", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "flatPath": "v1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/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": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ] }, "wait": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.featurestores.entityTypes.operations.wait", "path": "v1/{+name}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:wait", "parameters": { "timeout": { "format": "google-duration", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" }, "name": { "pattern": "^featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "required": true } }, "response": { "$ref": "GoogleLongrunningOperation" } } } } } } } }, "schedules": { "resources": { "operations": { "methods": { "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/schedules/{schedulesId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "httpMethod": "POST", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^schedules/[^/]+/operations/[^/]+$", "type": "string", "required": true }, "timeout": { "type": "string", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration" } }, "id": "aiplatform.schedules.operations.wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "get": { "parameterOrder": [ "name" ], "path": "v1/{+name}", "httpMethod": "GET", "id": "aiplatform.schedules.operations.get", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "required": true, "pattern": "^schedules/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "location": "path" } }, "flatPath": "v1/schedules/{schedulesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "parameterOrder": [ "name" ], "parameters": { "name": { "pattern": "^schedules/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string" } }, "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/schedules/{schedulesId}/operations/{operationsId}", "httpMethod": "DELETE", "id": "aiplatform.schedules.operations.delete" }, "cancel": { "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^schedules/[^/]+/operations/[^/]+$", "required": true } }, "path": "v1/{+name}:cancel", "id": "aiplatform.schedules.operations.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`.", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/schedules/{schedulesId}/operations/{operationsId}:cancel", "httpMethod": "POST" }, "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "pageSize": { "format": "int32", "description": "The standard list page size.", "location": "query", "type": "integer" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "name": { "type": "string", "required": true, "description": "The name of the operation's parent resource.", "pattern": "^schedules/[^/]+$", "location": "path" }, "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" } }, "path": "v1/{+name}/operations", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "flatPath": "v1/schedules/{schedulesId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.schedules.operations.list" } } } } }, "featureOnlineStores": { "resources": { "operations": { "methods": { "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "parameterOrder": [ "name" ], "id": "aiplatform.featureOnlineStores.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "timeout": { "format": "google-duration", "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" }, "name": { "location": "path", "description": "The name of the operation resource to wait on.", "required": true, "type": "string", "pattern": "^featureOnlineStores/[^/]+/operations/[^/]+$" } }, "path": "v1/{+name}:wait", "flatPath": "v1/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "flatPath": "v1/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}", "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "pattern": "^featureOnlineStores/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be deleted.", "required": true } }, "id": "aiplatform.featureOnlineStores.operations.delete", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "listWait": { "path": "v1/{+name}:wait", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.featureOnlineStores.operations.listWait", "parameterOrder": [ "name" ], "flatPath": "v1/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}:wait", "parameters": { "returnPartialSuccess": { "location": "query", "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." }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "name": { "description": "The name of the operation's parent resource.", "required": true, "type": "string", "location": "path", "pattern": "^featureOnlineStores/[^/]+/operations/[^/]+$" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET" }, "get": { "parameters": { "name": { "type": "string", "location": "path", "pattern": "^featureOnlineStores/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "required": true } }, "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}", "path": "v1/{+name}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "id": "aiplatform.featureOnlineStores.operations.get", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." } } }, "featureViews": { "resources": { "operations": { "methods": { "listWait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "httpMethod": "GET", "flatPath": "v1/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}:wait", "parameters": { "name": { "type": "string", "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "required": true }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "pageSize": { "location": "query", "description": "The standard list page size.", "type": "integer", "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" } }, "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "id": "aiplatform.featureOnlineStores.featureViews.operations.listWait", "path": "v1/{+name}:wait" }, "delete": { "httpMethod": "DELETE", "id": "aiplatform.featureOnlineStores.featureViews.operations.delete", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "type": "string", "required": true, "pattern": "^featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "location": "path" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "flatPath": "v1/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}:wait", "httpMethod": "POST", "id": "aiplatform.featureOnlineStores.featureViews.operations.wait", "path": "v1/{+name}:wait", "parameters": { "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.", "type": "string", "format": "google-duration", "location": "query" }, "name": { "pattern": "^featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "description": "The name of the operation resource to wait on.", "required": true } }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "httpMethod": "GET", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "id": "aiplatform.featureOnlineStores.featureViews.operations.get", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}", "parameters": { "name": { "required": true, "type": "string", "pattern": "^featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "location": "path" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" } } } } } } } }, "batchPredictionJobs": { "methods": { "create": { "httpMethod": "POST", "path": "v1/batchPredictionJobs", "id": "aiplatform.batchPredictionJobs.create", "parameterOrder": [], "flatPath": "v1/batchPredictionJobs", "response": { "$ref": "GoogleCloudAiplatformV1BatchPredictionJob" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1BatchPredictionJob" }, "parameters": { "parent": { "type": "string", "description": "Required. The resource name of the Location to create the BatchPredictionJob in. Format: `projects/{project}/locations/{location}`", "location": "query" } }, "description": "Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start." }, "list": { "parameters": { "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:*`" }, "pageSize": { "location": "query", "type": "integer", "description": "The standard list page size.", "format": "int32" }, "parent": { "description": "Required. The resource name of the Location to list the BatchPredictionJobs from. Format: `projects/{project}/locations/{location}`", "location": "query", "type": "string" }, "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "format": "google-fieldmask", "location": "query" }, "pageToken": { "description": "The standard list page token. Typically obtained via ListBatchPredictionJobsResponse.next_page_token of the previous JobService.ListBatchPredictionJobs call.", "type": "string", "location": "query" } }, "parameterOrder": [], "path": "v1/batchPredictionJobs", "id": "aiplatform.batchPredictionJobs.list", "flatPath": "v1/batchPredictionJobs", "response": { "$ref": "GoogleCloudAiplatformV1ListBatchPredictionJobsResponse" }, "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists BatchPredictionJobs in a Location." }, "get": { "response": { "$ref": "GoogleCloudAiplatformV1BatchPredictionJob" }, "flatPath": "v1/batchPredictionJobs/{batchPredictionJobsId}", "id": "aiplatform.batchPredictionJobs.get", "parameterOrder": [ "name" ], "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^batchPredictionJobs/[^/]+$", "required": true, "location": "path", "type": "string", "description": "Required. The name of the BatchPredictionJob resource. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`" } }, "description": "Gets a BatchPredictionJob", "path": "v1/{+name}" } } }, "interactions": { "methods": { "getPoll": { "description": "Fully typed proto, unary version of GetInteraction that returns Interaction proto.", "response": { "$ref": "GenaiVertexV1Interaction" }, "id": "aiplatform.interactions.getPoll", "flatPath": "v1/interactions/{interactionsId}:poll", "path": "v1/{+name}:poll", "parameters": { "lastEventId": { "location": "query", "type": "string", "description": "If set, resumes the interaction stream from the chunk after the event marked by the event id. Can only be used if `stream` is true." }, "stream": { "location": "query", "type": "boolean", "description": "If true, streams the interaction events as Server-Sent Events." }, "name": { "location": "path", "type": "string", "required": true, "description": "Required. The name of the interaction to retrieve. Format: interactions/{interaction}", "pattern": "^interactions/[^/]+$" } }, "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] }, "cancel": { "id": "aiplatform.interactions.cancel", "parameters": { "name": { "required": true, "type": "string", "description": "Required. The name of the interaction to cancel. Format: `interactions/{interaction}`.", "pattern": "^interactions/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "response": { "$ref": "GenaiVertexV1Interaction" }, "description": "Cancels an interaction.", "flatPath": "v1/interactions/{interactionsId}:cancel", "httpMethod": "POST", "parameterOrder": [ "name" ] }, "getStream": { "path": "v1/{+name}:stream", "id": "aiplatform.interactions.getStream", "description": "Fully typed proto, streaming version of GetInteraction that returns Interaction proto.", "response": { "$ref": "GenaiVertexV1InteractionStreamingEvent" }, "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "required": true, "pattern": "^interactions/[^/]+$", "location": "path", "description": "Required. The name of the interaction to retrieve. Format: interactions/{interaction}" }, "lastEventId": { "type": "string", "description": "If set, resumes the interaction stream from the chunk after the event marked by the event id. Can only be used if `stream` is true.", "location": "query" }, "stream": { "type": "boolean", "description": "If true, streams the interaction events as Server-Sent Events.", "location": "query" } }, "flatPath": "v1/interactions/{interactionsId}:stream", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "skills": { "resources": { "operations": { "methods": { "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "flatPath": "v1/skills/{skillsId}/operations/{operationsId}", "parameters": { "name": { "pattern": "^skills/[^/]+/operations/[^/]+$", "type": "string", "required": true, "location": "path", "description": "The name of the operation resource." } }, "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "httpMethod": "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.", "id": "aiplatform.skills.operations.get" }, "list": { "parameters": { "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "name": { "pattern": "^skills/[^/]+$", "location": "path", "type": "string", "description": "The name of the operation's parent resource.", "required": true }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "pageSize": { "type": "integer", "format": "int32", "description": "The standard list page size.", "location": "query" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "path": "v1/{+name}/operations", "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1/skills/{skillsId}/operations", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.skills.operations.list" }, "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "pattern": "^skills/[^/]+/operations/[^/]+$", "location": "path" }, "timeout": { "format": "google-duration", "location": "query", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "flatPath": "v1/skills/{skillsId}/operations/{operationsId}:wait", "response": { "$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.", "path": "v1/{+name}:wait", "id": "aiplatform.skills.operations.wait", "httpMethod": "POST" }, "delete": { "flatPath": "v1/skills/{skillsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "httpMethod": "DELETE", "id": "aiplatform.skills.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource to be deleted.", "pattern": "^skills/[^/]+/operations/[^/]+$", "required": true } }, "path": "v1/{+name}", "parameterOrder": [ "name" ] }, "cancel": { "parameterOrder": [ "name" ], "id": "aiplatform.skills.operations.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`.", "flatPath": "v1/skills/{skillsId}/operations/{operationsId}:cancel", "httpMethod": "POST", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^skills/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "path": "v1/{+name}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "tensorboards": { "resources": { "operations": { "methods": { "cancel": { "id": "aiplatform.tensorboards.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^tensorboards/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/tensorboards/{tensorboardsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "httpMethod": "POST", "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`.", "path": "v1/{+name}:cancel" }, "delete": { "httpMethod": "DELETE", "path": "v1/{+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`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "flatPath": "v1/tensorboards/{tensorboardsId}/operations/{operationsId}", "id": "aiplatform.tensorboards.operations.delete", "parameters": { "name": { "required": true, "pattern": "^tensorboards/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } } }, "get": { "parameterOrder": [ "name" ], "flatPath": "v1/tensorboards/{tensorboardsId}/operations/{operationsId}", "parameters": { "name": { "required": true, "type": "string", "pattern": "^tensorboards/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "location": "path" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "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.", "id": "aiplatform.tensorboards.operations.get" }, "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.tensorboards.operations.wait", "flatPath": "v1/tensorboards/{tensorboardsId}/operations/{operationsId}:wait", "parameters": { "name": { "pattern": "^tensorboards/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "type": "string", "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.", "format": "google-duration", "location": "query" } }, "httpMethod": "POST", "path": "v1/{+name}:wait", "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." }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "flatPath": "v1/tensorboards/{tensorboardsId}/operations", "path": "v1/{+name}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageSize": { "location": "query", "description": "The standard list page size.", "type": "integer", "format": "int32" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^tensorboards/[^/]+$", "type": "string", "required": true } }, "httpMethod": "GET", "id": "aiplatform.tensorboards.operations.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] } } }, "experiments": { "resources": { "operations": { "methods": { "cancel": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "parameters": { "name": { "type": "string", "required": true, "pattern": "^tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.tensorboards.experiments.operations.cancel", "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "path": "v1/{+name}: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`." }, "wait": { "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:wait", "parameterOrder": [ "name" ], "path": "v1/{+name}:wait", "parameters": { "timeout": { "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", "location": "query" }, "name": { "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "id": "aiplatform.tensorboards.experiments.operations.wait", "httpMethod": "POST" }, "delete": { "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", "parameters": { "name": { "pattern": "^tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string" } }, "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`.", "id": "aiplatform.tensorboards.experiments.operations.delete", "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`.", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.tensorboards.experiments.operations.list", "path": "v1/{+name}/operations", "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations", "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "format": "int32", "type": "integer" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^tensorboards/[^/]+/experiments/[^/]+$", "required": true, "type": "string" }, "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.", "type": "boolean", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } } }, "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.", "parameters": { "name": { "description": "The name of the operation resource.", "required": true, "type": "string", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "location": "path" } }, "parameterOrder": [ "name" ], "httpMethod": "GET", "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.tensorboards.experiments.operations.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] } } }, "runs": { "resources": { "operations": { "methods": { "list": { "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "name": { "required": true, "type": "string", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "description": "The name of the operation's parent resource.", "location": "path" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "pageSize": { "description": "The standard list page size.", "type": "integer", "location": "query", "format": "int32" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations", "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations", "httpMethod": "GET", "id": "aiplatform.tensorboards.experiments.runs.operations.list" }, "get": { "httpMethod": "GET", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.tensorboards.experiments.runs.operations.get", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource.", "required": true, "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$" } }, "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}", "path": "v1/{+name}" }, "cancel": { "httpMethod": "POST", "path": "v1/{+name}: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`.", "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "id": "aiplatform.tensorboards.experiments.runs.operations.cancel", "parameters": { "name": { "location": "path", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "type": "string" } } }, "wait": { "parameterOrder": [ "name" ], "id": "aiplatform.tensorboards.experiments.runs.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:wait", "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$" }, "timeout": { "location": "query", "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", "format": "google-duration" } }, "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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." }, "delete": { "path": "v1/{+name}", "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource to be deleted.", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "required": true } }, "id": "aiplatform.tensorboards.experiments.runs.operations.delete", "parameterOrder": [ "name" ], "response": { "$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": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}", "httpMethod": "DELETE" } } }, "timeSeries": { "resources": { "operations": { "methods": { "wait": { "parameters": { "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" }, "name": { "type": "string", "required": true, "description": "The name of the operation resource to wait on.", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "location": "path" } }, "id": "aiplatform.tensorboards.experiments.runs.timeSeries.operations.wait", "path": "v1/{+name}:wait", "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST" }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}", "httpMethod": "DELETE", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "path": "v1/{+name}", "parameterOrder": [ "name" ], "id": "aiplatform.tensorboards.experiments.runs.timeSeries.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string" } } }, "get": { "id": "aiplatform.tensorboards.experiments.runs.timeSeries.operations.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "type": "string", "location": "path" } }, "path": "v1/{+name}", "httpMethod": "GET", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}" }, "list": { "parameters": { "name": { "location": "path", "required": true, "type": "string", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "description": "The name of the operation's parent resource." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "pageSize": { "location": "query", "format": "int32", "type": "integer", "description": "The standard list page size." } }, "path": "v1/{+name}/operations", "id": "aiplatform.tensorboards.experiments.runs.timeSeries.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "id": "aiplatform.tensorboards.experiments.runs.timeSeries.operations.cancel", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "location": "path", "required": true } }, "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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`." } } } } } } } } } } }, "tuningJobs": { "resources": { "operations": { "methods": { "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.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^tuningJobs/[^/]+/operations/[^/]+$", "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ], "flatPath": "v1/tuningJobs/{tuningJobsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "path": "v1/{+name}:wait", "id": "aiplatform.tuningJobs.operations.wait" }, "list": { "parameters": { "pageSize": { "location": "query", "type": "integer", "description": "The standard list page size.", "format": "int32" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "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": "^tuningJobs/[^/]+$", "location": "path", "type": "string", "required": true, "description": "The name of the operation's parent resource." }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.tuningJobs.operations.list", "httpMethod": "GET", "flatPath": "v1/tuningJobs/{tuningJobsId}/operations", "path": "v1/{+name}/operations" }, "cancel": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/tuningJobs/{tuningJobsId}/operations/{operationsId}:cancel", "parameters": { "name": { "required": true, "pattern": "^tuningJobs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string" } }, "id": "aiplatform.tuningJobs.operations.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`." }, "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "httpMethod": "GET", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.tuningJobs.operations.get", "flatPath": "v1/tuningJobs/{tuningJobsId}/operations/{operationsId}", "parameters": { "name": { "required": true, "pattern": "^tuningJobs/[^/]+/operations/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "delete": { "id": "aiplatform.tuningJobs.operations.delete", "parameterOrder": [ "name" ], "httpMethod": "DELETE", "path": "v1/{+name}", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "pattern": "^tuningJobs/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be deleted.", "required": true } }, "flatPath": "v1/tuningJobs/{tuningJobsId}/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`." } } } } }, "notebookRuntimeTemplates": { "resources": { "operations": { "methods": { "get": { "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "location": "path", "type": "string" } }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "id": "aiplatform.notebookRuntimeTemplates.operations.get", "flatPath": "v1/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}" }, "wait": { "parameters": { "name": { "description": "The name of the operation resource to wait on.", "required": true, "type": "string", "pattern": "^notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "location": "path" }, "timeout": { "type": "string", "format": "google-duration", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "flatPath": "v1/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "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.", "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.notebookRuntimeTemplates.operations.wait", "httpMethod": "POST" }, "list": { "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "returnPartialSuccess": { "location": "query", "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." }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "name": { "description": "The name of the operation's parent resource.", "required": true, "type": "string", "pattern": "^notebookRuntimeTemplates/[^/]+$", "location": "path" }, "pageSize": { "format": "int32", "type": "integer", "location": "query", "description": "The standard list page size." } }, "id": "aiplatform.notebookRuntimeTemplates.operations.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}/operations", "flatPath": "v1/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "httpMethod": "GET" }, "cancel": { "flatPath": "v1/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:cancel", "httpMethod": "POST", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "path": "v1/{+name}:cancel", "id": "aiplatform.notebookRuntimeTemplates.operations.cancel", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "pattern": "^notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "required": true, "type": "string" } } }, "delete": { "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "pattern": "^notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to be deleted." } }, "id": "aiplatform.notebookRuntimeTemplates.operations.delete", "path": "v1/{+name}", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/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`.", "httpMethod": "DELETE" } } } } }, "pipelineJobs": { "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "pattern": "^pipelineJobs/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted.", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/pipelineJobs/{pipelineJobsId}/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`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.pipelineJobs.operations.delete", "path": "v1/{+name}", "httpMethod": "DELETE" }, "wait": { "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^pipelineJobs/[^/]+/operations/[^/]+$", "type": "string", "required": true }, "timeout": { "location": "query", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration" } }, "path": "v1/{+name}:wait", "id": "aiplatform.pipelineJobs.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST" }, "cancel": { "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled.", "required": true, "pattern": "^pipelineJobs/[^/]+/operations/[^/]+$" } }, "flatPath": "v1/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "id": "aiplatform.pipelineJobs.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$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`.", "path": "v1/{+name}:cancel", "httpMethod": "POST" }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "required": true, "description": "The name of the operation resource.", "type": "string", "location": "path", "pattern": "^pipelineJobs/[^/]+/operations/[^/]+$" } }, "flatPath": "v1/pipelineJobs/{pipelineJobsId}/operations/{operationsId}", "id": "aiplatform.pipelineJobs.operations.get", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "path": "v1/{+name}", "httpMethod": "GET" }, "list": { "httpMethod": "GET", "path": "v1/{+name}/operations", "id": "aiplatform.pipelineJobs.operations.list", "flatPath": "v1/pipelineJobs/{pipelineJobsId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "type": "integer", "description": "The standard list page size.", "format": "int32", "location": "query" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "name": { "type": "string", "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^pipelineJobs/[^/]+$", "required": true }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "parameterOrder": [ "name" ] } } } } }, "onlineEvaluators": { "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "type": "string", "required": true, "pattern": "^onlineEvaluators/[^/]+/operations/[^/]+$", "location": "path" } }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "path": "v1/{+name}", "flatPath": "v1/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "DELETE", "id": "aiplatform.onlineEvaluators.operations.delete", "parameterOrder": [ "name" ] }, "list": { "path": "v1/{+name}/operations", "id": "aiplatform.onlineEvaluators.operations.list", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "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" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "pageSize": { "format": "int32", "type": "integer", "location": "query", "description": "The standard list page size." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "name": { "type": "string", "description": "The name of the operation's parent resource.", "required": true, "pattern": "^onlineEvaluators/[^/]+$", "location": "path" } }, "flatPath": "v1/onlineEvaluators/{onlineEvaluatorsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "pattern": "^onlineEvaluators/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string" } }, "id": "aiplatform.onlineEvaluators.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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`.", "parameterOrder": [ "name" ], "path": "v1/{+name}:cancel", "httpMethod": "POST" }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.onlineEvaluators.operations.get", "flatPath": "v1/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}", "httpMethod": "GET", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "description": "The name of the operation resource.", "type": "string", "pattern": "^onlineEvaluators/[^/]+/operations/[^/]+$", "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." }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}:wait", "httpMethod": "POST", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "id": "aiplatform.onlineEvaluators.operations.wait", "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" }, "name": { "location": "path", "type": "string", "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^onlineEvaluators/[^/]+/operations/[^/]+$" } } } } } } }, "taskStores": { "resources": { "operations": { "methods": { "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^taskStores/[^/]+$" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "flatPath": "v1/taskStores/{taskStoresId}/operations", "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations", "parameterOrder": [ "name" ], "id": "aiplatform.taskStores.operations.list" }, "wait": { "flatPath": "v1/taskStores/{taskStoresId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^taskStores/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "location": "query", "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.", "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.", "id": "aiplatform.taskStores.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait", "httpMethod": "POST" }, "delete": { "httpMethod": "DELETE", "id": "aiplatform.taskStores.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "flatPath": "v1/taskStores/{taskStoresId}/operations/{operationsId}", "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": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "required": true, "pattern": "^taskStores/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string" } } }, "get": { "parameters": { "name": { "location": "path", "type": "string", "pattern": "^taskStores/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource." } }, "flatPath": "v1/taskStores/{taskStoresId}/operations/{operationsId}", "httpMethod": "GET", "id": "aiplatform.taskStores.operations.get", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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." }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/taskStores/{taskStoresId}/operations/{operationsId}:cancel", "httpMethod": "POST", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^taskStores/[^/]+/operations/[^/]+$", "type": "string", "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`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "id": "aiplatform.taskStores.operations.cancel" } } } } }, "deploymentResourcePools": { "resources": { "operations": { "methods": { "list": { "path": "v1/{+name}/operations", "httpMethod": "GET", "parameters": { "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "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": { "required": true, "description": "The name of the operation's parent resource.", "pattern": "^deploymentResourcePools/[^/]+$", "location": "path", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageSize": { "type": "integer", "format": "int32", "location": "query", "description": "The standard list page size." } }, "flatPath": "v1/deploymentResourcePools/{deploymentResourcePoolsId}/operations", "id": "aiplatform.deploymentResourcePools.operations.list", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.deploymentResourcePools.operations.get", "flatPath": "v1/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "pattern": "^deploymentResourcePools/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource." } }, "httpMethod": "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.", "parameterOrder": [ "name" ], "path": "v1/{+name}" }, "delete": { "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.deploymentResourcePools.operations.delete", "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}", "flatPath": "v1/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "pattern": "^deploymentResourcePools/[^/]+/operations/[^/]+$", "location": "path" } } }, "cancel": { "path": "v1/{+name}:cancel", "parameters": { "name": { "location": "path", "pattern": "^deploymentResourcePools/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.deploymentResourcePools.operations.cancel", "flatPath": "v1/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "POST" }, "wait": { "id": "aiplatform.deploymentResourcePools.operations.wait", "path": "v1/{+name}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "flatPath": "v1/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "pattern": "^deploymentResourcePools/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "type": "string" }, "timeout": { "location": "query", "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.", "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." } } } } }, "notebookExecutionJobs": { "resources": { "operations": { "methods": { "list": { "parameters": { "name": { "pattern": "^notebookExecutionJobs/[^/]+$", "type": "string", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "aiplatform.notebookExecutionJobs.operations.list", "path": "v1/{+name}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/notebookExecutionJobs/{notebookExecutionJobsId}/operations", "httpMethod": "GET" }, "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}", "id": "aiplatform.notebookExecutionJobs.operations.get", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "parameterOrder": [ "name" ], "httpMethod": "GET", "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource.", "pattern": "^notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true } }, "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": { "path": "v1/{+name}: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`.", "id": "aiplatform.notebookExecutionJobs.operations.cancel", "parameterOrder": [ "name" ], "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string" } }, "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:cancel" }, "delete": { "path": "v1/{+name}", "id": "aiplatform.notebookExecutionJobs.operations.delete", "parameters": { "name": { "location": "path", "pattern": "^notebookExecutionJobs/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be deleted.", "required": true } }, "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$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`.", "flatPath": "v1/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}", "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": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "flatPath": "v1/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:wait", "httpMethod": "POST", "parameters": { "name": { "type": "string", "description": "The name of the operation resource to wait on.", "pattern": "^notebookExecutionJobs/[^/]+/operations/[^/]+$", "location": "path", "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.", "format": "google-duration", "location": "query", "type": "string" } }, "id": "aiplatform.notebookExecutionJobs.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait" } } } } }, "notebookRuntimes": { "resources": { "operations": { "methods": { "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:wait", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "pattern": "^notebookRuntimes/[^/]+/operations/[^/]+$", "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", "type": "string", "format": "google-duration" } }, "path": "v1/{+name}:wait", "id": "aiplatform.notebookRuntimes.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." }, "delete": { "flatPath": "v1/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}", "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`.", "path": "v1/{+name}", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "pattern": "^notebookRuntimes/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be deleted.", "required": true } }, "id": "aiplatform.notebookRuntimes.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE" }, "list": { "path": "v1/{+name}/operations", "id": "aiplatform.notebookRuntimes.operations.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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`.", "parameters": { "returnPartialSuccess": { "location": "query", "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." }, "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "name": { "required": true, "description": "The name of the operation's parent resource.", "pattern": "^notebookRuntimes/[^/]+$", "type": "string", "location": "path" }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "pageSize": { "location": "query", "description": "The standard list page size.", "format": "int32", "type": "integer" } }, "parameterOrder": [ "name" ], "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/notebookRuntimes/{notebookRuntimesId}/operations" }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:cancel", "httpMethod": "POST", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "type": "string", "location": "path", "pattern": "^notebookRuntimes/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.notebookRuntimes.operations.cancel", "path": "v1/{+name}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "httpMethod": "GET", "flatPath": "v1/notebookRuntimes/{notebookRuntimesId}/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": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.notebookRuntimes.operations.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource.", "required": true, "type": "string", "pattern": "^notebookRuntimes/[^/]+/operations/[^/]+$", "location": "path" } } } } } } }, "modelDeploymentMonitoringJobs": { "resources": { "operations": { "methods": { "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "id": "aiplatform.modelDeploymentMonitoringJobs.operations.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.", "parameterOrder": [ "name" ], "path": "v1/{+name}", "flatPath": "v1/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", "parameters": { "name": { "description": "The name of the operation resource.", "required": true, "location": "path", "pattern": "^modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "type": "string" } }, "response": { "$ref": "GoogleLongrunningOperation" } }, "wait": { "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "description": "The name of the operation resource to wait on.", "type": "string", "location": "path", "pattern": "^modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$" }, "timeout": { "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "type": "string" } }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.modelDeploymentMonitoringJobs.operations.wait", "flatPath": "v1/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:wait" }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations", "parameters": { "name": { "pattern": "^modelDeploymentMonitoringJobs/[^/]+$", "required": true, "location": "path", "type": "string", "description": "The name of the operation's parent resource." }, "pageSize": { "format": "int32", "type": "integer", "location": "query", "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" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.modelDeploymentMonitoringJobs.operations.list" }, "cancel": { "path": "v1/{+name}:cancel", "httpMethod": "POST", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:cancel", "parameters": { "name": { "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path", "required": true, "pattern": "^modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$" } }, "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`.", "id": "aiplatform.modelDeploymentMonitoringJobs.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "required": true, "location": "path", "type": "string" } }, "id": "aiplatform.modelDeploymentMonitoringJobs.operations.delete", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ] } } } } }, "persistentResources": { "resources": { "operations": { "methods": { "wait": { "httpMethod": "POST", "id": "aiplatform.persistentResources.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.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "timeout": { "location": "query", "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", "format": "google-duration" }, "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^persistentResources/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "flatPath": "v1/persistentResources/{persistentResourcesId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "flatPath": "v1/persistentResources/{persistentResourcesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "id": "aiplatform.persistentResources.operations.delete", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "pattern": "^persistentResources/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be deleted.", "required": true } } }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/persistentResources/{persistentResourcesId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameterOrder": [ "name" ], "id": "aiplatform.persistentResources.operations.cancel", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "pattern": "^persistentResources/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "type": "string", "location": "path" } }, "path": "v1/{+name}:cancel" }, "list": { "parameters": { "name": { "required": true, "pattern": "^persistentResources/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "returnPartialSuccess": { "location": "query", "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "id": "aiplatform.persistentResources.operations.list", "path": "v1/{+name}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/persistentResources/{persistentResourcesId}/operations", "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "get": { "parameters": { "name": { "location": "path", "pattern": "^persistentResources/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource.", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "flatPath": "v1/persistentResources/{persistentResourcesId}/operations/{operationsId}", "id": "aiplatform.persistentResources.operations.get", "response": { "$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.", "parameterOrder": [ "name" ], "httpMethod": "GET" } } } } }, "ragCorpora": { "resources": { "operations": { "methods": { "cancel": { "id": "aiplatform.ragCorpora.operations.cancel", "httpMethod": "POST", "path": "v1/{+name}:cancel", "parameters": { "name": { "pattern": "^ragCorpora/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string" } }, "flatPath": "v1/ragCorpora/{ragCorporaId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "id": "aiplatform.ragCorpora.operations.delete", "httpMethod": "DELETE", "flatPath": "v1/ragCorpora/{ragCorporaId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "type": "string", "required": true, "pattern": "^ragCorpora/[^/]+/operations/[^/]+$", "location": "path" } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "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.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.ragCorpora.operations.wait", "parameters": { "name": { "location": "path", "pattern": "^ragCorpora/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to wait on." }, "timeout": { "format": "google-duration", "location": "query", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:wait", "flatPath": "v1/ragCorpora/{ragCorporaId}/operations/{operationsId}:wait" }, "get": { "flatPath": "v1/ragCorpora/{ragCorporaId}/operations/{operationsId}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "httpMethod": "GET", "id": "aiplatform.ragCorpora.operations.get", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "pattern": "^ragCorpora/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource.", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameterOrder": [ "name" ], "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "aiplatform.ragCorpora.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/ragCorpora/{ragCorporaId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "pageSize": { "format": "int32", "description": "The standard list page size.", "type": "integer", "location": "query" }, "name": { "type": "string", "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^ragCorpora/[^/]+$", "required": true }, "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" } }, "path": "v1/{+name}/operations" } } }, "ragFiles": { "resources": { "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`.", "parameters": { "name": { "required": true, "pattern": "^ragCorpora/[^/]+/ragFiles/[^/]+$", "location": "path", "type": "string", "description": "The name of the operation's parent resource." }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "id": "aiplatform.ragCorpora.ragFiles.operations.list", "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations", "flatPath": "v1/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] }, "delete": { "httpMethod": "DELETE", "id": "aiplatform.ragCorpora.ragFiles.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`.", "flatPath": "v1/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}", "path": "v1/{+name}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "required": true } } }, "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": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "path": "v1/{+name}", "id": "aiplatform.ragCorpora.ragFiles.operations.get", "flatPath": "v1/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] }, "cancel": { "path": "v1/{+name}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "required": true, "type": "string", "pattern": "^ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "location": "path" } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "id": "aiplatform.ragCorpora.ragFiles.operations.cancel", "httpMethod": "POST", "flatPath": "v1/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ] }, "wait": { "id": "aiplatform.ragCorpora.ragFiles.operations.wait", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "path": "v1/{+name}:wait", "parameters": { "name": { "type": "string", "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "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.", "format": "google-duration", "location": "query" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] } } } } } } }, "semanticGovernancePolicies": { "resources": { "operations": { "methods": { "cancel": { "path": "v1/{+name}:cancel", "httpMethod": "POST", "parameterOrder": [ "name" ], "id": "aiplatform.semanticGovernancePolicies.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "required": true, "pattern": "^semanticGovernancePolicies/[^/]+/operations/[^/]+$" } }, "response": { "$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": "v1/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}:cancel" }, "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.semanticGovernancePolicies.operations.wait", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "pattern": "^semanticGovernancePolicies/[^/]+/operations/[^/]+$", "type": "string", "required": true, "location": "path" }, "timeout": { "type": "string", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query" } }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameterOrder": [ "name" ], "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:wait", "flatPath": "v1/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}:wait" }, "delete": { "httpMethod": "DELETE", "flatPath": "v1/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "id": "aiplatform.semanticGovernancePolicies.operations.delete", "path": "v1/{+name}", "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation resource to be deleted.", "pattern": "^semanticGovernancePolicies/[^/]+/operations/[^/]+$", "location": "path" } }, "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": { "parameterOrder": [ "name" ], "id": "aiplatform.semanticGovernancePolicies.operations.get", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "parameters": { "name": { "description": "The name of the operation resource.", "type": "string", "location": "path", "pattern": "^semanticGovernancePolicies/[^/]+/operations/[^/]+$", "required": true } }, "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "flatPath": "v1/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}" }, "list": { "httpMethod": "GET", "parameterOrder": [ "name" ], "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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations", "flatPath": "v1/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations", "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "location": "query", "type": "integer", "description": "The standard list page size.", "format": "int32" }, "name": { "required": true, "pattern": "^semanticGovernancePolicies/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "returnPartialSuccess": { "location": "query", "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." } }, "id": "aiplatform.semanticGovernancePolicies.operations.list" } } } } }, "endpoints": { "methods": { "computeTokens": { "request": { "$ref": "GoogleCloudAiplatformV1ComputeTokensRequest" }, "path": "v1/{+endpoint}:computeTokens", "httpMethod": "POST", "parameters": { "endpoint": { "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids.", "location": "path", "pattern": "^endpoints/[^/]+$", "type": "string", "required": true } }, "response": { "$ref": "GoogleCloudAiplatformV1ComputeTokensResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.endpoints.computeTokens", "flatPath": "v1/endpoints/{endpointsId}:computeTokens", "description": "Return a list of tokens based on the input text.", "parameterOrder": [ "endpoint" ] }, "predictLongRunning": { "parameters": { "endpoint": { "type": "string", "pattern": "^endpoints/[^/]+$", "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" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "path": "v1/{+endpoint}:predictLongRunning", "request": { "$ref": "GoogleCloudAiplatformV1PredictLongRunningRequest" }, "id": "aiplatform.endpoints.predictLongRunning", "description": "", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/endpoints/{endpointsId}:predictLongRunning", "httpMethod": "POST" }, "predict": { "id": "aiplatform.endpoints.predict", "parameters": { "endpoint": { "required": true, "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^endpoints/[^/]+$", "location": "path", "type": "string" } }, "description": "", "request": { "$ref": "GoogleCloudAiplatformV1PredictRequest" }, "path": "v1/{+endpoint}:predict", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameterOrder": [ "endpoint" ], "response": { "$ref": "GoogleCloudAiplatformV1PredictResponse" }, "flatPath": "v1/endpoints/{endpointsId}:predict", "httpMethod": "POST" }, "streamGenerateContent": { "flatPath": "v1/endpoints/{endpointsId}:streamGenerateContent", "description": "Generate content with multimodal inputs with streaming support.", "parameters": { "model": { "required": true, "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string", "location": "path", "pattern": "^endpoints/[^/]+$" } }, "response": { "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" }, "request": { "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" }, "id": "aiplatform.endpoints.streamGenerateContent", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameterOrder": [ "model" ], "path": "v1/{+model}:streamGenerateContent", "httpMethod": "POST" }, "fetchPredictOperation": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "httpMethod": "POST", "parameterOrder": [ "endpoint" ], "description": "Fetch an asynchronous online prediction operation.", "path": "v1/{+endpoint}:fetchPredictOperation", "request": { "$ref": "GoogleCloudAiplatformV1FetchPredictOperationRequest" }, "flatPath": "v1/endpoints/{endpointsId}:fetchPredictOperation", "id": "aiplatform.endpoints.fetchPredictOperation", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "endpoint": { "location": "path", "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}`", "pattern": "^endpoints/[^/]+$", "required": true } } }, "countTokens": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+endpoint}:countTokens", "request": { "$ref": "GoogleCloudAiplatformV1CountTokensRequest" }, "description": "Perform a token counting.", "id": "aiplatform.endpoints.countTokens", "response": { "$ref": "GoogleCloudAiplatformV1CountTokensResponse" }, "parameterOrder": [ "endpoint" ], "parameters": { "endpoint": { "location": "path", "type": "string", "pattern": "^endpoints/[^/]+$", "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "required": true } }, "flatPath": "v1/endpoints/{endpointsId}:countTokens" }, "generateContent": { "flatPath": "v1/endpoints/{endpointsId}:generateContent", "description": "Generate content with multimodal inputs.", "response": { "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" }, "parameters": { "model": { "location": "path", "pattern": "^endpoints/[^/]+$", "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}`", "required": true } }, "id": "aiplatform.endpoints.generateContent", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "request": { "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" }, "parameterOrder": [ "model" ], "path": "v1/{+model}:generateContent", "httpMethod": "POST" } }, "resources": { "chat": { "methods": { "completions": { "request": { "$ref": "GoogleApiHttpBody" }, "path": "v1/{+endpoint}/chat/completions", "response": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1/endpoints/{endpointsId}/chat/completions", "parameters": { "endpoint": { "description": "Required. The name of the endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "required": true, "pattern": "^endpoints/[^/]+$", "type": "string", "location": "path" } }, "description": "Exposes an OpenAI-compatible endpoint for chat completions.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "httpMethod": "POST", "id": "aiplatform.endpoints.chat.completions", "parameterOrder": [ "endpoint" ] } } }, "operations": { "methods": { "list": { "httpMethod": "GET", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/endpoints/{endpointsId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.endpoints.operations.list", "parameters": { "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^endpoints/[^/]+$", "required": true, "type": "string" }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "pageSize": { "description": "The standard list page size.", "type": "integer", "format": "int32", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "path": "v1/{+name}/operations" }, "delete": { "parameters": { "name": { "location": "path", "type": "string", "pattern": "^endpoints/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/endpoints/{endpointsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+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`.", "parameterOrder": [ "name" ], "httpMethod": "DELETE", "id": "aiplatform.endpoints.operations.delete" }, "get": { "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "type": "string", "location": "path", "pattern": "^endpoints/[^/]+/operations/[^/]+$", "description": "The name of the operation resource." } }, "flatPath": "v1/endpoints/{endpointsId}/operations/{operationsId}", "response": { "$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.", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "id": "aiplatform.endpoints.operations.get" }, "wait": { "parameters": { "name": { "location": "path", "pattern": "^endpoints/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "type": "string", "format": "google-duration" } }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameterOrder": [ "name" ], "id": "aiplatform.endpoints.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/endpoints/{endpointsId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST" }, "cancel": { "path": "v1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1/endpoints/{endpointsId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "location": "path", "type": "string", "pattern": "^endpoints/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled." } }, "id": "aiplatform.endpoints.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "projects": { "methods": { "updateCacheConfig": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "request": { "$ref": "GoogleCloudAiplatformV1CacheConfig" }, "parameters": { "updateMask": { "description": "Optional. The list of fields of `cache_config` to update. Supported paths are `disable_cache`, `retention_config` (and its subfields such as `retention_config.retention_type`), and the special value `*`; any other path returns `INVALID_ARGUMENT`. Fields not covered by the mask keep their stored value. If the mask is omitted, it is treated as an implied mask covering the fields populated in `cache_config`, so updating one field never clears another. `retention_config` is covered only when the request carries it. `disable_cache` is always covered: it is a bare `bool`, so the server cannot tell a request that omits it from one that sets it to `false`. `*` requests full replacement of the resource: every settable field is written from the request, clearing `retention_config` when the request omits it. It cannot be combined with other paths. Prefer naming fields explicitly -- a caller that sends `*` without knowing about a field added to `CacheConfig` later would silently reset that field.", "format": "google-fieldmask", "type": "string", "location": "query" }, "name": { "location": "path", "pattern": "^projects/[^/]+/cacheConfig$", "description": "Identifier. Name of the cache config. Format: - `projects/{project}/cacheConfig`.", "required": true, "type": "string" } }, "id": "aiplatform.projects.updateCacheConfig", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/cacheConfig", "parameterOrder": [ "name" ], "httpMethod": "PATCH", "description": "Updates a cache config." }, "getCacheConfig": { "response": { "$ref": "GoogleCloudAiplatformV1CacheConfig" }, "id": "aiplatform.projects.getCacheConfig", "flatPath": "v1/projects/{projectsId}/cacheConfig", "httpMethod": "GET", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Gets a GenAI cache config.", "parameters": { "name": { "location": "path", "description": "Required. Name of the cache config. Format: - `projects/{project}/cacheConfig`.", "pattern": "^projects/[^/]+/cacheConfig$", "required": true, "type": "string" } } } }, "resources": { "locations": { "methods": { "asyncRetrieveContexts": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:asyncRetrieveContexts", "path": "v1/{+parent}:asyncRetrieveContexts", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "location": "path", "description": "Required. The resource name of the Location from which to retrieve RagContexts. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`." } }, "request": { "$ref": "GoogleCloudAiplatformV1AsyncRetrieveContextsRequest" }, "id": "aiplatform.projects.locations.asyncRetrieveContexts", "parameterOrder": [ "parent" ], "description": "Asynchronous API to retrieves relevant contexts for a query." }, "generateUserScenarios": { "parameters": { "location": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Location to run the job. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "path": "v1/{+location}:generateUserScenarios", "response": { "$ref": "GoogleCloudAiplatformV1GenerateUserScenariosResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:generateUserScenarios", "request": { "$ref": "GoogleCloudAiplatformV1GenerateUserScenariosRequest" }, "id": "aiplatform.projects.locations.generateUserScenarios", "parameterOrder": [ "location" ], "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Generates user scenarios for agent evaluation." }, "get": { "id": "aiplatform.projects.locations.get", "description": "Gets information about a location.", "httpMethod": "GET", "path": "v1/{+name}", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudLocationLocation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Resource name for the location.", "location": "path", "type": "string" } } }, "updateSemanticGovernancePolicyEngine": { "description": "Updates a SemanticGovernancePolicyEngine. This method performs an upsert operation. If the SemanticGovernancePolicyEngine resource does not exist, it will be created. Otherwise, it will be updated.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicyEngine$", "location": "path", "description": "Identifier. The resource name of the SemanticGovernancePolicyEngine. Format: projects/{project}/locations/{location}/semanticGovernancePolicyEngine", "required": true, "type": "string" }, "updateMask": { "format": "google-fieldmask", "location": "query", "description": "Optional. Specifies the fields to be overwritten in the SemanticGovernancePolicyEngine resource by the update. The fields specified in the update_mask are relative to the resource itself. If no update_mask is provided, all fields are overwritten.", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.updateSemanticGovernancePolicyEngine", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicyEngine", "request": { "$ref": "GoogleCloudAiplatformV1SemanticGovernancePolicyEngine" }, "httpMethod": "PATCH" }, "evaluateDataset": { "description": "Evaluates a dataset based on a set of given metrics.", "id": "aiplatform.projects.locations.evaluateDataset", "httpMethod": "POST", "path": "v1/{+location}:evaluateDataset", "parameterOrder": [ "location" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "location": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to evaluate the dataset. Format: `projects/{project}/locations/{location}`" } }, "request": { "$ref": "GoogleCloudAiplatformV1EvaluateDatasetRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:evaluateDataset", "response": { "$ref": "GoogleLongrunningOperation" } }, "deploy": { "request": { "$ref": "GoogleCloudAiplatformV1DeployRequest" }, "id": "aiplatform.projects.locations.deploy", "parameterOrder": [ "destination" ], "httpMethod": "POST", "path": "v1/{+destination}:deploy", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:deploy", "description": "Deploys a model to a new endpoint.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "destination": { "type": "string", "location": "path", "description": "Required. The resource name of the Location to deploy the model in. Format: `projects/{project}/locations/{location}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$" } } }, "retrieveContexts": { "parameterOrder": [ "parent" ], "parameters": { "parent": { "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}`.", "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "location": "path" } }, "path": "v1/{+parent}:retrieveContexts", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:retrieveContexts", "response": { "$ref": "GoogleCloudAiplatformV1RetrieveContextsResponse" }, "description": "Retrieves relevant contexts for a query.", "request": { "$ref": "GoogleCloudAiplatformV1RetrieveContextsRequest" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.retrieveContexts", "httpMethod": "POST" }, "generateSyntheticData": { "request": { "$ref": "GoogleCloudAiplatformV1GenerateSyntheticDataRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1GenerateSyntheticDataResponse" }, "path": "v1/{+location}:generateSyntheticData", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:generateSyntheticData", "description": "Generates synthetic (artificial) data based on a description", "httpMethod": "POST", "id": "aiplatform.projects.locations.generateSyntheticData", "parameterOrder": [ "location" ], "parameters": { "location": { "required": true, "description": "Required. The geographic location where the synthetic data generation request is processed. This should be in the format `projects/{project}/locations/{location}`. For example, `projects/my-project/locations/us-central1`.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "corroborateContent": { "httpMethod": "POST", "path": "v1/{+parent}:corroborateContent", "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.corroborateContent", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1CorroborateContentResponse" }, "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "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", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:corroborateContent", "request": { "$ref": "GoogleCloudAiplatformV1CorroborateContentRequest" }, "description": "Given an input text, it returns a score that evaluates the factuality of the text. It also extracts and returns claims from the text and provides supporting facts." }, "generateLossClusters": { "request": { "$ref": "GoogleCloudAiplatformV1GenerateLossClustersRequest" }, "httpMethod": "POST", "id": "aiplatform.projects.locations.generateLossClusters", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:generateLossClusters", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "location": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "description": "Required. The resource name of the Location. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "parameterOrder": [ "location" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Generates loss clusters from evaluation results. This is a statelss API method that would not modify the EvaluationSet resource.", "path": "v1/{+location}:generateLossClusters" }, "updateRagEngineConfig": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.updateRagEngineConfig", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "PATCH", "description": "Updates a RagEngineConfig.", "request": { "$ref": "GoogleCloudAiplatformV1RagEngineConfig" }, "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig$", "type": "string", "description": "Identifier. The name of the RagEngineConfig. Format: `projects/{project}/locations/{location}/ragEngineConfig`", "required": true } }, "parameterOrder": [ "name" ] }, "generateInstanceRubrics": { "httpMethod": "POST", "path": "v1/{+location}:generateInstanceRubrics", "id": "aiplatform.projects.locations.generateInstanceRubrics", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Generates rubrics for a given prompt. A rubric represents a single testable criterion for evaluation. One input prompt could have multiple rubrics This RPC allows users to get suggested rubrics based on provided prompt, which can then be reviewed and used for subsequent evaluations.", "request": { "$ref": "GoogleCloudAiplatformV1GenerateInstanceRubricsRequest" }, "parameterOrder": [ "location" ], "response": { "$ref": "GoogleCloudAiplatformV1GenerateInstanceRubricsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:generateInstanceRubrics", "parameters": { "location": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Location to generate rubrics from. Format: `projects/{project}/locations/{location}`" } } }, "augmentPrompt": { "parameters": { "parent": { "location": "path", "type": "string", "required": true, "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}`.", "pattern": "^projects/[^/]+/locations/[^/]+$" } }, "id": "aiplatform.projects.locations.augmentPrompt", "path": "v1/{+parent}:augmentPrompt", "request": { "$ref": "GoogleCloudAiplatformV1AugmentPromptRequest" }, "parameterOrder": [ "parent" ], "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:augmentPrompt", "description": "Given an input prompt, it returns augmented prompt from vertex rag store to guide LLM towards generating grounded responses.", "response": { "$ref": "GoogleCloudAiplatformV1AugmentPromptResponse" } }, "list": { "parameters": { "name": { "type": "string", "location": "path", "description": "The resource that owns the locations collection, if applicable.", "required": true, "pattern": "^projects/[^/]+$" }, "pageSize": { "location": "query", "description": "The maximum number of results to return. If not set, the service selects a default.", "format": "int32", "type": "integer" }, "pageToken": { "type": "string", "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." }, "extraLocationTypes": { "repeated": true, "type": "string", "location": "query", "description": "Optional. Do not use this field unless explicitly documented otherwise. This is primarily for internal usage." }, "filter": { "type": "string", "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" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}/locations", "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.", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.list", "flatPath": "v1/projects/{projectsId}/locations", "response": { "$ref": "GoogleCloudLocationListLocationsResponse" }, "httpMethod": "GET" }, "getSemanticGovernancePolicyEngine": { "path": "v1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.getSemanticGovernancePolicyEngine", "parameters": { "name": { "required": true, "description": "Required. The resource name of the SemanticGovernancePolicyEngine to retrieve. Format: projects/{project}/locations/{location}/semanticGovernancePolicyEngine", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicyEngine$", "location": "path" } }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicyEngine", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1SemanticGovernancePolicyEngine" }, "description": "Gets a SemanticGovernancePolicyEngine. A SemanticGovernancePolicyEngine is a singleton resource that is created when its parent is created, and deleted when its parent is deleted. This method retrieves the current state of the Semantic Governance Policy Engine." }, "evaluateInstances": { "path": "v1/{+location}:evaluateInstances", "request": { "$ref": "GoogleCloudAiplatformV1EvaluateInstancesRequest" }, "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Evaluates instances based on a given metric.", "parameters": { "location": { "description": "Required. The resource name of the Location to evaluate the instances. Format: `projects/{project}/locations/{location}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "id": "aiplatform.projects.locations.evaluateInstances", "response": { "$ref": "GoogleCloudAiplatformV1EvaluateInstancesResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:evaluateInstances", "parameterOrder": [ "location" ] }, "askContexts": { "description": "Agentic Retrieval Ask API for RAG.", "path": "v1/{+parent}:askContexts", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "description": "Required. The resource name of the Location from which to retrieve RagContexts. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`.", "required": true, "location": "path" } }, "id": "aiplatform.projects.locations.askContexts", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}:askContexts", "request": { "$ref": "GoogleCloudAiplatformV1AskContextsRequest" }, "httpMethod": "POST", "response": { "$ref": "GoogleCloudAiplatformV1AskContextsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ] }, "getRagEngineConfig": { "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1RagEngineConfig" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig$", "description": "Required. The name of the RagEngineConfig resource. Format: `projects/{project}/locations/{location}/ragEngineConfig`", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.getRagEngineConfig", "httpMethod": "GET", "description": "Gets a RagEngineConfig.", "path": "v1/{+name}" } }, "resources": { "tuningJobs": { "methods": { "cancel": { "parameters": { "name": { "description": "Required. The name of the tuning job to cancel. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+$", "location": "path", "type": "string" } }, "path": "v1/{+name}:cancel", "parameterOrder": [ "name" ], "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`.", "request": { "$ref": "GoogleCloudAiplatformV1CancelTuningJobRequest" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.tuningJobs.cancel", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}:cancel", "httpMethod": "POST" }, "get": { "response": { "$ref": "GoogleCloudAiplatformV1TuningJob" }, "description": "Gets a tuning job.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}", "parameters": { "name": { "location": "path", "description": "Required. The name of the tuning job to retrieve. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}`", "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+$", "type": "string", "required": true } }, "id": "aiplatform.projects.locations.tuningJobs.get", "path": "v1/{+name}", "httpMethod": "GET", "parameterOrder": [ "name" ] }, "list": { "path": "v1/{+parent}/tuningJobs", "httpMethod": "GET", "parameterOrder": [ "parent" ], "parameters": { "filter": { "location": "query", "description": "Optional. The standard list filter.", "type": "string" }, "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." }, "pageSize": { "location": "query", "format": "int32", "type": "integer", "description": "Optional. The standard list page size." }, "parent": { "type": "string", "location": "path", "description": "Required. The resource name of the location to list the tuning jobs from. Format: `projects/{project}/locations/{location}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs", "id": "aiplatform.projects.locations.tuningJobs.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1ListTuningJobsResponse" }, "description": "Lists tuning jobs in a location." }, "create": { "description": "Creates a tuning job. A created tuning job will be subsequently executed to start the model tuning process.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.tuningJobs.create", "httpMethod": "POST", "path": "v1/{+parent}/tuningJobs", "request": { "$ref": "GoogleCloudAiplatformV1TuningJob" }, "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1TuningJob" }, "parameters": { "parent": { "type": "string", "required": true, "description": "Required. The resource name of the location to create the tuning job in. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs" }, "rebaseTunedModel": { "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the location in which to rebase the Model. Format: `projects/{project}/locations/{location}`" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.tuningJobs.rebaseTunedModel", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs:rebaseTunedModel", "request": { "$ref": "GoogleCloudAiplatformV1RebaseTunedModelRequest" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/tuningJobs:rebaseTunedModel", "parameterOrder": [ "parent" ], "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.", "httpMethod": "POST" } }, "resources": { "operations": { "methods": { "delete": { "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+/operations/[^/]+$", "type": "string", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "httpMethod": "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`.", "id": "aiplatform.projects.locations.tuningJobs.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "id": "aiplatform.projects.locations.tuningJobs.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.", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+/operations/[^/]+$" }, "timeout": { "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "location": "query" } }, "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST" }, "cancel": { "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+/operations/[^/]+$", "location": "path" } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}:cancel", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.tuningJobs.operations.cancel", "httpMethod": "POST", "parameterOrder": [ "name" ] }, "list": { "id": "aiplatform.projects.locations.tuningJobs.operations.list", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "parameters": { "name": { "type": "string", "required": true, "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+$", "description": "The name of the operation's parent resource." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean", "location": "query" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "path": "v1/{+name}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}/operations" }, "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tuningJobs/{tuningJobsId}/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": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.tuningJobs.operations.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "location": "path", "required": true, "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/tuningJobs/[^/]+/operations/[^/]+$" } }, "parameterOrder": [ "name" ], "httpMethod": "GET", "path": "v1/{+name}" } } } } }, "featurestores": { "methods": { "setIamPolicy": { "id": "aiplatform.projects.locations.featurestores.setIamPolicy", "response": { "$ref": "GoogleIamV1Policy" }, "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "parameterOrder": [ "resource" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:setIamPolicy", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "parameters": { "resource": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "type": "string", "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" } }, "path": "v1/{+resource}:setIamPolicy", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "testIamPermissions": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:testIamPermissions", "httpMethod": "POST", "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "path": "v1/{+resource}:testIamPermissions", "parameterOrder": [ "resource" ], "id": "aiplatform.projects.locations.featurestores.testIamPermissions", "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", "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.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "location": "path" }, "permissions": { "type": "string", "location": "query", "repeated": true, "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions)." } } }, "batchReadFeatureValues": { "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.batchReadFeatureValues", "parameterOrder": [ "featurestore" ], "path": "v1/{+featurestore}:batchReadFeatureValues", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "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.", "parameters": { "featurestore": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "required": true, "description": "Required. The resource name of the Featurestore from which to query Feature values. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:batchReadFeatureValues", "request": { "$ref": "GoogleCloudAiplatformV1BatchReadFeatureValuesRequest" } }, "create": { "id": "aiplatform.projects.locations.featurestores.create", "httpMethod": "POST", "parameterOrder": [ "parent" ], "path": "v1/{+parent}/featurestores", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a new Featurestore in a given project and location.", "request": { "$ref": "GoogleCloudAiplatformV1Featurestore" }, "parameters": { "featurestoreId": { "location": "query", "type": "string", "description": "Required. The ID to use for this Featurestore, which will become the final component of the Featurestore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location." }, "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to create Featurestores. Format: `projects/{project}/locations/{location}`", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores", "response": { "$ref": "GoogleLongrunningOperation" } }, "delete": { "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "description": "Required. The name of the Featurestore to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`" }, "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.)" } }, "path": "v1/{+name}", "id": "aiplatform.projects.locations.featurestores.delete", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a single Featurestore. The Featurestore must not contain any EntityTypes or `force` must be set to true for the request to succeed.", "httpMethod": "DELETE" }, "searchFeatures": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores:searchFeatures", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1SearchFeaturesResponse" }, "httpMethod": "GET", "description": "Searches Features matching a query in a given project.", "path": "v1/{+location}/featurestores:searchFeatures", "id": "aiplatform.projects.locations.featurestores.searchFeatures", "parameterOrder": [ "location" ], "parameters": { "query": { "type": "string", "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" }, "location": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to search Features. Format: `projects/{project}/locations/{location}`", "type": "string", "location": "path" }, "pageToken": { "type": "string", "description": "A page token, received from a previous FeaturestoreService.SearchFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.SearchFeatures, except `page_size`, must match the call that provided the page token.", "location": "query" }, "pageSize": { "format": "int32", "type": "integer", "location": "query", "description": "The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 100 Features will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100." } } }, "patch": { "parameters": { "updateMask": { "location": "query", "description": "Field mask is used to specify the fields to be overwritten in the Featurestore resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `online_serving_config.fixed_node_count` * `online_serving_config.scaling` * `online_storage_ttl_days`", "format": "google-fieldmask", "type": "string" }, "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "type": "string", "description": "Output only. Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", "required": true } }, "request": { "$ref": "GoogleCloudAiplatformV1Featurestore" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.featurestores.patch", "parameterOrder": [ "name" ], "path": "v1/{+name}", "description": "Updates the parameters of a single Featurestore.", "httpMethod": "PATCH", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameterOrder": [ "parent" ], "httpMethod": "GET", "description": "Lists Featurestores in a given project and location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/featurestores", "id": "aiplatform.projects.locations.featurestores.list", "response": { "$ref": "GoogleCloudAiplatformV1ListFeaturestoresResponse" }, "parameters": { "readMask": { "type": "string", "location": "query", "description": "Mask specifying which fields to read.", "format": "google-fieldmask" }, "pageToken": { "description": "A page token, received from a previous FeaturestoreService.ListFeaturestores call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeaturestores must match the call that provided the page token.", "type": "string", "location": "query" }, "filter": { "description": "Lists the featurestores that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `online_serving_config.fixed_node_count`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` Featurestores created or updated after 2020-01-01. * `labels.env = \"prod\"` Featurestores with label \"env\" set to \"prod\".", "location": "query", "type": "string" }, "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "description": "Required. The resource name of the Location to list Featurestores. Format: `projects/{project}/locations/{location}`", "required": true }, "pageSize": { "location": "query", "format": "int32", "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.", "type": "integer" }, "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" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores" }, "get": { "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "description": "Required. The name of the Featurestore resource.", "required": true } }, "response": { "$ref": "GoogleCloudAiplatformV1Featurestore" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}", "description": "Gets details of a single Featurestore.", "path": "v1/{+name}", "id": "aiplatform.projects.locations.featurestores.get", "parameterOrder": [ "name" ], "httpMethod": "GET" }, "getIamPolicy": { "response": { "$ref": "GoogleIamV1Policy" }, "parameters": { "resource": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "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." }, "options.requestedPolicyVersion": { "location": "query", "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).", "format": "int32" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}:getIamPolicy", "path": "v1/{+resource}: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.", "id": "aiplatform.projects.locations.featurestores.getIamPolicy", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "resource" ], "httpMethod": "POST" } }, "resources": { "entityTypes": { "methods": { "readFeatureValues": { "request": { "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:readFeatureValues", "parameters": { "entityType": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "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`.", "type": "string", "required": true } }, "response": { "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponse" }, "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+entityType}:readFeatureValues", "id": "aiplatform.projects.locations.featurestores.entityTypes.readFeatureValues", "parameterOrder": [ "entityType" ], "description": "Reads Feature values of a specific entity of an EntityType. For reading feature values of multiple entities of an EntityType, please use StreamingReadFeatureValues." }, "list": { "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes", "response": { "$ref": "GoogleCloudAiplatformV1ListEntityTypesResponse" }, "httpMethod": "GET", "path": "v1/{+parent}/entityTypes", "description": "Lists EntityTypes in a given Featurestore.", "id": "aiplatform.projects.locations.featurestores.entityTypes.list", "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "description": "Required. The resource name of the Featurestore to list EntityTypes. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", "type": "string", "required": true }, "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." }, "readMask": { "description": "Mask specifying which fields to read.", "type": "string", "format": "google-fieldmask", "location": "query" }, "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": { "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.", "location": "query", "type": "integer", "format": "int32" }, "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: * `entity_type_id` * `create_time` * `update_time`", "type": "string", "location": "query" } } }, "writeFeatureValues": { "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1WriteFeatureValuesRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:writeFeatureValues", "response": { "$ref": "GoogleCloudAiplatformV1WriteFeatureValuesResponse" }, "parameterOrder": [ "entityType" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Writes Feature values of one or more entities of an EntityType. The Feature values are merged into existing entities if any. The Feature values to be written must have timestamp within the online storage retention.", "id": "aiplatform.projects.locations.featurestores.entityTypes.writeFeatureValues", "parameters": { "entityType": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "type": "string", "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`.", "location": "path" } }, "path": "v1/{+entityType}:writeFeatureValues" }, "streamingReadFeatureValues": { "httpMethod": "POST", "parameterOrder": [ "entityType" ], "response": { "$ref": "GoogleCloudAiplatformV1ReadFeatureValuesResponse" }, "path": "v1/{+entityType}:streamingReadFeatureValues", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:streamingReadFeatureValues", "id": "aiplatform.projects.locations.featurestores.entityTypes.streamingReadFeatureValues", "description": "Reads Feature values for multiple entities. Depending on their size, data for different entities may be broken up across multiple responses.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "entityType": { "description": "Required. The resource name of the entities' type. Value format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "type": "string", "location": "path" } }, "request": { "$ref": "GoogleCloudAiplatformV1StreamingReadFeatureValuesRequest" } }, "testIamPermissions": { "parameterOrder": [ "resource" ], "parameters": { "resource": { "location": "path", "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "type": "string" }, "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)." } }, "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.", "path": "v1/{+resource}:testIamPermissions", "id": "aiplatform.projects.locations.featurestores.entityTypes.testIamPermissions", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:testIamPermissions", "httpMethod": "POST", "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" } }, "getIamPolicy": { "response": { "$ref": "GoogleIamV1Policy" }, "path": "v1/{+resource}:getIamPolicy", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}: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.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "type": "string", "location": "path" }, "options.requestedPolicyVersion": { "type": "integer", "format": "int32", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "location": "query" } }, "id": "aiplatform.projects.locations.featurestores.entityTypes.getIamPolicy", "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "httpMethod": "POST" }, "create": { "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.featurestores.entityTypes.create", "path": "v1/{+parent}/entityTypes", "request": { "$ref": "GoogleCloudAiplatformV1EntityType" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "type": "string", "description": "Required. The resource name of the Featurestore to create EntityTypes. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`", "location": "path" }, "entityTypeId": { "type": "string", "description": "Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a featurestore.", "location": "query" } }, "description": "Creates a new EntityType in a given Featurestore.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" } }, "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}", "httpMethod": "DELETE", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "force": { "type": "boolean", "location": "query", "description": "If set to true, any Features for this EntityType will also be deleted. (Otherwise, the request will only work if the EntityType has no Features.)" }, "name": { "required": true, "type": "string", "description": "Required. The name of the EntityType to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "location": "path" } }, "description": "Deletes a single EntityType. The EntityType must not have any Features or `force` must be set to true for the request to succeed.", "id": "aiplatform.projects.locations.featurestores.entityTypes.delete" }, "get": { "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featurestores.entityTypes.get", "response": { "$ref": "GoogleCloudAiplatformV1EntityType" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the EntityType resource. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`" } }, "path": "v1/{+name}", "description": "Gets details of a single EntityType." }, "setIamPolicy": { "parameters": { "resource": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path" } }, "id": "aiplatform.projects.locations.featurestores.entityTypes.setIamPolicy", "parameterOrder": [ "resource" ], "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:setIamPolicy", "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "path": "v1/{+resource}:setIamPolicy", "response": { "$ref": "GoogleIamV1Policy" } }, "exportFeatureValues": { "parameterOrder": [ "entityType" ], "parameters": { "entityType": { "required": true, "description": "Required. The resource name of the EntityType from which to export Feature values. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$" } }, "id": "aiplatform.projects.locations.featurestores.entityTypes.exportFeatureValues", "path": "v1/{+entityType}:exportFeatureValues", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:exportFeatureValues", "description": "Exports Feature values from all the entities of a target EntityType.", "request": { "$ref": "GoogleCloudAiplatformV1ExportFeatureValuesRequest" }, "httpMethod": "POST" }, "deleteFeatureValues": { "parameters": { "entityType": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "type": "string", "description": "Required. The resource name of the EntityType grouping the Features for which values are being deleted from. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}`", "required": true } }, "parameterOrder": [ "entityType" ], "description": "Delete Feature values from Featurestore. The progress of the deletion is tracked by the returned operation. The deleted feature values are guaranteed to be invisible to subsequent read operations after the operation is marked as successfully done. If a delete feature values operation fails, the feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same delete request again and wait till the new operation returned is marked as successfully done.", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+entityType}:deleteFeatureValues", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:deleteFeatureValues", "request": { "$ref": "GoogleCloudAiplatformV1DeleteFeatureValuesRequest" }, "id": "aiplatform.projects.locations.featurestores.entityTypes.deleteFeatureValues", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "importFeatureValues": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}:importFeatureValues", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1ImportFeatureValuesRequest" }, "parameterOrder": [ "entityType" ], "id": "aiplatform.projects.locations.featurestores.entityTypes.importFeatureValues", "path": "v1/{+entityType}:importFeatureValues", "parameters": { "entityType": { "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "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}`", "location": "path", "type": "string", "required": true } }, "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.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "id": "aiplatform.projects.locations.featurestores.entityTypes.patch", "description": "Updates the parameters of a single EntityType.", "httpMethod": "PATCH", "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1EntityType" }, "parameters": { "updateMask": { "format": "google-fieldmask", "location": "query", "type": "string", "description": "Field mask is used to specify the fields to be overwritten in the EntityType resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `monitoring_config.snapshot_analysis.disabled` * `monitoring_config.snapshot_analysis.monitoring_interval_days` * `monitoring_config.snapshot_analysis.staleness_days` * `monitoring_config.import_features_analysis.state` * `monitoring_config.import_features_analysis.anomaly_detection_baseline` * `monitoring_config.numerical_threshold_config.value` * `monitoring_config.categorical_threshold_config.value` * `offline_storage_ttl_days`" }, "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "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", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}", "response": { "$ref": "GoogleCloudAiplatformV1EntityType" } } }, "resources": { "operations": { "methods": { "get": { "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.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": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}", "parameterOrder": [ "name" ], "httpMethod": "GET" }, "list": { "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.list", "path": "v1/{+name}/operations", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations", "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "type": "string", "location": "path", "description": "The name of the operation's parent resource.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "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." }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.delete", "path": "v1/{+name}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "httpMethod": "DELETE", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" } }, "wait": { "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.wait", "httpMethod": "POST", "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "timeout": { "type": "string", "location": "query", "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.", "format": "google-duration" }, "name": { "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "required": true, "location": "path" } }, "parameterOrder": [ "name" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featurestores.entityTypes.operations.cancel", "httpMethod": "POST", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/operations/{operationsId}:cancel", "parameters": { "name": { "type": "string", "required": true, "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled." } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "path": "v1/{+name}:cancel" } } }, "features": { "methods": { "patch": { "parameters": { "name": { "location": "path", "description": "Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", "type": "string", "required": true }, "updateMask": { "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", "type": "string", "format": "google-fieldmask" } }, "response": { "$ref": "GoogleCloudAiplatformV1Feature" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", "httpMethod": "PATCH", "description": "Updates the parameters of a single Feature.", "request": { "$ref": "GoogleCloudAiplatformV1Feature" }, "id": "aiplatform.projects.locations.featurestores.entityTypes.features.patch", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "path": "v1/{+name}" }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "description": "Gets details of a single Feature.", "path": "v1/{+name}", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.get", "response": { "$ref": "GoogleCloudAiplatformV1Feature" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", "parameters": { "name": { "location": "path", "type": "string", "description": "Required. The name of the Feature resource. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", "required": true } } }, "batchCreate": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features:batchCreate", "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.batchCreate", "path": "v1/{+parent}/features:batchCreate", "parameters": { "parent": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "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" } }, "description": "Creates a batch of Features in a given EntityType.", "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1BatchCreateFeaturesRequest" } }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "path": "v1/{+parent}/features", "description": "Lists Features in a given EntityType.", "parameters": { "latestStatsCount": { "format": "int32", "type": "integer", "location": "query", "description": "Only applicable for Vertex AI Feature Store (Legacy). If set, return the most recent ListFeaturesRequest.latest_stats_count of stats for each Feature in response. Valid value is [0, 10]. If number of stats exists \u003c ListFeaturesRequest.latest_stats_count, return all existing stats." }, "readMask": { "description": "Mask specifying which fields to read.", "type": "string", "format": "google-fieldmask", "location": "query" }, "orderBy": { "location": "query", "type": "string", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `feature_id` * `value_type` (Not supported for FeatureRegistry Feature) * `create_time` * `update_time`" }, "pageSize": { "location": "query", "format": "int32", "description": "The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 1000 Features will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.", "type": "integer" }, "parent": { "location": "path", "description": "Required. The resource name of the Location to list Features. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "type": "string" }, "pageToken": { "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", "type": "string" }, "filter": { "type": "string", "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.", "location": "query" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features", "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1ListFeaturesResponse" }, "id": "aiplatform.projects.locations.featurestores.entityTypes.features.list" }, "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/features", "parameters": { "featureId": { "description": "Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.", "location": "query", "type": "string" }, "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+$", "required": true, "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" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.create", "request": { "$ref": "GoogleCloudAiplatformV1Feature" }, "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "description": "Creates a new Feature in a given EntityType.", "parameterOrder": [ "parent" ] }, "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", "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", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featurestores.entityTypes.features.delete", "parameterOrder": [ "name" ], "description": "Deletes a single Feature.", "httpMethod": "DELETE" } }, "resources": { "operations": { "methods": { "get": { "path": "v1/{+name}", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.get", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}", "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." }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "timeout": { "location": "query", "format": "google-duration", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." }, "name": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:wait", "parameterOrder": [ "name" ], "path": "v1/{+name}:wait", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "httpMethod": "POST", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "location": "path" } }, "parameterOrder": [ "name" ] }, "list": { "path": "v1/{+name}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations", "httpMethod": "GET", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featurestores.entityTypes.features.operations.list", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+$", "description": "The name of the operation's parent resource.", "required": true, "location": "path" }, "pageSize": { "format": "int32", "description": "The standard list page size.", "location": "query", "type": "integer" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } } }, "delete": { "httpMethod": "DELETE", "id": "aiplatform.projects.locations.featurestores.entityTypes.features.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`.", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/entityTypes/{entityTypesId}/features/{featuresId}/operations/{operationsId}", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/entityTypes/[^/]+/features/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "required": true, "type": "string" } }, "response": { "$ref": "GoogleProtobufEmpty" } } } } } } } }, "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.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}", "parameters": { "name": { "description": "The name of the operation resource.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "GET", "id": "aiplatform.projects.locations.featurestores.operations.get", "path": "v1/{+name}", "parameterOrder": [ "name" ] }, "delete": { "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featurestores.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": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}", "parameters": { "name": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "location": "path" } } }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.projects.locations.featurestores.operations.list", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations", "parameters": { "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "pageSize": { "format": "int32", "description": "The standard list page size.", "type": "integer", "location": "query" }, "name": { "required": true, "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+$", "location": "path", "type": "string" } }, "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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}/operations", "httpMethod": "GET" }, "cancel": { "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", "required": true } }, "id": "aiplatform.projects.locations.featurestores.operations.cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featurestores/{featurestoresId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featurestores.operations.wait", "parameters": { "timeout": { "type": "string", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query" }, "name": { "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/featurestores/[^/]+/operations/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait" } } } } }, "interactionsHttp": { "methods": { "create": { "response": { "$ref": "GoogleApiHttpBody" }, "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/interactionsHttp", "id": "aiplatform.projects.locations.interactionsHttp.create", "path": "v1/{+parent}/interactionsHttp", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The parent resource where this interaction will be created. Format: `projects/{project}/locations/{location}` Supported only by the Vertex API only." } }, "request": { "$ref": "GenaiVertexV1CreateInteractionHttpRequest" }, "description": "Creates a new interaction." }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Retrieves the full details of a single interaction based on its `Interaction.id`.", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/interactionsHttp/{interactionsHttpId}", "response": { "$ref": "GoogleApiHttpBody" }, "parameters": { "stream": { "description": "If true, streams the interaction events as Server-Sent Events.", "location": "query", "type": "boolean" }, "lastEventId": { "location": "query", "type": "string", "description": "If set, resumes the interaction stream from the chunk after the event marked by the event id. Can only be used if `stream` is true." }, "name": { "location": "path", "type": "string", "description": "Required. The name of the interaction to retrieve. Format: interactions/{interaction}", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/interactionsHttp/[^/]+$" } }, "httpMethod": "GET", "path": "v1/{+name}", "id": "aiplatform.projects.locations.interactionsHttp.get" }, "cancel": { "response": { "$ref": "GoogleApiHttpBody" }, "path": "v1/{+name}/cancel", "description": "Cancels an interaction by id. This only applies to background interactions that are still running.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/interactionsHttp/{interactionsHttpId}/cancel", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.interactionsHttp.cancel", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/interactionsHttp/[^/]+$", "description": "Required. The name of the interaction to cancel. Format: `interactions/{interaction}`.", "type": "string", "required": true } } } } }, "migratableResources": { "resources": { "operations": { "methods": { "get": { "path": "v1/{+name}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}", "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "type": "string" } }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "id": "aiplatform.projects.locations.migratableResources.operations.get" }, "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "parameters": { "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+$", "required": true, "type": "string" }, "pageSize": { "description": "The standard list page size.", "type": "integer", "format": "int32", "location": "query" } }, "id": "aiplatform.projects.locations.migratableResources.operations.list", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations", "path": "v1/{+name}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET" }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}:cancel", "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`.", "id": "aiplatform.projects.locations.migratableResources.operations.cancel", "path": "v1/{+name}:cancel", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "required": true, "type": "string" } } }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "id": "aiplatform.projects.locations.migratableResources.operations.wait", "path": "v1/{+name}:wait", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "description": "The name of the operation resource to wait on.", "required": true }, "timeout": { "format": "google-duration", "location": "query", "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" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}:wait", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "id": "aiplatform.projects.locations.migratableResources.operations.delete", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/migratableResources/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources/{migratableResourcesId}/operations/{operationsId}", "path": "v1/{+name}" } } } }, "methods": { "search": { "httpMethod": "POST", "id": "aiplatform.projects.locations.migratableResources.search", "response": { "$ref": "GoogleCloudAiplatformV1SearchMigratableResourcesResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources:search", "request": { "$ref": "GoogleCloudAiplatformV1SearchMigratableResourcesRequest" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Searches all of the resources in automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com that can be migrated to Vertex AI's given location.", "path": "v1/{+parent}/migratableResources:search", "parameterOrder": [ "parent" ], "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "required": true, "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}`" } } }, "batchMigrate": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "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", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/migratableResources:batchMigrate", "path": "v1/{+parent}/migratableResources:batchMigrate", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.migratableResources.batchMigrate", "request": { "$ref": "GoogleCloudAiplatformV1BatchMigrateResourcesRequest" } } } }, "evaluationMetrics": { "methods": { "get": { "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/evaluationMetrics/[^/]+$", "description": "Required. The name of the EvaluationMetric resource. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}`", "type": "string", "location": "path" } }, "response": { "$ref": "GoogleCloudAiplatformV1EvaluationMetric" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationMetrics/{evaluationMetricsId}", "description": "Gets an EvaluationMetric.", "id": "aiplatform.projects.locations.evaluationMetrics.get", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "httpMethod": "GET" }, "create": { "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "description": "Required. The resource name of the Location to create the EvaluationMetric in. Format: `projects/{project}/locations/{location}`", "required": true }, "evaluationMetricId": { "type": "string", "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.", "location": "query" } }, "request": { "$ref": "GoogleCloudAiplatformV1EvaluationMetric" }, "path": "v1/{+parent}/evaluationMetrics", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationMetrics", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1EvaluationMetric" }, "httpMethod": "POST", "id": "aiplatform.projects.locations.evaluationMetrics.create", "parameterOrder": [ "parent" ], "description": "Creates an EvaluationMetric." }, "delete": { "path": "v1/{+name}", "id": "aiplatform.projects.locations.evaluationMetrics.delete", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "Required. The name of the EvaluationMetric resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}`", "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/evaluationMetrics/[^/]+$", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationMetrics/{evaluationMetricsId}", "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes an EvaluationMetric.", "parameterOrder": [ "name" ] }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/evaluationMetrics", "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": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location from which to list the EvaluationMetrics. Format: `projects/{project}/locations/{location}`", "location": "path" }, "orderBy": { "location": "query", "type": "string", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending." }, "pageToken": { "location": "query", "description": "Optional. A page token, received from a previous `ListEvaluationMetrics` call. Provide this to retrieve the subsequent page.", "type": "string" }, "pageSize": { "type": "integer", "format": "int32", "location": "query", "description": "Optional. The maximum number of EvaluationMetrics to return." } }, "description": "Lists EvaluationMetrics.", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationMetrics.list", "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1ListEvaluationMetricsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationMetrics" } } }, "semanticGovernancePolicies": { "methods": { "list": { "response": { "$ref": "GoogleCloudAiplatformV1ListSemanticGovernancePoliciesResponse" }, "parameterOrder": [ "parent" ], "parameters": { "pageSize": { "format": "int32", "type": "integer", "description": "Optional. The list page size. If zero, a default page size of 10 is used.", "location": "query" }, "pageToken": { "location": "query", "type": "string", "description": "Optional. The standard list page token." }, "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location from which to list the SemanticGovernancePolicies. Format: `projects/{project}/locations/{location}`", "type": "string", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists SemanticGovernancePolicies in a given location.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies", "id": "aiplatform.projects.locations.semanticGovernancePolicies.list", "path": "v1/{+parent}/semanticGovernancePolicies", "httpMethod": "GET" }, "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+$", "description": "Required. The name of the SemanticGovernancePolicy resource. Format: `projects/{project}/locations/{location}/semanticGovernancePolicies/{semantic_governance_policy}`", "location": "path" } }, "response": { "$ref": "GoogleCloudAiplatformV1SemanticGovernancePolicy" }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a SemanticGovernancePolicy.", "httpMethod": "GET", "id": "aiplatform.projects.locations.semanticGovernancePolicies.get" }, "patch": { "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "updateMask": { "description": "Optional. `update_mask` is used to specify the fields to be overwritten in the SemanticGovernancePolicy resource by the update. The fields specified in the `update_mask` are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the mask is not present, then all fields that are populated in the request message will be overwritten. Set the `update_mask` to `*` to override all fields.", "location": "query", "format": "google-fieldmask", "type": "string" }, "name": { "type": "string", "required": true, "description": "Identifier. Resource name of the SemanticGovernancePolicy.", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+$", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}", "httpMethod": "PATCH", "description": "Updates a SemanticGovernancePolicy.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.semanticGovernancePolicies.patch", "request": { "$ref": "GoogleCloudAiplatformV1SemanticGovernancePolicy" }, "parameterOrder": [ "name" ], "path": "v1/{+name}" }, "create": { "request": { "$ref": "GoogleCloudAiplatformV1SemanticGovernancePolicy" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location into which to create the SemanticGovernancePolicy. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string" }, "semanticGovernancePolicyId": { "description": "Required. The ID to use for the SemanticGovernancePolicy, which will become the final component of the SemanticGovernancePolicy's resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The first character cannot be a number or hyphen. The last character must be a letter or a number.", "location": "query", "type": "string" } }, "description": "Creates a SemanticGovernancePolicy.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "parent" ], "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies", "id": "aiplatform.projects.locations.semanticGovernancePolicies.create", "path": "v1/{+parent}/semanticGovernancePolicies" }, "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "etag": { "description": "Optional. The etag of the SemanticGovernancePolicy. If an etag is provided and does not match the current etag of the SemanticGovernancePolicy, deletion will be blocked and an ABORTED error will be returned.", "location": "query", "type": "string" }, "name": { "type": "string", "description": "Required. The name of the SemanticGovernancePolicy resource to be deleted. Format: `projects/{project}/locations/{location}/semanticGovernancePolicies/{semantic_governance_policy}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a SemanticGovernancePolicy.", "id": "aiplatform.projects.locations.semanticGovernancePolicies.delete", "httpMethod": "DELETE", "path": "v1/{+name}", "parameterOrder": [ "name" ] } }, "resources": { "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`.", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+$", "description": "The name of the operation's parent resource." }, "pageSize": { "description": "The standard list page size.", "type": "integer", "format": "int32", "location": "query" }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET", "path": "v1/{+name}/operations", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations", "id": "aiplatform.projects.locations.semanticGovernancePolicies.operations.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "parameterOrder": [ "name" ], "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+/operations/[^/]+$" } }, "id": "aiplatform.projects.locations.semanticGovernancePolicies.operations.get", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/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.", "httpMethod": "GET" }, "wait": { "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.semanticGovernancePolicies.operations.wait", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:wait", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+/operations/[^/]+$", "required": true, "location": "path", "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" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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." }, "delete": { "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`.", "path": "v1/{+name}", "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.semanticGovernancePolicies.operations.delete", "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+/operations/[^/]+$", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "path": "v1/{+name}: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`.", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicies/[^/]+/operations/[^/]+$", "location": "path" } }, "httpMethod": "POST", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.semanticGovernancePolicies.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicies/{semanticGovernancePoliciesId}/operations/{operationsId}:cancel" } } } } }, "notebookExecutionJobs": { "resources": { "operations": { "methods": { "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/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.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.get", "parameterOrder": [ "name" ], "httpMethod": "GET" }, "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.", "parameters": { "name": { "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on." }, "timeout": { "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "type": "string" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.wait" }, "list": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.list", "parameterOrder": [ "name" ], "parameters": { "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "required": true }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." } }, "path": "v1/{+name}/operations", "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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameterOrder": [ "name" ], "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}:cancel", "path": "v1/{+name}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.cancel", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "type": "string" } }, "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": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}/operations/{operationsId}", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+/operations/[^/]+$", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.notebookExecutionJobs.operations.delete", "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`.", "httpMethod": "DELETE", "path": "v1/{+name}" } } } }, "methods": { "create": { "id": "aiplatform.projects.locations.notebookExecutionJobs.create", "parameters": { "parent": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`" }, "notebookExecutionJobId": { "location": "query", "description": "Optional. User specified ID for the NotebookExecutionJob.", "type": "string" } }, "description": "Creates a NotebookExecutionJob.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/notebookExecutionJobs", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1NotebookExecutionJob" } }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", "description": "Required. The name of the NotebookExecutionJob resource to be deleted.", "required": true } }, "parameterOrder": [ "name" ], "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}", "description": "Deletes a NotebookExecutionJob.", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "id": "aiplatform.projects.locations.notebookExecutionJobs.delete" }, "get": { "description": "Gets a NotebookExecutionJob.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1NotebookExecutionJob" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs/{notebookExecutionJobsId}", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookExecutionJobs.get", "parameters": { "name": { "location": "path", "description": "Required. The name of the NotebookExecutionJob resource.", "pattern": "^projects/[^/]+/locations/[^/]+/notebookExecutionJobs/[^/]+$", "required": true, "type": "string" }, "view": { "location": "query", "type": "string", "enum": [ "NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED", "NOTEBOOK_EXECUTION_JOB_VIEW_BASIC", "NOTEBOOK_EXECUTION_JOB_VIEW_FULL" ], "description": "Optional. The NotebookExecutionJob view. Defaults to BASIC.", "enumDescriptions": [ "When unspecified, the API defaults to the BASIC view.", "Includes all fields except for direct notebook inputs.", "Includes all fields." ] } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "pageToken": { "description": "Optional. The standard list page token. Typically obtained via ListNotebookExecutionJobsResponse.next_page_token of the previous NotebookService.ListNotebookExecutionJobs call.", "type": "string", "location": "query" }, "filter": { "description": "Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookExecutionJob` supports = and !=. `notebookExecutionJob` represents the NotebookExecutionJob ID. * `displayName` supports = and != and regex. * `schedule` supports = and != and regex. Some examples: * `notebookExecutionJob=\"123\"` * `notebookExecutionJob=\"my-execution-job\"` * `displayName=\"myDisplayName\"` and `displayName=~\"myDisplayNameRegex\"`", "type": "string", "location": "query" }, "view": { "location": "query", "type": "string", "enum": [ "NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED", "NOTEBOOK_EXECUTION_JOB_VIEW_BASIC", "NOTEBOOK_EXECUTION_JOB_VIEW_FULL" ], "enumDescriptions": [ "When unspecified, the API defaults to the BASIC view.", "Includes all fields except for direct notebook inputs.", "Includes all fields." ], "description": "Optional. The NotebookExecutionJob view. Defaults to BASIC." }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "location": "path", "required": true, "description": "Required. The resource name of the Location from which to list the NotebookExecutionJobs. Format: `projects/{project}/locations/{location}`" }, "pageSize": { "description": "Optional. The standard list page size.", "type": "integer", "format": "int32", "location": "query" }, "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: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", "location": "query", "type": "string" } }, "path": "v1/{+parent}/notebookExecutionJobs", "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.notebookExecutionJobs.list", "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookExecutionJobs", "description": "Lists NotebookExecutionJobs in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1ListNotebookExecutionJobsResponse" } } } }, "reasoningEngines": { "resources": { "sessions": { "resources": { "events": { "methods": { "list": { "parameterOrder": [ "parent" ], "path": "v1/{+parent}/events", "parameters": { "orderBy": { "type": "string", "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `timestamp` Example: `timestamp desc`." }, "pageToken": { "location": "query", "description": "Optional. The next_page_token value returned from a previous list SessionService.ListEvents call.", "type": "string" }, "filter": { "location": "query", "description": "Optional. The standard list filter. Supported fields: * `timestamp` range (i.e. `timestamp\u003e=\"2025-01-31T11:30:00-04:00\"` where the timestamp is in RFC 3339 format) More detail in [AIP-160](https://google.aip.dev/160).", "type": "string" }, "pageSize": { "description": "Optional. The maximum number of events to return. The service may return fewer than this value. If unspecified, at most 100 events will be returned. These events are ordered by timestamp in ascending order.", "type": "integer", "format": "int32", "location": "query" }, "parent": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "location": "path", "description": "Required. The resource name of the session to list events from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`" } }, "id": "aiplatform.projects.locations.reasoningEngines.sessions.events.list", "description": "Lists Events in a given session.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/events", "response": { "$ref": "GoogleCloudAiplatformV1ListEventsResponse" }, "httpMethod": "GET" } } }, "operations": { "methods": { "wait": { "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:wait", "id": "aiplatform.projects.locations.reasoningEngines.sessions.operations.wait", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "type": "string", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } } }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted.", "required": true, "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "path": "v1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.sessions.operations.delete" }, "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "location": "path" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}:cancel", "id": "aiplatform.projects.locations.reasoningEngines.sessions.operations.cancel", "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}:cancel" }, "get": { "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "required": true } }, "httpMethod": "GET", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "id": "aiplatform.projects.locations.reasoningEngines.sessions.operations.get", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}" }, "list": { "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.sessions.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "name": { "required": true, "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "type": "string", "location": "path" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "pageSize": { "description": "The standard list page size.", "type": "integer", "location": "query", "format": "int32" } } } } } }, "methods": { "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1Session" }, "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "description": "Required. The resource name of the session. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "location": "path", "type": "string" } }, "id": "aiplatform.projects.locations.reasoningEngines.sessions.get", "path": "v1/{+name}", "description": "Gets details of the specific Session.", "httpMethod": "GET" }, "compact": { "path": "v1/{+name}:compact", "id": "aiplatform.projects.locations.reasoningEngines.sessions.compact", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Compacts the event history of a given Session, which may run an LLM summarization call and rewrite the full event history. Compaction is a storage-side rewrite that can apply a stackable pipeline of rules (event-horizon preservation, tool-response truncation, thought stripping, and LLM summarization etc.)", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}:compact", "parameters": { "name": { "location": "path", "description": "Required. The resource name of the session to compact. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "type": "string", "required": true } }, "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1CompactSessionRequest" } }, "list": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions", "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` * `update_time` Example: `create_time desc`.", "type": "string", "location": "query" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the location to list sessions from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "location": "path" }, "filter": { "description": "Optional. The standard list filter. Supported fields: * `display_name` * `user_id` * `labels` Example: `display_name=\"abc\"`, `user_id=\"123\"`, `labels.key=\"value\"`.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "format": "int32", "description": "Optional. The maximum number of sessions to return. The service may return fewer than this value. If unspecified, the default page size is 100. Values greater than 100 will be capped at 100.", "location": "query" }, "pageToken": { "type": "string", "description": "Optional. The next_page_token value returned from a previous list SessionService.ListSessions call.", "location": "query" } }, "response": { "$ref": "GoogleCloudAiplatformV1ListSessionsResponse" }, "description": "Lists Sessions in a given reasoning engine.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/sessions", "id": "aiplatform.projects.locations.reasoningEngines.sessions.list", "parameterOrder": [ "parent" ], "httpMethod": "GET" }, "patch": { "description": "Updates the specific Session.", "parameters": { "updateMask": { "location": "query", "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", "format": "google-fieldmask" }, "name": { "description": "Identifier. The resource name of the session. Format: 'projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}'.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "location": "path", "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1Session" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1Session" }, "httpMethod": "PATCH", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}", "path": "v1/{+name}", "id": "aiplatform.projects.locations.reasoningEngines.sessions.patch" }, "create": { "path": "v1/{+parent}/sessions", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "description": "Creates a new Session.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions", "parameters": { "sessionId": { "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", "type": "string" }, "parent": { "description": "Required. The resource name of the location to create the session in. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "required": true, "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.reasoningEngines.sessions.create", "request": { "$ref": "GoogleCloudAiplatformV1Session" } }, "delete": { "id": "aiplatform.projects.locations.reasoningEngines.sessions.delete", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "Required. The resource name of the session. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "type": "string", "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$" } }, "httpMethod": "DELETE", "description": "Deletes details of the specific Session.", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] }, "appendEvent": { "id": "aiplatform.projects.locations.reasoningEngines.sessions.appendEvent", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:appendEvent", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}:appendEvent", "response": { "$ref": "GoogleCloudAiplatformV1AppendEventResponse" }, "description": "Appends an event to a given session.", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1SessionEvent" }, "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sessions/[^/]+$", "required": true, "description": "Required. The resource name of the session to append event to. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}`", "type": "string" } } } } }, "runtimeRevisions": { "methods": { "query": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:query", "description": "Queries using a reasoning engine.", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.query", "response": { "$ref": "GoogleCloudAiplatformV1QueryReasoningEngineResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}:query", "request": { "$ref": "GoogleCloudAiplatformV1QueryReasoningEngineRequest" }, "parameters": { "name": { "required": true, "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$" } } }, "streamQuery": { "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1StreamQueryReasoningEngineRequest" }, "parameterOrder": [ "name" ], "description": "Streams queries using a reasoning engine.", "response": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}:streamQuery", "id": "aiplatform.projects.locations.reasoningEngines.runtimeRevisions.streamQuery", "parameters": { "name": { "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:streamQuery" } } }, "sandboxEnvironmentTemplates": { "methods": { "get": { "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplate" }, "description": "Gets details of the specific SandboxEnvironmentTemplate.", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.get", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "description": "Required. The resource name of the sandbox environment template. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentTemplates/{sandbox_environment_template}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+$", "required": true } } }, "create": { "description": "Creates a SandboxEnvironmentTemplate in a given reasoning engine.", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.create", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates", "path": "v1/{+parent}/sandboxEnvironmentTemplates", "request": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplate" }, "parameters": { "parent": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the reasoning engine to create the SandboxEnvironmentTemplate in. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`." } }, "parameterOrder": [ "parent" ] }, "delete": { "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes the specific SandboxEnvironmentTemplate.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.delete", "path": "v1/{+name}", "parameterOrder": [ "name" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+$", "description": "Required. The resource name of the SandboxEnvironmentTemplate to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentTemplates/{sandbox_environment_template}`", "location": "path", "required": true, "type": "string" } } }, "list": { "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.list", "parameterOrder": [ "parent" ], "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists SandboxEnvironmentTemplates in a given reasoning engine.", "parameters": { "pageToken": { "description": "Optional. The standard list page token, received from a previous `ListSandboxEnvironmentTemplates` call. Provide this to retrieve the subsequent page.", "type": "string", "location": "query" }, "filter": { "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "type": "string", "location": "query" }, "parent": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "description": "Required. The resource name of the reasoning engine to list sandbox environment templates from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "pageSize": { "description": "Optional. The maximum number of SandboxEnvironmentTemplates to return. The service may return fewer than this value. If unspecified, at most 100 SandboxEnvironmentTemplates will be returned.", "format": "int32", "type": "integer", "location": "query" } }, "path": "v1/{+parent}/sandboxEnvironmentTemplates", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates", "response": { "$ref": "GoogleCloudAiplatformV1ListSandboxEnvironmentTemplatesResponse" } } }, "resources": { "operations": { "methods": { "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "location": "path" } }, "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.operations.delete", "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`.", "path": "v1/{+name}" }, "get": { "httpMethod": "GET", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/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": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.operations.get", "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.operations.cancel", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "type": "string", "required": true } } }, "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "type": "string", "format": "google-duration" } }, "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentTemplates.operations.wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}:wait", "httpMethod": "POST", "parameterOrder": [ "name" ], "path": "v1/{+name}:wait" } } } } }, "memories": { "resources": { "revisions": { "methods": { "get": { "description": "Get a Memory Revision.", "parameterOrder": [ "name" ], "httpMethod": "GET", "response": { "$ref": "GoogleCloudAiplatformV1MemoryRevision" }, "parameters": { "name": { "description": "Required. The resource name of the Memory Revision to retrieve. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}/revisions/{revision}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+/revisions/[^/]+$", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/revisions/{revisionsId}", "id": "aiplatform.projects.locations.reasoningEngines.memories.revisions.get", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}" }, "list": { "id": "aiplatform.projects.locations.reasoningEngines.memories.revisions.list", "response": { "$ref": "GoogleCloudAiplatformV1ListMemoryRevisionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "description": "Required. The resource name of the Memory to list revisions for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "type": "string", "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token." }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The standard list page size." }, "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`" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/revisions", "parameterOrder": [ "parent" ], "path": "v1/{+parent}/revisions", "httpMethod": "GET", "description": "List Memory Revisions for a Memory." } } }, "operations": { "methods": { "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "format": "int32", "type": "integer", "description": "The standard list page size.", "location": "query" }, "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" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "description": "The name of the operation's parent resource.", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$", "required": true }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations", "id": "aiplatform.projects.locations.reasoningEngines.memories.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations", "parameterOrder": [ "name" ], "httpMethod": "GET" }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.memories.operations.get", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "type": "string", "location": "path" } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.memories.operations.delete", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "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`.", "path": "v1/{+name}" }, "wait": { "id": "aiplatform.projects.locations.reasoningEngines.memories.operations.wait", "httpMethod": "POST", "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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "path": "v1/{+name}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "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", "format": "google-duration" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}:wait" }, "cancel": { "id": "aiplatform.projects.locations.reasoningEngines.memories.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "httpMethod": "POST", "path": "v1/{+name}: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`.", "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" } } } } }, "methods": { "retrieve": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories:retrieve", "response": { "$ref": "GoogleCloudAiplatformV1RetrieveMemoriesResponse" }, "request": { "$ref": "GoogleCloudAiplatformV1RetrieveMemoriesRequest" }, "description": "Retrieve memories.", "parameterOrder": [ "parent" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.memories.retrieve", "path": "v1/{+parent}/memories:retrieve", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the ReasoningEngine to retrieve memories from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "generate": { "id": "aiplatform.projects.locations.reasoningEngines.memories.generate", "path": "v1/{+parent}/memories:generate", "parameters": { "parent": { "type": "string", "location": "path", "description": "Required. The resource name of the ReasoningEngine to generate memories for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories:generate", "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "request": { "$ref": "GoogleCloudAiplatformV1GenerateMemoriesRequest" }, "description": "Generate memories.", "httpMethod": "POST" }, "rollback": { "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}:rollback", "httpMethod": "POST", "parameters": { "name": { "location": "path", "type": "string", "required": true, "description": "Required. The resource name of the Memory to rollback. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:rollback", "request": { "$ref": "GoogleCloudAiplatformV1RollbackMemoryRequest" }, "description": "Rollback Memory to a specific revision.", "id": "aiplatform.projects.locations.reasoningEngines.memories.rollback" }, "patch": { "description": "Update a Memory.", "request": { "$ref": "GoogleCloudAiplatformV1Memory" }, "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "PATCH", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}", "path": "v1/{+name}", "id": "aiplatform.projects.locations.reasoningEngines.memories.patch", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "required": true, "description": "Identifier. Represents the resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$", "location": "path" }, "updateMask": { "description": "Optional. Mask specifying which fields to update. The following fields are immutable: * `scope` * `memory_type`", "format": "google-fieldmask", "location": "query", "type": "string" } } }, "purge": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories:purge", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+parent}/memories:purge", "httpMethod": "POST", "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.reasoningEngines.memories.purge", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Purge memories.", "parameters": { "parent": { "required": true, "description": "Required. The resource name of the ReasoningEngine to purge memories from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "type": "string", "location": "path" } }, "request": { "$ref": "GoogleCloudAiplatformV1PurgeMemoriesRequest" } }, "list": { "response": { "$ref": "GoogleCloudAiplatformV1ListMemoriesResponse" }, "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories", "path": "v1/{+parent}/memories", "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.reasoningEngines.memories.list", "description": "List Memories.", "parameters": { "pageSize": { "format": "int32", "type": "integer", "location": "query", "description": "Optional. The standard list page size." }, "parent": { "description": "Required. The resource name of the ReasoningEngine to list the Memories under. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "location": "path", "type": "string", "required": true }, "pageToken": { "location": "query", "type": "string", "description": "Optional. The standard list page token." }, "filter": { "location": "query", "type": "string", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). Supported fields: * `scope` (as a JSON string with equality match only) * `topics` (i.e. `topics.custom_memory_topic_label: \"example topic\" OR topics.managed_memory_topic: USER_PREFERENCES`)" }, "orderBy": { "description": "Optional. The standard list order by string. If not specified, the default order is `create_time desc`. If specified, the default sorting order of provided fields is ascending. More detail in [AIP-132](https://google.aip.dev/132). Supported fields: * `create_time` * `update_time`", "location": "query", "type": "string" } } }, "ingestEvents": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Ingests events for a Memory Bank.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories:ingestEvents", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1IngestEventsRequest" }, "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "type": "string", "description": "Required. The resource name of the ReasoningEngine to ingest events to. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "required": true } }, "path": "v1/{+parent}/memories:ingestEvents", "id": "aiplatform.projects.locations.reasoningEngines.memories.ingestEvents" }, "get": { "id": "aiplatform.projects.locations.reasoningEngines.memories.get", "description": "Get a Memory.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$", "description": "Required. The resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "type": "string", "required": true, "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}", "response": { "$ref": "GoogleCloudAiplatformV1Memory" }, "httpMethod": "GET" }, "create": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/memories", "request": { "$ref": "GoogleCloudAiplatformV1Memory" }, "description": "Create a Memory.", "id": "aiplatform.projects.locations.reasoningEngines.memories.create", "parameterOrder": [ "parent" ], "parameters": { "parent": { "required": true, "description": "Required. The resource name of the ReasoningEngine to create the Memory under. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "type": "string" }, "memoryId": { "type": "string", "location": "query", "description": "Optional. The user defined ID to use for memory, which will become the final component of the memory resource name. If not provided, Vertex AI will generate a value for this ID. This value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The first character must be a letter, and the last character must be a letter or number." } } }, "delete": { "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.memories.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Delete a Memory.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/memories/[^/]+$", "description": "Required. The resource name of the Memory to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "location": "path", "type": "string" } }, "path": "v1/{+name}" } } }, "operations": { "methods": { "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+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.", "id": "aiplatform.projects.locations.reasoningEngines.operations.get", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}", "id": "aiplatform.projects.locations.reasoningEngines.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`.", "httpMethod": "DELETE", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "id": "aiplatform.projects.locations.reasoningEngines.operations.list", "parameterOrder": [ "name" ], "path": "v1/{+name}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "name": { "required": true, "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "location": "path", "type": "string" }, "returnPartialSuccess": { "location": "query", "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." }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "filter": { "description": "The standard list filter.", "type": "string", "location": "query" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations" }, "cancel": { "path": "v1/{+name}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "id": "aiplatform.projects.locations.reasoningEngines.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}:cancel", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "POST", "parameterOrder": [ "name" ] }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/operations/[^/]+$", "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.", "format": "google-duration", "location": "query", "type": "string" } }, "id": "aiplatform.projects.locations.reasoningEngines.operations.wait", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "path": "v1/{+name}:wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}:wait" } } }, "sandboxEnvironmentSnapshots": { "resources": { "operations": { "methods": { "delete": { "httpMethod": "DELETE", "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.operations.delete", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "path": "v1/{+name}" }, "wait": { "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "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" } }, "path": "v1/{+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.", "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.operations.wait" }, "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}", "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.operations.get", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "type": "string", "location": "path", "required": true, "description": "The name of the operation resource." } }, "path": "v1/{+name}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.operations.cancel", "httpMethod": "POST", "path": "v1/{+name}:cancel", "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." } } } }, "methods": { "list": { "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the reasoning engine to list sandbox environments from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$" }, "pageSize": { "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.", "type": "integer" }, "filter": { "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "type": "string", "location": "query" }, "pageToken": { "description": "Optional. The standard list page token, received from a previous `ListSandboxEnvironmentSnapshots` call. Provide this to retrieve the subsequent page.", "location": "query", "type": "string" } }, "parameterOrder": [ "parent" ], "path": "v1/{+parent}/sandboxEnvironmentSnapshots", "description": "Lists SandboxEnvironmentSnapshots in a given reasoning engine.", "httpMethod": "GET", "response": { "$ref": "GoogleCloudAiplatformV1ListSandboxEnvironmentSnapshotsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.list", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots" }, "get": { "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+$", "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": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentSnapshot" }, "path": "v1/{+name}", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.get", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}", "httpMethod": "GET" }, "delete": { "description": "Deletes the specific SandboxEnvironmentSnapshot.", "parameters": { "name": { "description": "Required. The resource name of the SandboxEnvironmentSnapshot to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentSnapshots/{sandbox_environment_snapshot}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+$", "required": true } }, "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironmentSnapshots.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "path": "v1/{+name}", "httpMethod": "DELETE", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}" } } }, "sandboxEnvironments": { "methods": { "list": { "parameters": { "filter": { "location": "query", "type": "string", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160)." }, "pageToken": { "type": "string", "description": "Optional. The standard list page token, received from a previous `ListSandboxEnvironments` call. Provide this to retrieve the subsequent page.", "location": "query" }, "pageSize": { "format": "int32", "location": "query", "type": "integer", "description": "Optional. The maximum number of SandboxEnvironments to return. The service may return fewer than this value. If unspecified, at most 100 SandboxEnvironments will be returned." }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "location": "path", "description": "Required. The resource name of the reasoning engine to list sandbox environments from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "required": true, "type": "string" } }, "path": "v1/{+parent}/sandboxEnvironments", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.list", "response": { "$ref": "GoogleCloudAiplatformV1ListSandboxEnvironmentsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists SandboxEnvironments in a given reasoning engine.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments", "parameterOrder": [ "parent" ], "httpMethod": "GET" }, "snapshot": { "request": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentSnapshot" }, "parameters": { "name": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true, "description": "Required. The resource name of the sandbox environment to snapshot. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`." } }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:snapshot", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.snapshot", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:snapshot", "description": "Snapshots the specific SandboxEnvironment resource and creates a SandboxEnvironmentSnapshot resource.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] }, "create": { "description": "Creates a SandboxEnvironment in a given reasoning engine.", "httpMethod": "POST", "parameterOrder": [ "parent" ], "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "type": "string", "description": "Required. The resource name of the reasoning engine to create the SandboxEnvironment in. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`.", "required": true, "location": "path" } }, "request": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironment" }, "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.create", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments", "path": "v1/{+parent}/sandboxEnvironments" }, "delete": { "description": "Deletes the specific SandboxEnvironment.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "location": "path", "description": "Required. The resource name of the SandboxEnvironment to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.delete", "path": "v1/{+name}", "httpMethod": "DELETE" }, "get": { "parameters": { "name": { "required": true, "type": "string", "description": "Required. The resource name of the sandbox environment. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}", "response": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironment" }, "parameterOrder": [ "name" ], "description": "Gets details of the specific SandboxEnvironment.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.get" }, "execute": { "description": "Executes using a sandbox environment.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:execute", "httpMethod": "POST", "response": { "$ref": "GoogleCloudAiplatformV1ExecuteSandboxEnvironmentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1ExecuteSandboxEnvironmentRequest" }, "path": "v1/{+name}:execute", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.execute", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "description": "Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "required": true } } }, "authorizeAccess": { "path": "v1/{+name}:authorizeAccess", "description": "Checks whether the caller is authorized to access the sandbox environment. Authorization is performed entirely by the API infrastructure from the `method_policy` below; the handler is a no-op. A successful response means the caller holds `sandboxEnvironments.execute` on the named sandbox. Used by the sandbox data-plane proxy, which forwards the caller's credential and proxies traffic only on success.", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.authorizeAccess", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:authorizeAccess", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1AuthorizeSandboxEnvironmentAccessResponse" }, "request": { "$ref": "GoogleCloudAiplatformV1AuthorizeSandboxEnvironmentAccessRequest" }, "parameters": { "name": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true, "description": "Required. The resource name of the sandbox environment to authorize access to. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`" } } }, "pause": { "request": { "$ref": "GoogleCloudAiplatformV1PauseSandboxEnvironmentRequest" }, "path": "v1/{+name}:pause", "parameters": { "name": { "location": "path", "description": "Required. The resource name of the sandbox environment to pause. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "type": "string" } }, "httpMethod": "POST", "description": "Pauses the specific SandboxEnvironment.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:pause", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.pause" }, "resume": { "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "location": "path", "type": "string", "description": "Required. The resource name of the sandbox environment to resume. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:resume", "path": "v1/{+name}:resume", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Resumes the specific SandboxEnvironment.", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.resume", "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1ResumeSandboxEnvironmentRequest" } } }, "resources": { "operations": { "methods": { "delete": { "path": "v1/{+name}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.operations.delete" }, "cancel": { "parameterOrder": [ "name" ], "path": "v1/{+name}:cancel", "parameters": { "name": { "required": true, "description": "The name of the operation resource to be cancelled.", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$" } }, "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.operations.cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "httpMethod": "POST" }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}:wait", "parameterOrder": [ "name" ], "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "location": "path" }, "timeout": { "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "format": "google-duration" } }, "path": "v1/{+name}:wait", "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.operations.wait" }, "get": { "parameterOrder": [ "name" ], "httpMethod": "GET", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.reasoningEngines.sandboxEnvironments.operations.get", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}" } } } } } }, "methods": { "streamQuery": { "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "location": "path", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.reasoningEngines.streamQuery", "path": "v1/{+name}:streamQuery", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:streamQuery", "request": { "$ref": "GoogleCloudAiplatformV1StreamQueryReasoningEngineRequest" }, "response": { "$ref": "GoogleApiHttpBody" }, "httpMethod": "POST", "description": "Streams queries using a reasoning engine." }, "create": { "request": { "$ref": "GoogleCloudAiplatformV1ReasoningEngine" }, "httpMethod": "POST", "path": "v1/{+parent}/reasoningEngines", "id": "aiplatform.projects.locations.reasoningEngines.create", "description": "Creates a reasoning engine.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines", "parameters": { "parent": { "required": true, "description": "Required. The resource name of the Location to create the ReasoningEngine in. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "type": "string" } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}", "parameters": { "name": { "description": "Required. The name of the ReasoningEngine resource to be deleted. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$" }, "force": { "type": "boolean", "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" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.reasoningEngines.delete", "path": "v1/{+name}", "description": "Deletes a reasoning engine." }, "list": { "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "type": "string", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "location": "query" }, "pageToken": { "description": "Optional. The standard list page token.", "type": "string", "location": "query" }, "pageSize": { "type": "integer", "format": "int32", "description": "Optional. The standard list page size.", "location": "query" }, "parent": { "type": "string", "location": "path", "description": "Required. The resource name of the Location to list the ReasoningEngines from. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "description": "Lists reasoning engines in a location.", "response": { "$ref": "GoogleCloudAiplatformV1ListReasoningEnginesResponse" }, "id": "aiplatform.projects.locations.reasoningEngines.list", "path": "v1/{+parent}/reasoningEngines", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines", "httpMethod": "GET" }, "query": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Queries using a reasoning engine.", "parameters": { "name": { "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true } }, "id": "aiplatform.projects.locations.reasoningEngines.query", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:query", "response": { "$ref": "GoogleCloudAiplatformV1QueryReasoningEngineResponse" }, "path": "v1/{+name}:query", "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1QueryReasoningEngineRequest" }, "httpMethod": "POST" }, "setIamPolicy": { "response": { "$ref": "GoogleIamV1Policy" }, "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:setIamPolicy", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "path": "v1/{+resource}:setIamPolicy", "parameterOrder": [ "resource" ], "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.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true } }, "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "id": "aiplatform.projects.locations.reasoningEngines.setIamPolicy" }, "get": { "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}", "id": "aiplatform.projects.locations.reasoningEngines.get", "description": "Gets a reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1ReasoningEngine" }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "parameters": { "name": { "required": true, "type": "string", "description": "Required. The name of the ReasoningEngine resource. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "location": "path" } } }, "cancelAsyncQuery": { "parameters": { "name": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1CancelAsyncQueryReasoningEngineRequest" }, "parameterOrder": [ "name" ], "description": "Cancels an AsyncQueryReasoningEngine operation.", "id": "aiplatform.projects.locations.reasoningEngines.cancelAsyncQuery", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:cancelAsyncQuery", "httpMethod": "POST", "response": { "$ref": "GoogleCloudAiplatformV1CancelAsyncQueryReasoningEngineResponse" }, "path": "v1/{+name}:cancelAsyncQuery" }, "testIamPermissions": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:testIamPermissions", "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": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "resource" ], "parameters": { "resource": { "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "location": "path" }, "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).", "type": "string", "repeated": true } }, "path": "v1/{+resource}:testIamPermissions", "id": "aiplatform.projects.locations.reasoningEngines.testIamPermissions" }, "asyncQuery": { "id": "aiplatform.projects.locations.reasoningEngines.asyncQuery", "request": { "$ref": "GoogleCloudAiplatformV1AsyncQueryReasoningEngineRequest" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "httpMethod": "POST", "path": "v1/{+name}:asyncQuery", "description": "Async query using a reasoning engine.", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "location": "path", "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:asyncQuery", "response": { "$ref": "GoogleLongrunningOperation" } }, "getIamPolicy": { "path": "v1/{+resource}:getIamPolicy", "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "parameters": { "options.requestedPolicyVersion": { "type": "integer", "format": "int32", "location": "query", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies)." }, "resource": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "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" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:getIamPolicy", "response": { "$ref": "GoogleIamV1Policy" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "resource" ], "id": "aiplatform.projects.locations.reasoningEngines.getIamPolicy", "httpMethod": "POST" }, "patch": { "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Updates a reasoning engine.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}", "id": "aiplatform.projects.locations.reasoningEngines.patch", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "required": true, "location": "path", "type": "string", "description": "Identifier. The resource name of the ReasoningEngine. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "updateMask": { "type": "string", "description": "Optional. Mask specifying which fields to update.", "format": "google-fieldmask", "location": "query" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "httpMethod": "PATCH", "path": "v1/{+name}", "request": { "$ref": "GoogleCloudAiplatformV1ReasoningEngine" } }, "executeCode": { "request": { "$ref": "GoogleCloudAiplatformV1ExecuteCodeRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1ExecuteCodeResponse" }, "path": "v1/{+name}:executeCode", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/reasoningEngines/{reasoningEnginesId}:executeCode", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/reasoningEngines/[^/]+$", "location": "path", "description": "Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "description": "Executes code statelessly.", "httpMethod": "POST", "id": "aiplatform.projects.locations.reasoningEngines.executeCode", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "cachedContents": { "methods": { "create": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/cachedContents", "response": { "$ref": "GoogleCloudAiplatformV1CachedContent" }, "path": "v1/{+parent}/cachedContents", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1CachedContent" }, "httpMethod": "POST", "description": "Creates cached content, this call will initialize the cached content in the data storage, and users need to pay for the cache data storage.", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "required": true, "description": "Required. The parent resource where the cached content will be created", "location": "path" } }, "id": "aiplatform.projects.locations.cachedContents.create" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/cachedContents/[^/]+$", "description": "Required. The resource name referring to the cached content" } }, "description": "Deletes cached content", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.cachedContents.delete", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/cachedContents/{cachedContentsId}", "path": "v1/{+name}" }, "list": { "parameterOrder": [ "parent" ], "httpMethod": "GET", "path": "v1/{+parent}/cachedContents", "id": "aiplatform.projects.locations.cachedContents.list", "parameters": { "parent": { "required": true, "type": "string", "description": "Required. The parent, which owns this collection of cached contents.", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path" }, "pageToken": { "description": "Optional. A page token, received from a previous `ListCachedContents` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `ListCachedContents` must match the call that provided the page token.", "type": "string", "location": "query" }, "pageSize": { "location": "query", "description": "Optional. The maximum number of cached contents to return. The service may return fewer than this value. If unspecified, some default (under maximum) number of items will be returned. The maximum value is 1000; values above 1000 will be coerced to 1000.", "format": "int32", "type": "integer" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/cachedContents", "description": "Lists cached contents in a project", "response": { "$ref": "GoogleCloudAiplatformV1ListCachedContentsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "type": "string", "description": "Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}", "pattern": "^projects/[^/]+/locations/[^/]+/cachedContents/[^/]+$", "location": "path" }, "updateMask": { "type": "string", "description": "Required. The list of fields to update.", "format": "google-fieldmask", "location": "query" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleCloudAiplatformV1CachedContent" }, "httpMethod": "PATCH", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/cachedContents/{cachedContentsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1CachedContent" }, "description": "Updates cached content configurations", "id": "aiplatform.projects.locations.cachedContents.patch" }, "get": { "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/cachedContents/[^/]+$", "required": true, "description": "Required. The resource name referring to the cached content" } }, "description": "Gets cached content configurations", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/cachedContents/{cachedContentsId}", "response": { "$ref": "GoogleCloudAiplatformV1CachedContent" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.cachedContents.get", "parameterOrder": [ "name" ], "path": "v1/{+name}", "httpMethod": "GET" } } }, "memoryBanks": { "methods": { "ingestEvents": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}:ingestEvents", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Ingests events for a Memory Bank.", "id": "aiplatform.projects.locations.memoryBanks.ingestEvents", "path": "v1/{+parent}:ingestEvents", "request": { "$ref": "GoogleCloudAiplatformV1IngestEventsRequest" }, "parameterOrder": [ "parent" ], "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+$", "required": true, "location": "path", "type": "string", "description": "Required. The resource name of the ReasoningEngine to ingest events to. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } } } }, "resources": { "operations": { "methods": { "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/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" }, "id": "aiplatform.projects.locations.memoryBanks.operations.get", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/operations/{operationsId}", "httpMethod": "GET" }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.memoryBanks.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } }, "path": "v1/{+name}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "httpMethod": "POST", "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`." }, "wait": { "httpMethod": "POST", "id": "aiplatform.projects.locations.memoryBanks.operations.wait", "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/operations/[^/]+$" }, "timeout": { "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "type": "string" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/operations/{operationsId}:wait", "path": "v1/{+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.", "parameterOrder": [ "name" ] }, "delete": { "parameters": { "name": { "type": "string", "description": "The name of the operation resource to be deleted.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/operations/[^/]+$", "location": "path" } }, "path": "v1/{+name}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.memoryBanks.operations.delete", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/operations/{operationsId}" }, "list": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/operations", "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations", "id": "aiplatform.projects.locations.memoryBanks.operations.list", "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path", "type": "string" }, "pageSize": { "location": "query", "type": "integer", "format": "int32", "description": "The standard list page size." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "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" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] } } }, "memories": { "methods": { "create": { "httpMethod": "POST", "parameterOrder": [ "parent" ], "path": "v1/{+parent}/memories", "description": "Create a Memory.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1Memory" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories", "id": "aiplatform.projects.locations.memoryBanks.memories.create", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+$", "description": "Required. The resource name of the ReasoningEngine to create the Memory under. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" }, "memoryId": { "type": "string", "location": "query", "description": "Optional. The user defined ID to use for memory, which will become the final component of the memory resource name. If not provided, Vertex AI will generate a value for this ID. This value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The first character must be a letter, and the last character must be a letter or number." } } }, "delete": { "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories/{memoriesId}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "required": true, "description": "Required. The resource name of the Memory to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/memories/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.memoryBanks.memories.delete", "description": "Delete a Memory.", "parameterOrder": [ "name" ], "path": "v1/{+name}" }, "purge": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "description": "Purge memories.", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.memoryBanks.memories.purge", "path": "v1/{+parent}/memories:purge", "parameters": { "parent": { "required": true, "type": "string", "description": "Required. The resource name of the ReasoningEngine to purge memories from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+$", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories:purge", "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1PurgeMemoriesRequest" } }, "retrieve": { "description": "Retrieve memories.", "id": "aiplatform.projects.locations.memoryBanks.memories.retrieve", "httpMethod": "POST", "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1RetrieveMemoriesResponse" }, "path": "v1/{+parent}/memories:retrieve", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories:retrieve", "request": { "$ref": "GoogleCloudAiplatformV1RetrieveMemoriesRequest" }, "parameters": { "parent": { "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the ReasoningEngine to retrieve memories from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+$" } } }, "list": { "response": { "$ref": "GoogleCloudAiplatformV1ListMemoriesResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories", "description": "List Memories.", "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/memories", "parameters": { "pageToken": { "location": "query", "description": "Optional. The standard list page token.", "type": "string" }, "filter": { "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`)", "type": "string" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+$", "required": true, "location": "path", "type": "string", "description": "Required. The resource name of the ReasoningEngine to list the Memories under. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" }, "orderBy": { "description": "Optional. The standard list order by string. If not specified, the default order is `create_time desc`. If specified, the default sorting order of provided fields is ascending. More detail in [AIP-132](https://google.aip.dev/132). Supported fields: * `create_time` * `update_time`", "type": "string", "location": "query" }, "pageSize": { "type": "integer", "format": "int32", "location": "query", "description": "Optional. The standard list page size." } }, "id": "aiplatform.projects.locations.memoryBanks.memories.list", "httpMethod": "GET" }, "generate": { "parameterOrder": [ "parent" ], "path": "v1/{+parent}/memories:generate", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories:generate", "request": { "$ref": "GoogleCloudAiplatformV1GenerateMemoriesRequest" }, "parameters": { "parent": { "type": "string", "location": "path", "required": true, "description": "Required. The resource name of the ReasoningEngine to generate memories for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+$" } }, "id": "aiplatform.projects.locations.memoryBanks.memories.generate", "description": "Generate memories.", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "rollback": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories/{memoriesId}:rollback", "request": { "$ref": "GoogleCloudAiplatformV1RollbackMemoryRequest" }, "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "id": "aiplatform.projects.locations.memoryBanks.memories.rollback", "parameters": { "name": { "required": true, "description": "Required. The resource name of the Memory to rollback. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/memories/[^/]+$", "location": "path", "type": "string" } }, "path": "v1/{+name}:rollback", "description": "Rollback Memory to a specific revision." }, "patch": { "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "Identifier. Represents the resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/memories/[^/]+$", "type": "string", "location": "path" }, "updateMask": { "description": "Optional. Mask specifying which fields to update. The following fields are immutable: * `scope` * `memory_type`", "location": "query", "format": "google-fieldmask", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories/{memoriesId}", "request": { "$ref": "GoogleCloudAiplatformV1Memory" }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.memoryBanks.memories.patch", "description": "Update a Memory.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "httpMethod": "PATCH" }, "get": { "httpMethod": "GET", "description": "Get a Memory.", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.memoryBanks.memories.get", "response": { "$ref": "GoogleCloudAiplatformV1Memory" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories/{memoriesId}", "parameters": { "name": { "description": "Required. The resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "required": true, "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/memories/[^/]+$", "type": "string" } } } }, "resources": { "revisions": { "methods": { "list": { "id": "aiplatform.projects.locations.memoryBanks.memories.revisions.list", "parameters": { "parent": { "type": "string", "location": "path", "required": true, "description": "Required. The resource name of the Memory to list revisions for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/memories/[^/]+$" }, "pageSize": { "format": "int32", "type": "integer", "description": "Optional. The standard list page size.", "location": "query" }, "pageToken": { "description": "Optional. The standard list page token.", "type": "string", "location": "query" }, "filter": { "type": "string", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). Supported fields (equality match only): * `labels`", "location": "query" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "List Memory Revisions for a Memory.", "parameterOrder": [ "parent" ], "path": "v1/{+parent}/revisions", "response": { "$ref": "GoogleCloudAiplatformV1ListMemoryRevisionsResponse" }, "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories/{memoriesId}/revisions" }, "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories/{memoriesId}/revisions/{revisionsId}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1MemoryRevision" }, "parameters": { "name": { "type": "string", "location": "path", "description": "Required. The resource name of the Memory Revision to retrieve. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}/revisions/{revision}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/memories/[^/]+/revisions/[^/]+$" } }, "description": "Get a Memory Revision.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.memoryBanks.memories.revisions.get", "httpMethod": "GET" } } }, "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`.", "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories/{memoriesId}/operations", "path": "v1/{+name}/operations", "parameters": { "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "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", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/memories/[^/]+$", "required": true, "description": "The name of the operation's parent resource." } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.memoryBanks.memories.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "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.", "id": "aiplatform.projects.locations.memoryBanks.memories.operations.wait", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/memories/[^/]+/operations/[^/]+$", "type": "string", "required": true }, "timeout": { "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "format": "google-duration" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories/{memoriesId}/operations/{operationsId}:wait", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:wait" }, "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories/{memoriesId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "id": "aiplatform.projects.locations.memoryBanks.memories.operations.get", "httpMethod": "GET", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/memories/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "type": "string", "required": true } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "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`.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/memories/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be deleted.", "required": true, "location": "path" } }, "path": "v1/{+name}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.memoryBanks.memories.operations.delete", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories/{memoriesId}/operations/{operationsId}", "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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`.", "path": "v1/{+name}:cancel", "id": "aiplatform.projects.locations.memoryBanks.memories.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/memoryBanks/{memoryBanksId}/memories/{memoriesId}/operations/{operationsId}:cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/memoryBanks/[^/]+/memories/[^/]+/operations/[^/]+$", "location": "path" } } } } } } } } }, "ragCorpora": { "resources": { "operations": { "methods": { "wait": { "path": "v1/{+name}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.ragCorpora.operations.wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}:wait", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "type": "string", "format": "google-duration" }, "name": { "location": "path", "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$", "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." }, "get": { "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.ragCorpora.operations.get", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}", "httpMethod": "GET" }, "cancel": { "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string" } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.ragCorpora.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "path": "v1/{+name}:cancel", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}:cancel" }, "list": { "path": "v1/{+name}/operations", "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", "format": "int32", "location": "query", "description": "The standard list page size." }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "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", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "description": "The name of the operation's parent resource.", "type": "string", "required": true } }, "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations", "id": "aiplatform.projects.locations.ragCorpora.operations.list", "parameterOrder": [ "name" ], "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "id": "aiplatform.projects.locations.ragCorpora.operations.delete", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "httpMethod": "DELETE", "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/operations/[^/]+$" } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "ragFiles": { "resources": { "operations": { "methods": { "list": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "httpMethod": "GET", "parameters": { "pageSize": { "location": "query", "description": "The standard list page size.", "format": "int32", "type": "integer" }, "returnPartialSuccess": { "location": "query", "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$", "type": "string", "required": true, "description": "The name of the operation's parent resource." }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." } }, "path": "v1/{+name}/operations" }, "get": { "httpMethod": "GET", "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.", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource." } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.get", "path": "v1/{+name}" }, "delete": { "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "type": "string", "required": true } }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.delete", "path": "v1/{+name}", "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "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.", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.wait", "parameterOrder": [ "name" ], "path": "v1/{+name}:wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}:wait", "parameters": { "name": { "required": true, "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "type": "string", "location": "path" }, "timeout": { "location": "query", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration" } }, "response": { "$ref": "GoogleLongrunningOperation" } }, "cancel": { "id": "aiplatform.projects.locations.ragCorpora.ragFiles.operations.cancel", "httpMethod": "POST", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}/operations/{operationsId}:cancel", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be cancelled." } }, "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}: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`." } } } }, "methods": { "list": { "httpMethod": "GET", "description": "Lists RagFiles in a RagCorpus.", "path": "v1/{+parent}/ragFiles", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1ListRagFilesResponse" }, "id": "aiplatform.projects.locations.ragCorpora.ragFiles.list", "parameterOrder": [ "parent" ], "parameters": { "pageSize": { "location": "query", "type": "integer", "description": "Optional. The standard list page size. The maximum value is 100. If not specified, a default value of 100 will be used.", "format": "int32" }, "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "type": "string", "description": "Required. The resource name of the RagCorpus from which to list the RagFiles. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "location": "path" }, "pageToken": { "location": "query", "description": "Optional. The standard list page token. Typically obtained via ListRagFilesResponse.next_page_token of the previous VertexRagDataService.ListRagFiles call.", "type": "string" } } }, "delete": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.delete", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$", "required": true, "description": "Required. The name of the RagFile resource to be deleted. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}`", "type": "string", "location": "path" }, "forceDelete": { "description": "Optional. If set to true, any errors generated by external vector database during the deletion will be ignored. The default value is false.", "type": "boolean", "location": "query" } }, "parameterOrder": [ "name" ], "description": "Deletes a RagFile.", "path": "v1/{+name}" }, "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "response": { "$ref": "GoogleCloudAiplatformV1RagFile" }, "id": "aiplatform.projects.locations.ragCorpora.ragFiles.get", "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles/{ragFilesId}", "description": "Gets a RagFile.", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "type": "string", "description": "Required. The name of the RagFile resource. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+/ragFiles/[^/]+$" } } }, "import": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Import files from Google Cloud Storage or Google Drive into a RagCorpus.", "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1ImportRagFilesRequest" }, "parameters": { "parent": { "location": "path", "type": "string", "description": "Required. The name of the RagCorpus resource into which to import files. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$" } }, "httpMethod": "POST", "path": "v1/{+parent}/ragFiles:import", "id": "aiplatform.projects.locations.ragCorpora.ragFiles.import", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles:import" } } } }, "methods": { "get": { "response": { "$ref": "GoogleCloudAiplatformV1RagCorpus" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}", "parameterOrder": [ "name" ], "httpMethod": "GET", "parameters": { "name": { "location": "path", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "description": "Required. The name of the RagCorpus resource. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`" } }, "description": "Gets a RagCorpus.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.ragCorpora.get", "path": "v1/{+name}" }, "create": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.ragCorpora.create", "description": "Creates a RagCorpus.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora", "path": "v1/{+parent}/ragCorpora", "parameterOrder": [ "parent" ], "parameters": { "parent": { "location": "path", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location to create the RagCorpus in. Format: `projects/{project}/locations/{location}`" } }, "request": { "$ref": "GoogleCloudAiplatformV1RagCorpus" } }, "delete": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a RagCorpus.", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}", "httpMethod": "DELETE", "parameters": { "force": { "description": "Optional. If set to true, any RagFiles in this RagCorpus will also be deleted. Otherwise, the request will only work if the RagCorpus has no RagFiles.", "location": "query", "type": "boolean" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "location": "path", "required": true, "type": "string", "description": "Required. The name of the RagCorpus resource to be deleted. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`" } }, "id": "aiplatform.projects.locations.ragCorpora.delete" }, "patch": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Output only. The resource name of the RagCorpus.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "type": "string", "required": true } }, "description": "Updates a RagCorpus.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1RagCorpus" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}", "id": "aiplatform.projects.locations.ragCorpora.patch", "path": "v1/{+name}", "httpMethod": "PATCH" }, "list": { "httpMethod": "GET", "id": "aiplatform.projects.locations.ragCorpora.list", "path": "v1/{+parent}/ragCorpora", "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The standard list page size. The maximum value is 100. If not specified, a default value of 100 will be used." }, "pageToken": { "description": "Optional. The standard list page token. Typically obtained via ListRagCorporaResponse.next_page_token of the previous VertexRagDataService.ListRagCorpora call.", "type": "string", "location": "query" }, "parent": { "location": "path", "description": "Required. The resource name of the Location from which to list the RagCorpora. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "required": true } }, "description": "Lists RagCorpora in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1ListRagCorporaResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora" } } }, "hyperparameterTuningJobs": { "resources": { "operations": { "methods": { "wait": { "path": "v1/{+name}:wait", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.hyperparameterTuningJobs.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.", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "required": true, "type": "string" }, "timeout": { "location": "query", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration" } } }, "list": { "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.list", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "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" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "location": "path", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", "description": "The name of the operation's parent resource." }, "pageSize": { "description": "The standard list page size.", "type": "integer", "format": "int32", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations" }, "cancel": { "parameterOrder": [ "name" ], "path": "v1/{+name}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "httpMethod": "POST", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.cancel", "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}:cancel" }, "delete": { "parameterOrder": [ "name" ], "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "description": "The name of the operation resource to be deleted.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.delete" }, "get": { "id": "aiplatform.projects.locations.hyperparameterTuningJobs.operations.get", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource." } }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/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.", "parameterOrder": [ "name" ], "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" } } } } }, "methods": { "create": { "parameters": { "parent": { "type": "string", "required": true, "description": "Required. The resource name of the Location to create the HyperparameterTuningJob in. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path" } }, "description": "Creates a HyperparameterTuningJob", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1HyperparameterTuningJob" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.create", "httpMethod": "POST", "path": "v1/{+parent}/hyperparameterTuningJobs", "request": { "$ref": "GoogleCloudAiplatformV1HyperparameterTuningJob" } }, "delete": { "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}", "httpMethod": "DELETE", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a HyperparameterTuningJob.", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.delete", "parameters": { "name": { "description": "Required. The name of the HyperparameterTuningJob resource to be deleted. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", "type": "string", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}" }, "cancel": { "parameters": { "name": { "type": "string", "location": "path", "description": "Required. The name of the HyperparameterTuningJob to cancel. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}:cancel", "request": { "$ref": "GoogleCloudAiplatformV1CancelHyperparameterTuningJobRequest" }, "description": "Cancels a HyperparameterTuningJob. Starts asynchronous cancellation on the HyperparameterTuningJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetHyperparameterTuningJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the HyperparameterTuningJob is not deleted; instead it becomes a job with a HyperparameterTuningJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and HyperparameterTuningJob.state is set to `CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.hyperparameterTuningJobs.cancel" }, "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs/{hyperparameterTuningJobsId}", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1HyperparameterTuningJob" }, "description": "Gets a HyperparameterTuningJob", "parameterOrder": [ "name" ], "path": "v1/{+name}", "parameters": { "name": { "description": "Required. The name of the HyperparameterTuningJob resource. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}`", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/hyperparameterTuningJobs/[^/]+$", "location": "path" } }, "id": "aiplatform.projects.locations.hyperparameterTuningJobs.get" }, "list": { "response": { "$ref": "GoogleCloudAiplatformV1ListHyperparameterTuningJobsResponse" }, "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/hyperparameterTuningJobs", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "description": "Lists HyperparameterTuningJobs in a Location.", "path": "v1/{+parent}/hyperparameterTuningJobs", "parameters": { "pageSize": { "type": "integer", "location": "query", "description": "The standard list page size.", "format": "int32" }, "readMask": { "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "type": "string", "location": "query" }, "filter": { "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", "location": "query" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token. Typically obtained via ListHyperparameterTuningJobsResponse.next_page_token of the previous JobService.ListHyperparameterTuningJobs call." }, "parent": { "description": "Required. The resource name of the Location to list the HyperparameterTuningJobs from. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "id": "aiplatform.projects.locations.hyperparameterTuningJobs.list" } } }, "metadataStores": { "resources": { "artifacts": { "methods": { "queryArtifactLineageSubgraph": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "artifact" ], "parameters": { "maxHops": { "format": "int32", "location": "query", "description": "Specifies the size of the lineage graph in terms of number of hops from the specified artifact. Negative Value: INVALID_ARGUMENT error is returned 0: Only input artifact is returned. No value: Transitive closure is performed to return the complete graph.", "type": "integer" }, "artifact": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", "type": "string", "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.", "required": true }, "filter": { "location": "query", "type": "string", "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`." } }, "path": "v1/{+artifact}:queryArtifactLineageSubgraph", "id": "aiplatform.projects.locations.metadataStores.artifacts.queryArtifactLineageSubgraph", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}:queryArtifactLineageSubgraph", "description": "Retrieves lineage of an Artifact represented through Artifacts and Executions connected by Event edges and returned as a LineageSubgraph.", "response": { "$ref": "GoogleCloudAiplatformV1LineageSubgraph" }, "httpMethod": "GET" }, "purge": { "description": "Purges Artifacts.", "id": "aiplatform.projects.locations.metadataStores.artifacts.purge", "parameters": { "parent": { "required": true, "description": "Required. The metadata store to purge Artifacts from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "location": "path", "type": "string" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1PurgeArtifactsRequest" }, "path": "v1/{+parent}/artifacts:purge", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts:purge", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST" }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.metadataStores.artifacts.list", "description": "Lists Artifacts in the MetadataStore.", "parameters": { "parent": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "description": "Required. The MetadataStore whose Artifacts should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "required": true }, "filter": { "location": "query", "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`.", "type": "string" }, "pageSize": { "description": "The maximum number of Artifacts to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100.", "format": "int32", "type": "integer", "location": "query" }, "orderBy": { "type": "string", "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." }, "pageToken": { "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", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts", "response": { "$ref": "GoogleCloudAiplatformV1ListArtifactsResponse" }, "path": "v1/{+parent}/artifacts", "httpMethod": "GET" }, "get": { "httpMethod": "GET", "id": "aiplatform.projects.locations.metadataStores.artifacts.get", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", "type": "string", "required": true, "description": "Required. The resource name of the Artifact to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`" } }, "response": { "$ref": "GoogleCloudAiplatformV1Artifact" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Retrieves a specific Artifact." }, "patch": { "request": { "$ref": "GoogleCloudAiplatformV1Artifact" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", "required": true, "location": "path", "description": "Output only. The resource name of the Artifact.", "type": "string" }, "updateMask": { "format": "google-fieldmask", "description": "Optional. A FieldMask indicating which fields should be updated.", "type": "string", "location": "query" }, "allowMissing": { "type": "boolean", "description": "If set to true, and the Artifact is not found, a new Artifact is created.", "location": "query" } }, "path": "v1/{+name}", "description": "Updates a stored Artifact.", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.artifacts.patch", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}", "httpMethod": "PATCH", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1Artifact" } }, "create": { "path": "v1/{+parent}/artifacts", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "description": "Required. The resource name of the MetadataStore where the Artifact should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "type": "string", "required": true }, "artifactId": { "location": "query", "type": "string", "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.)" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts", "id": "aiplatform.projects.locations.metadataStores.artifacts.create", "response": { "$ref": "GoogleCloudAiplatformV1Artifact" }, "description": "Creates an Artifact associated with a MetadataStore.", "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1Artifact" }, "httpMethod": "POST" }, "delete": { "parameterOrder": [ "name" ], "httpMethod": "DELETE", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}", "description": "Deletes an Artifact.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "etag": { "location": "query", "description": "Optional. The etag of the Artifact to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION.", "type": "string" }, "name": { "type": "string", "description": "Required. The resource name of the Artifact to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", "location": "path" } }, "id": "aiplatform.projects.locations.metadataStores.artifacts.delete" } }, "resources": { "operations": { "methods": { "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "type": "string", "location": "path", "required": true, "description": "The name of the operation resource." } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.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.", "httpMethod": "GET", "path": "v1/{+name}" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "required": true, "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "location": "path" }, "timeout": { "format": "google-duration", "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" } } }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted.", "required": true } }, "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "httpMethod": "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`.", "parameterOrder": [ "name" ] }, "list": { "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "path": "v1/{+name}/operations", "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.list", "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+$", "type": "string" }, "pageSize": { "location": "query", "type": "integer", "description": "The standard list page size.", "format": "int32" }, "filter": { "description": "The standard list filter.", "type": "string", "location": "query" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations" }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "path": "v1/{+name}:cancel", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:cancel", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.artifacts.operations.cancel" } } } } }, "executions": { "methods": { "purge": { "request": { "$ref": "GoogleCloudAiplatformV1PurgeExecutionsRequest" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/executions:purge", "httpMethod": "POST", "description": "Purges Executions.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions:purge", "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.metadataStores.executions.purge", "parameters": { "parent": { "location": "path", "description": "Required. The metadata store to purge Executions from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$" } }, "response": { "$ref": "GoogleLongrunningOperation" } }, "queryExecutionInputsAndOutputs": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}:queryExecutionInputsAndOutputs", "description": "Obtains the set of input and output Artifacts for this Execution, in the form of LineageSubgraph that also contains the Execution and connecting Events.", "response": { "$ref": "GoogleCloudAiplatformV1LineageSubgraph" }, "parameterOrder": [ "execution" ], "parameters": { "execution": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", "type": "string", "location": "path", "description": "Required. The resource name of the Execution whose input and output Artifacts should be retrieved as a LineageSubgraph. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`" } }, "httpMethod": "GET", "path": "v1/{+execution}:queryExecutionInputsAndOutputs", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.metadataStores.executions.queryExecutionInputsAndOutputs" }, "create": { "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "description": "Required. The resource name of the MetadataStore where the Execution should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "type": "string" }, "executionId": { "type": "string", "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" } }, "description": "Creates an Execution associated with a MetadataStore.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions", "path": "v1/{+parent}/executions", "id": "aiplatform.projects.locations.metadataStores.executions.create", "response": { "$ref": "GoogleCloudAiplatformV1Execution" }, "request": { "$ref": "GoogleCloudAiplatformV1Execution" }, "httpMethod": "POST", "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "httpMethod": "DELETE", "parameterOrder": [ "name" ], "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes an Execution.", "id": "aiplatform.projects.locations.metadataStores.executions.delete", "parameters": { "name": { "location": "path", "description": "Required. The resource name of the Execution to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", "type": "string" }, "etag": { "type": "string", "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.", "location": "query" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.metadataStores.executions.patch", "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", "location": "path", "description": "Output only. The resource name of the Execution." }, "allowMissing": { "type": "boolean", "location": "query", "description": "If set to true, and the Execution is not found, a new Execution is created." }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Optional. A FieldMask indicating which fields should be updated.", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1/{+name}", "httpMethod": "PATCH", "response": { "$ref": "GoogleCloudAiplatformV1Execution" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", "description": "Updates a stored Execution.", "request": { "$ref": "GoogleCloudAiplatformV1Execution" } }, "get": { "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "path": "v1/{+name}", "description": "Retrieves a specific Execution.", "response": { "$ref": "GoogleCloudAiplatformV1Execution" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}", "id": "aiplatform.projects.locations.metadataStores.executions.get", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Execution to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`" } } }, "list": { "parameters": { "parent": { "location": "path", "description": "Required. The MetadataStore whose Executions should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "type": "string" }, "pageSize": { "format": "int32", "location": "query", "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." }, "orderBy": { "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", "type": "string" }, "filter": { "location": "query", "type": "string", "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`." }, "pageToken": { "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.)", "location": "query", "type": "string" } }, "response": { "$ref": "GoogleCloudAiplatformV1ListExecutionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions", "path": "v1/{+parent}/executions", "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.metadataStores.executions.list", "httpMethod": "GET", "description": "Lists Executions in the MetadataStore." }, "addExecutionEvents": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+execution}:addExecutionEvents", "parameters": { "execution": { "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$", "description": "Required. The resource name of the Execution that the Events connect Artifacts with. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}:addExecutionEvents", "parameterOrder": [ "execution" ], "request": { "$ref": "GoogleCloudAiplatformV1AddExecutionEventsRequest" }, "id": "aiplatform.projects.locations.metadataStores.executions.addExecutionEvents", "response": { "$ref": "GoogleCloudAiplatformV1AddExecutionEventsResponse" }, "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.", "httpMethod": "POST" } }, "resources": { "operations": { "methods": { "cancel": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "type": "string", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.executions.operations.cancel", "path": "v1/{+name}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:cancel", "httpMethod": "POST" }, "wait": { "parameterOrder": [ "name" ], "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.metadataStores.executions.operations.wait", "path": "v1/{+name}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "type": "string", "format": "google-duration" }, "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to wait on.", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.metadataStores.executions.operations.delete", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}" }, "get": { "id": "aiplatform.projects.locations.metadataStores.executions.operations.get", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "type": "string", "required": true } }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}", "path": "v1/{+name}" }, "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/executions/{executionsId}/operations", "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "type": "integer", "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": { "required": true, "description": "The name of the operation's parent resource.", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/executions/[^/]+$" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" } }, "id": "aiplatform.projects.locations.metadataStores.executions.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations" } } } } }, "operations": { "methods": { "list": { "path": "v1/{+name}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations", "parameters": { "pageSize": { "format": "int32", "location": "query", "type": "integer", "description": "The standard list page size." }, "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "description": "The name of the operation's parent resource.", "required": true, "type": "string" }, "returnPartialSuccess": { "location": "query", "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." }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "httpMethod": "GET", "id": "aiplatform.projects.locations.metadataStores.operations.list", "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.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to wait on.", "location": "path", "required": true }, "timeout": { "location": "query", "format": "google-duration", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.metadataStores.operations.wait", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" } }, "cancel": { "httpMethod": "POST", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "id": "aiplatform.projects.locations.metadataStores.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", "location": "path" } } }, "get": { "id": "aiplatform.projects.locations.metadataStores.operations.get", "parameterOrder": [ "name" ], "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "location": "path", "type": "string" } } }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/operations/[^/]+$", "type": "string", "location": "path" } }, "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/operations/{operationsId}", "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`.", "path": "v1/{+name}", "id": "aiplatform.projects.locations.metadataStores.operations.delete", "httpMethod": "DELETE" } } }, "metadataSchemas": { "methods": { "create": { "request": { "$ref": "GoogleCloudAiplatformV1MetadataSchema" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas", "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.create", "description": "Creates a MetadataSchema.", "response": { "$ref": "GoogleCloudAiplatformV1MetadataSchema" }, "parameterOrder": [ "parent" ], "parameters": { "metadataSchemaId": { "location": "query", "type": "string", "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.)" }, "parent": { "type": "string", "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/[^/]+$", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/metadataSchemas" }, "get": { "parameterOrder": [ "name" ], "httpMethod": "GET", "description": "Retrieves a specific MetadataSchema.", "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.get", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1MetadataSchema" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas/{metadataSchemasId}", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/metadataSchemas/[^/]+$", "description": "Required. The resource name of the MetadataSchema to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}`", "location": "path", "type": "string" } } }, "list": { "description": "Lists MetadataSchemas.", "httpMethod": "GET", "response": { "$ref": "GoogleCloudAiplatformV1ListMetadataSchemasResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/metadataSchemas", "path": "v1/{+parent}/metadataSchemas", "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.metadataStores.metadataSchemas.list", "parameters": { "pageSize": { "type": "integer", "format": "int32", "location": "query", "description": "The maximum number of MetadataSchemas to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100." }, "filter": { "description": "A query to filter available MetadataSchemas for matching results.", "type": "string", "location": "query" }, "parent": { "location": "path", "type": "string", "description": "Required. The MetadataStore whose MetadataSchemas should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true }, "pageToken": { "type": "string", "description": "A page token, received from a previous MetadataService.ListMetadataSchemas call. Provide this to retrieve the next page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.)", "location": "query" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "contexts": { "methods": { "addContextChildren": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:addContextChildren", "parameters": { "context": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "description": "Required. The resource name of the parent Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", "required": true, "type": "string" } }, "response": { "$ref": "GoogleCloudAiplatformV1AddContextChildrenResponse" }, "description": "Adds a set of Contexts as children to a parent Context. If any of the child Contexts have already been added to the parent Context, they are simply skipped. If this call would create a cycle or cause any Context to have more than 10 parents, the request will fail with an INVALID_ARGUMENT error.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+context}:addContextChildren", "id": "aiplatform.projects.locations.metadataStores.contexts.addContextChildren", "request": { "$ref": "GoogleCloudAiplatformV1AddContextChildrenRequest" }, "httpMethod": "POST", "parameterOrder": [ "context" ] }, "purge": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "parameters": { "parent": { "type": "string", "description": "Required. The metadata store to purge Contexts from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true } }, "description": "Purges Contexts.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts:purge", "path": "v1/{+parent}/contexts:purge", "id": "aiplatform.projects.locations.metadataStores.contexts.purge", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "request": { "$ref": "GoogleCloudAiplatformV1PurgeContextsRequest" } }, "removeContextChildren": { "request": { "$ref": "GoogleCloudAiplatformV1RemoveContextChildrenRequest" }, "parameters": { "context": { "description": "Required. The resource name of the parent Context. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "type": "string", "location": "path", "required": true } }, "parameterOrder": [ "context" ], "path": "v1/{+context}:removeContextChildren", "id": "aiplatform.projects.locations.metadataStores.contexts.removeContextChildren", "description": "Remove a set of children contexts from a parent Context. If any of the child Contexts were NOT added to the parent Context, they are simply skipped.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:removeContextChildren", "response": { "$ref": "GoogleCloudAiplatformV1RemoveContextChildrenResponse" }, "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "addContextArtifactsAndExecutions": { "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.", "parameterOrder": [ "context" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.metadataStores.contexts.addContextArtifactsAndExecutions", "request": { "$ref": "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1AddContextArtifactsAndExecutionsResponse" }, "parameters": { "context": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "description": "Required. The resource name of the Context that the Artifacts and Executions belong to. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:addContextArtifactsAndExecutions", "path": "v1/{+context}:addContextArtifactsAndExecutions" }, "create": { "id": "aiplatform.projects.locations.metadataStores.contexts.create", "description": "Creates a Context associated with a MetadataStore.", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "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}`" }, "contextId": { "location": "query", "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.)" } }, "httpMethod": "POST", "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1Context" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/contexts", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts", "response": { "$ref": "GoogleCloudAiplatformV1Context" } }, "delete": { "description": "Deletes a stored Context.", "parameterOrder": [ "name" ], "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.metadataStores.contexts.delete", "parameters": { "etag": { "location": "query", "type": "string", "description": "Optional. The etag of the Context to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION." }, "force": { "location": "query", "description": "The force deletion semantics is still undefined. Users should not use this field.", "type": "boolean" }, "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "description": "Required. The resource name of the Context to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", "required": true } }, "httpMethod": "DELETE" }, "list": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1ListContextsResponse" }, "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "description": "Required. The MetadataStore whose Contexts should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "required": true, "type": "string" }, "pageSize": { "description": "The maximum number of Contexts to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100.", "location": "query", "type": "integer", "format": "int32" }, "pageToken": { "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.)", "location": "query", "type": "string" }, "orderBy": { "location": "query", "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." }, "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" } }, "description": "Lists Contexts on the MetadataStore.", "id": "aiplatform.projects.locations.metadataStores.contexts.list", "path": "v1/{+parent}/contexts", "parameterOrder": [ "parent" ], "httpMethod": "GET" }, "queryContextLineageSubgraph": { "parameterOrder": [ "context" ], "httpMethod": "GET", "description": "Retrieves Artifacts and Executions within the specified Context, connected by Event edges and returned as a LineageSubgraph.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.metadataStores.contexts.queryContextLineageSubgraph", "path": "v1/{+context}:queryContextLineageSubgraph", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}:queryContextLineageSubgraph", "response": { "$ref": "GoogleCloudAiplatformV1LineageSubgraph" }, "parameters": { "context": { "description": "Required. The resource name of the Context whose Artifacts and Executions should be retrieved as a LineageSubgraph. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}` The request may error with FAILED_PRECONDITION if the number of Artifacts, the number of Executions, or the number of Events that would be returned for the Context exceeds 1000.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "location": "path", "type": "string" } } }, "get": { "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "description": "Required. The resource name of the Context to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`", "type": "string", "required": true } }, "id": "aiplatform.projects.locations.metadataStores.contexts.get", "description": "Retrieves a specific Context.", "response": { "$ref": "GoogleCloudAiplatformV1Context" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}" }, "patch": { "path": "v1/{+name}", "parameters": { "allowMissing": { "type": "boolean", "description": "If set to true, and the Context is not found, a new Context is created.", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "required": true, "description": "Immutable. The resource name of the Context.", "location": "path", "type": "string" }, "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Optional. A FieldMask indicating which fields should be updated.", "type": "string" } }, "request": { "$ref": "GoogleCloudAiplatformV1Context" }, "response": { "$ref": "GoogleCloudAiplatformV1Context" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}", "id": "aiplatform.projects.locations.metadataStores.contexts.patch", "httpMethod": "PATCH", "parameterOrder": [ "name" ], "description": "Updates a stored Context." } }, "resources": { "operations": { "methods": { "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "path": "v1/{+name}:cancel", "id": "aiplatform.projects.locations.metadataStores.contexts.operations.cancel", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.contexts.operations.get", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}", "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}" }, "delete": { "path": "v1/{+name}", "id": "aiplatform.projects.locations.metadataStores.contexts.operations.delete", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted." } }, "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}" }, "wait": { "parameters": { "timeout": { "type": "string", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query" }, "name": { "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "required": true, "location": "path", "type": "string" } }, "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.contexts.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:wait" }, "list": { "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation's parent resource.", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+/contexts/[^/]+$", "required": true }, "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", "description": "The standard list filter.", "location": "query" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations", "id": "aiplatform.projects.locations.metadataStores.contexts.operations.list", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations" } } } } } }, "methods": { "create": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.metadataStores.create", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the Location where the MetadataStore should be created. Format: `projects/{project}/locations/{location}/`" }, "metadataStoreId": { "description": "The {metadatastore} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataStores in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataStore.)", "location": "query", "type": "string" } }, "request": { "$ref": "GoogleCloudAiplatformV1MetadataStore" }, "description": "Initializes a MetadataStore, including allocation of resources.", "path": "v1/{+parent}/metadataStores", "httpMethod": "POST" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.metadataStores.delete", "path": "v1/{+name}", "httpMethod": "DELETE", "description": "Deletes a single MetadataStore and all its child resources (Artifacts, Executions, and Contexts).", "parameters": { "force": { "location": "query", "description": "Deprecated: Field is no longer supported.", "type": "boolean", "deprecated": true }, "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "description": "Required. The resource name of the MetadataStore to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "required": true, "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" } }, "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.metadataStores.get", "description": "Retrieves a specific MetadataStore.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores/{metadataStoresId}", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/metadataStores/[^/]+$", "required": true, "description": "Required. The resource name of the MetadataStore to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}`", "type": "string" } }, "response": { "$ref": "GoogleCloudAiplatformV1MetadataStore" } }, "list": { "parameterOrder": [ "parent" ], "httpMethod": "GET", "description": "Lists MetadataStores for a Location.", "id": "aiplatform.projects.locations.metadataStores.list", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/metadataStores", "path": "v1/{+parent}/metadataStores", "response": { "$ref": "GoogleCloudAiplatformV1ListMetadataStoresResponse" }, "parameters": { "parent": { "location": "path", "type": "string", "description": "Required. The Location whose MetadataStores should be listed. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "pageSize": { "location": "query", "type": "integer", "description": "The maximum number of Metadata Stores to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100.", "format": "int32" }, "pageToken": { "type": "string", "location": "query", "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.)" } } } } }, "dataLabelingJobs": { "resources": { "operations": { "methods": { "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations", "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "name": { "type": "string", "description": "The name of the operation's parent resource.", "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$" }, "pageSize": { "location": "query", "description": "The standard list page size.", "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" ], "path": "v1/{+name}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "aiplatform.projects.locations.dataLabelingJobs.operations.list", "httpMethod": "GET" }, "delete": { "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`.", "parameters": { "name": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}", "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.dataLabelingJobs.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}" }, "get": { "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}", "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "required": true, "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.dataLabelingJobs.operations.get" }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.dataLabelingJobs.operations.cancel", "parameterOrder": [ "name" ], "httpMethod": "POST", "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "required": true, "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } } }, "wait": { "id": "aiplatform.projects.locations.dataLabelingJobs.operations.wait", "path": "v1/{+name}:wait", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+/operations/[^/]+$" }, "timeout": { "type": "string", "format": "google-duration", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "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.", "httpMethod": "POST" } } } }, "methods": { "cancel": { "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", "description": "Required. The name of the DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", "location": "path" } }, "request": { "$ref": "GoogleCloudAiplatformV1CancelDataLabelingJobRequest" }, "description": "Cancels a DataLabelingJob. Success of cancellation is not guaranteed.", "httpMethod": "POST", "path": "v1/{+name}:cancel", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.dataLabelingJobs.cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" } }, "create": { "response": { "$ref": "GoogleCloudAiplatformV1DataLabelingJob" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs", "id": "aiplatform.projects.locations.dataLabelingJobs.create", "parameterOrder": [ "parent" ], "description": "Creates a DataLabelingJob.", "request": { "$ref": "GoogleCloudAiplatformV1DataLabelingJob" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/dataLabelingJobs", "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "description": "Required. The parent of the DataLabelingJob. Format: `projects/{project}/locations/{location}`", "required": true } } }, "delete": { "description": "Deletes a DataLabelingJob.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.dataLabelingJobs.delete", "parameters": { "name": { "location": "path", "description": "Required. The name of the DataLabelingJob to be deleted. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", "required": true } } }, "list": { "response": { "$ref": "GoogleCloudAiplatformV1ListDataLabelingJobsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs", "id": "aiplatform.projects.locations.dataLabelingJobs.list", "path": "v1/{+parent}/dataLabelingJobs", "description": "Lists DataLabelingJobs in a Location.", "httpMethod": "GET", "parameterOrder": [ "parent" ], "parameters": { "readMask": { "description": "Mask specifying which fields to read. FieldMask represents a set of symbolic field paths. For example, the mask can be `paths: \"name\"`. The \"name\" here is a field in DataLabelingJob. If this field is not set, all fields of the DataLabelingJob are returned.", "type": "string", "location": "query", "format": "google-fieldmask" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "parent": { "location": "path", "description": "Required. The parent of the DataLabelingJob. Format: `projects/{project}/locations/{location}`", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$" }, "filter": { "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", "type": "string" }, "orderBy": { "description": "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" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "parameters": { "name": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/dataLabelingJobs/[^/]+$", "required": true, "description": "Required. The name of the DataLabelingJob. Format: `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`" } }, "description": "Gets a DataLabelingJob.", "parameterOrder": [ "name" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.dataLabelingJobs.get", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs/{dataLabelingJobsId}", "response": { "$ref": "GoogleCloudAiplatformV1DataLabelingJob" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET" } } }, "skills": { "resources": { "operations": { "methods": { "cancel": { "httpMethod": "POST", "id": "aiplatform.projects.locations.skills.operations.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`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/skills/{skillsId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "path": "v1/{+name}:cancel", "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/skills/[^/]+/operations/[^/]+$", "required": true } } }, "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/skills/{skillsId}/operations/{operationsId}", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/skills/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "required": true } }, "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.skills.operations.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "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." }, "delete": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/skills/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.skills.operations.delete", "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/skills/{skillsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" } }, "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/skills/{skillsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "timeout": { "format": "google-duration", "location": "query", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." }, "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/skills/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "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.", "httpMethod": "POST", "id": "aiplatform.projects.locations.skills.operations.wait" }, "list": { "id": "aiplatform.projects.locations.skills.operations.list", "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/skills/{skillsId}/operations", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/skills/[^/]+$", "type": "string", "required": true, "description": "The name of the operation's parent resource." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "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.", "type": "boolean", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "pageSize": { "description": "The standard list page size.", "format": "int32", "location": "query", "type": "integer" } } } } } } }, "taskStores": { "resources": { "operations": { "methods": { "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.taskStores.operations.get", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/taskStores/{taskStoresId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "path": "v1/{+name}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/taskStores/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "type": "string", "required": true } }, "parameterOrder": [ "name" ] }, "delete": { "id": "aiplatform.projects.locations.taskStores.operations.delete", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/taskStores/[^/]+/operations/[^/]+$", "location": "path" } }, "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/taskStores/{taskStoresId}/operations/{operationsId}", "httpMethod": "DELETE" }, "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.taskStores.operations.list", "parameters": { "pageSize": { "description": "The standard list page size.", "format": "int32", "location": "query", "type": "integer" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "name": { "location": "path", "type": "string", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/taskStores/[^/]+$", "required": true }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/taskStores/{taskStoresId}/operations", "path": "v1/{+name}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "cancel": { "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/taskStores/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "type": "string", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "httpMethod": "POST", "id": "aiplatform.projects.locations.taskStores.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/taskStores/{taskStoresId}/operations/{operationsId}:cancel", "path": "v1/{+name}:cancel" }, "wait": { "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/taskStores/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "format": "google-duration", "location": "query" } }, "path": "v1/{+name}:wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/taskStores/{taskStoresId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.taskStores.operations.wait", "httpMethod": "POST" } } } } }, "nasJobs": { "methods": { "cancel": { "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`.", "parameters": { "name": { "location": "path", "description": "Required. The name of the NasJob to cancel. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", "type": "string", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}:cancel", "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.nasJobs.cancel", "request": { "$ref": "GoogleCloudAiplatformV1CancelNasJobRequest" }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST" }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "id": "aiplatform.projects.locations.nasJobs.list", "parameters": { "pageToken": { "description": "The standard list page token. Typically obtained via ListNasJobsResponse.next_page_token of the previous JobService.ListNasJobs call.", "location": "query", "type": "string" }, "filter": { "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", "type": "string", "location": "query" }, "readMask": { "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "location": "query", "type": "string" }, "parent": { "required": true, "description": "Required. The resource name of the Location to list the NasJobs from. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "location": "path" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." } }, "path": "v1/{+parent}/nasJobs", "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs", "description": "Lists NasJobs in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1ListNasJobsResponse" } }, "create": { "path": "v1/{+parent}/nasJobs", "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Location to create the NasJob in. Format: `projects/{project}/locations/{location}`" } }, "description": "Creates a NasJob", "id": "aiplatform.projects.locations.nasJobs.create", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1NasJob" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs", "request": { "$ref": "GoogleCloudAiplatformV1NasJob" }, "httpMethod": "POST" }, "delete": { "description": "Deletes a NasJob.", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", "type": "string", "required": true, "description": "Required. The name of the NasJob resource to be deleted. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`" } }, "id": "aiplatform.projects.locations.nasJobs.delete" }, "get": { "path": "v1/{+name}", "response": { "$ref": "GoogleCloudAiplatformV1NasJob" }, "id": "aiplatform.projects.locations.nasJobs.get", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}", "parameters": { "name": { "required": true, "description": "Required. The name of the NasJob resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", "type": "string", "location": "path" } }, "description": "Gets a NasJob", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "httpMethod": "GET" } }, "resources": { "nasTrialDetails": { "methods": { "list": { "description": "List top NasTrialDetails of a NasJob.", "id": "aiplatform.projects.locations.nasJobs.nasTrialDetails.list", "path": "v1/{+parent}/nasTrialDetails", "parameters": { "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": { "format": "int32", "location": "query", "type": "integer", "description": "The standard list page size." }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+$", "required": true, "description": "Required. The name of the NasJob resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}`", "location": "path", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}/nasTrialDetails", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "httpMethod": "GET", "response": { "$ref": "GoogleCloudAiplatformV1ListNasTrialDetailsResponse" } }, "get": { "httpMethod": "GET", "id": "aiplatform.projects.locations.nasJobs.nasTrialDetails.get", "response": { "$ref": "GoogleCloudAiplatformV1NasTrialDetail" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/nasJobs/{nasJobsId}/nasTrialDetails/{nasTrialDetailsId}", "parameterOrder": [ "name" ], "description": "Gets a NasTrialDetail.", "path": "v1/{+name}", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/nasJobs/[^/]+/nasTrialDetails/[^/]+$", "description": "Required. The name of the NasTrialDetail resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}/nasTrialDetails/{nas_trial_detail}`", "type": "string", "required": true, "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "indexEndpoints": { "methods": { "create": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates an IndexEndpoint.", "path": "v1/{+parent}/indexEndpoints", "parameters": { "parent": { "description": "Required. The resource name of the Location to create the IndexEndpoint in. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path" } }, "request": { "$ref": "GoogleCloudAiplatformV1IndexEndpoint" }, "id": "aiplatform.projects.locations.indexEndpoints.create", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints", "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" } }, "delete": { "parameterOrder": [ "name" ], "description": "Deletes an IndexEndpoint.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "parameters": { "name": { "required": true, "description": "Required. The name of the IndexEndpoint resource to be deleted. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "location": "path", "type": "string" } }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.indexEndpoints.delete" }, "findNeighbors": { "request": { "$ref": "GoogleCloudAiplatformV1FindNeighborsRequest" }, "httpMethod": "POST", "path": "v1/{+indexEndpoint}:findNeighbors", "description": "Finds the nearest neighbors of each vector within the request.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:findNeighbors", "response": { "$ref": "GoogleCloudAiplatformV1FindNeighborsResponse" }, "id": "aiplatform.projects.locations.indexEndpoints.findNeighbors", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "indexEndpoint": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "location": "path", "type": "string", "description": "Required. The name of the index endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`" } }, "parameterOrder": [ "indexEndpoint" ] }, "mutateDeployedIndex": { "parameterOrder": [ "indexEndpoint" ], "parameters": { "updateMask": { "format": "google-fieldmask", "type": "string", "location": "query", "description": "Optional. The update mask applies to the resource. The supported paths are `automatic_resources`, `dedicated_resources`, `enable_access_logging` and `deployed_index_auth_config`. When omitted, the service will perform a full update of all fields. See google.protobuf.FieldMask." }, "indexEndpoint": { "description": "Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "location": "path", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$" } }, "httpMethod": "POST", "path": "v1/{+indexEndpoint}:mutateDeployedIndex", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1DeployedIndex" }, "id": "aiplatform.projects.locations.indexEndpoints.mutateDeployedIndex", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:mutateDeployedIndex", "description": "Update an existing DeployedIndex under an IndexEndpoint.", "response": { "$ref": "GoogleLongrunningOperation" } }, "patch": { "parameters": { "updateMask": { "type": "string", "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask.", "format": "google-fieldmask", "location": "query" }, "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "location": "path", "description": "Output only. The resource name of the IndexEndpoint.", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Updates an IndexEndpoint.", "path": "v1/{+name}", "request": { "$ref": "GoogleCloudAiplatformV1IndexEndpoint" }, "response": { "$ref": "GoogleCloudAiplatformV1IndexEndpoint" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}", "id": "aiplatform.projects.locations.indexEndpoints.patch", "httpMethod": "PATCH" }, "undeployIndex": { "parameterOrder": [ "indexEndpoint" ], "path": "v1/{+indexEndpoint}:undeployIndex", "httpMethod": "POST", "description": "Undeploys an Index from an IndexEndpoint, removing a DeployedIndex from it, and freeing all resources it's using.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:undeployIndex", "response": { "$ref": "GoogleLongrunningOperation" }, "request": { "$ref": "GoogleCloudAiplatformV1UndeployIndexRequest" }, "parameters": { "indexEndpoint": { "type": "string", "location": "path", "description": "Required. The name of the IndexEndpoint resource from which to undeploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.indexEndpoints.undeployIndex" }, "readIndexDatapoints": { "request": { "$ref": "GoogleCloudAiplatformV1ReadIndexDatapointsRequest" }, "parameterOrder": [ "indexEndpoint" ], "path": "v1/{+indexEndpoint}:readIndexDatapoints", "parameters": { "indexEndpoint": { "required": true, "description": "Required. The name of the index endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:readIndexDatapoints", "response": { "$ref": "GoogleCloudAiplatformV1ReadIndexDatapointsResponse" }, "httpMethod": "POST", "description": "Reads the datapoints/vectors of the given IDs. A maximum of 1000 datapoints can be retrieved in a batch.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.indexEndpoints.readIndexDatapoints" }, "deployIndex": { "id": "aiplatform.projects.locations.indexEndpoints.deployIndex", "httpMethod": "POST", "parameterOrder": [ "indexEndpoint" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}:deployIndex", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+indexEndpoint}:deployIndex", "request": { "$ref": "GoogleCloudAiplatformV1DeployIndexRequest" }, "description": "Deploys an Index into this IndexEndpoint, creating a DeployedIndex within it.", "parameters": { "indexEndpoint": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "type": "string", "description": "Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$", "description": "Required. The name of the IndexEndpoint resource. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}`", "location": "path", "type": "string" } }, "description": "Gets an IndexEndpoint.", "id": "aiplatform.projects.locations.indexEndpoints.get", "response": { "$ref": "GoogleCloudAiplatformV1IndexEndpoint" }, "path": "v1/{+name}", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}", "parameterOrder": [ "name" ] }, "list": { "description": "Lists IndexEndpoints in a Location.", "parameters": { "readMask": { "type": "string", "format": "google-fieldmask", "location": "query", "description": "Optional. Mask specifying which fields to read." }, "pageSize": { "description": "Optional. The standard list page size.", "location": "query", "type": "integer", "format": "int32" }, "pageToken": { "description": "Optional. The standard list page token. Typically obtained via ListIndexEndpointsResponse.next_page_token of the previous IndexEndpointService.ListIndexEndpoints call.", "location": "query", "type": "string" }, "parent": { "description": "Required. The resource name of the Location from which to list the IndexEndpoints. Format: `projects/{project}/locations/{location}`", "type": "string", "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$" }, "filter": { "type": "string", "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\"`", "location": "query" } }, "httpMethod": "GET", "path": "v1/{+parent}/indexEndpoints", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints", "id": "aiplatform.projects.locations.indexEndpoints.list", "response": { "$ref": "GoogleCloudAiplatformV1ListIndexEndpointsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ] } }, "resources": { "operations": { "methods": { "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.indexEndpoints.operations.get", "response": { "$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.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "path": "v1/{+name}", "httpMethod": "GET", "parameterOrder": [ "name" ] }, "list": { "id": "aiplatform.projects.locations.indexEndpoints.operations.list", "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+$" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "pageSize": { "type": "integer", "format": "int32", "description": "The standard list page size.", "location": "query" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "returnPartialSuccess": { "location": "query", "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." } }, "path": "v1/{+name}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "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": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations" }, "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameterOrder": [ "name" ], "httpMethod": "POST", "path": "v1/{+name}:cancel", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.indexEndpoints.operations.cancel", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be cancelled.", "required": true, "type": "string" } } }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "location": "query", "format": "google-duration", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.indexEndpoints.operations.wait", "httpMethod": "POST" }, "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexEndpoints/{indexEndpointsId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "DELETE", "id": "aiplatform.projects.locations.indexEndpoints.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "path": "v1/{+name}", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/indexEndpoints/[^/]+/operations/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } } } } } } }, "evaluationSets": { "methods": { "create": { "path": "v1/{+parent}/evaluationSets", "id": "aiplatform.projects.locations.evaluationSets.create", "request": { "$ref": "GoogleCloudAiplatformV1EvaluationSet" }, "description": "Creates an Evaluation Set.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationSets", "response": { "$ref": "GoogleCloudAiplatformV1EvaluationSet" }, "httpMethod": "POST", "parameterOrder": [ "parent" ], "parameters": { "parent": { "type": "string", "location": "path", "description": "Required. The resource name of the Location to create the Evaluation Set in. Format: `projects/{project}/locations/{location}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "parameterOrder": [ "name" ], "path": "v1/{+name}", "parameters": { "name": { "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationSets/[^/]+$", "description": "Required. The name of the EvaluationSet resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes an Evaluation Set.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationSets/{evaluationSetsId}", "httpMethod": "DELETE", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.evaluationSets.delete" }, "patch": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationSets/{evaluationSetsId}", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationSets/[^/]+$", "description": "Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`", "required": true, "type": "string" }, "updateMask": { "type": "string", "description": "Optional. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask.", "location": "query", "format": "google-fieldmask" } }, "response": { "$ref": "GoogleCloudAiplatformV1EvaluationSet" }, "path": "v1/{+name}", "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1EvaluationSet" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates an Evaluation Set.", "httpMethod": "PATCH", "id": "aiplatform.projects.locations.evaluationSets.patch" }, "get": { "id": "aiplatform.projects.locations.evaluationSets.get", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Gets an Evaluation Set.", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationSets/[^/]+$", "required": true, "description": "Required. The name of the EvaluationSet resource. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationSets/{evaluationSetsId}", "response": { "$ref": "GoogleCloudAiplatformV1EvaluationSet" } }, "list": { "id": "aiplatform.projects.locations.evaluationSets.list", "parameterOrder": [ "parent" ], "httpMethod": "GET", "description": "Lists Evaluation Sets.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/evaluationSets", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationSets", "response": { "$ref": "GoogleCloudAiplatformV1ListEvaluationSetsResponse" }, "parameters": { "pageToken": { "type": "string", "location": "query", "description": "Optional. A page token, received from a previous `ListEvaluationSets` 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" }, "parent": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "description": "Required. The resource name of the Location from which to list the Evaluation Sets. Format: `projects/{project}/locations/{location}`" }, "filter": { "description": "Optional. Filter expression that matches a subset of the EvaluationSets to show. For field names both snake_case and camelCase are supported. For more information about filter syntax, see [AIP-160](https://google.aip.dev/160).", "type": "string", "location": "query" }, "pageSize": { "location": "query", "description": "Optional. The maximum number of Evaluation Sets to return.", "format": "int32", "type": "integer" } } }, "import": { "description": "Imports an Evaluation Set.", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1ImportEvaluationSetRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationSets:import", "path": "v1/{+parent}/evaluationSets:import", "id": "aiplatform.projects.locations.evaluationSets.import", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "required": true, "description": "Required. Parent resource name." } } } } }, "pipelineJobs": { "resources": { "operations": { "methods": { "get": { "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "id": "aiplatform.projects.locations.pipelineJobs.operations.get", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "httpMethod": "GET" }, "cancel": { "id": "aiplatform.projects.locations.pipelineJobs.operations.cancel", "httpMethod": "POST", "path": "v1/{+name}:cancel", "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "response": { "$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": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "id": "aiplatform.projects.locations.pipelineJobs.operations.list", "path": "v1/{+name}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", "location": "path", "description": "The name of the operation's parent resource.", "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "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" }, "pageSize": { "location": "query", "format": "int32", "type": "integer", "description": "The standard list page size." } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] }, "delete": { "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}", "path": "v1/{+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`.", "id": "aiplatform.projects.locations.pipelineJobs.operations.delete", "httpMethod": "DELETE" }, "wait": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+/operations/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation resource to wait on.", "required": true }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration", "location": "query" } }, "path": "v1/{+name}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "id": "aiplatform.projects.locations.pipelineJobs.operations.wait", "parameterOrder": [ "name" ], "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" } } } } }, "methods": { "batchCancel": { "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1BatchCancelPipelineJobsRequest" }, "path": "v1/{+parent}/pipelineJobs:batchCancel", "httpMethod": "POST", "id": "aiplatform.projects.locations.pipelineJobs.batchCancel", "description": "Batch cancel PipelineJobs. Firstly the server will check if all the jobs are in non-terminal states, and skip the jobs that are already terminated. If the operation failed, none of the pipeline jobs are cancelled. The server will poll the states of all the pipeline jobs periodically to check the cancellation status. This operation will return an LRO.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}`", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs:batchCancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "httpMethod": "GET", "response": { "$ref": "GoogleCloudAiplatformV1PipelineJob" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}", "description": "Gets a PipelineJob.", "id": "aiplatform.projects.locations.pipelineJobs.get", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", "required": true, "description": "Required. The name of the PipelineJob resource. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`", "location": "path" } }, "path": "v1/{+name}", "parameterOrder": [ "name" ] }, "list": { "httpMethod": "GET", "path": "v1/{+parent}/pipelineJobs", "description": "Lists PipelineJobs in a Location.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs", "response": { "$ref": "GoogleCloudAiplatformV1ListPipelineJobsResponse" }, "id": "aiplatform.projects.locations.pipelineJobs.list", "parameters": { "pageToken": { "description": "The standard list page token. Typically obtained via ListPipelineJobsResponse.next_page_token of the previous PipelineService.ListPipelineJobs call.", "type": "string", "location": "query" }, "pageSize": { "description": "The standard list page size.", "format": "int32", "location": "query", "type": "integer" }, "parent": { "type": "string", "required": true, "description": "Required. The resource name of the Location to list the PipelineJobs from. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path" }, "orderBy": { "type": "string", "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`" }, "filter": { "type": "string", "location": "query", "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\"." }, "readMask": { "type": "string", "format": "google-fieldmask", "location": "query", "description": "Mask specifying which fields to read." } }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}:cancel", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1CancelPipelineJobRequest" }, "path": "v1/{+name}:cancel", "parameters": { "name": { "type": "string", "location": "path", "description": "Required. The name of the PipelineJob to cancel. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`", "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$", "required": true } }, "id": "aiplatform.projects.locations.pipelineJobs.cancel", "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`." }, "create": { "id": "aiplatform.projects.locations.pipelineJobs.create", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "parameters": { "parent": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`", "location": "path" }, "pipelineJobId": { "description": "The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.", "location": "query", "type": "string" } }, "path": "v1/{+parent}/pipelineJobs", "description": "Creates a PipelineJob. A PipelineJob will run immediately when created.", "response": { "$ref": "GoogleCloudAiplatformV1PipelineJob" }, "request": { "$ref": "GoogleCloudAiplatformV1PipelineJob" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs", "httpMethod": "POST" }, "delete": { "description": "Deletes a PipelineJob.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "required": true, "description": "Required. The name of the PipelineJob resource to be deleted. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/pipelineJobs/[^/]+$" } }, "httpMethod": "DELETE", "id": "aiplatform.projects.locations.pipelineJobs.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}" }, "batchDelete": { "path": "v1/{+parent}/pipelineJobs:batchDelete", "request": { "$ref": "GoogleCloudAiplatformV1BatchDeletePipelineJobsRequest" }, "id": "aiplatform.projects.locations.pipelineJobs.batchDelete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/pipelineJobs:batchDelete", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "description": "Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "parameterOrder": [ "parent" ], "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." } } }, "schedules": { "methods": { "resume": { "parameters": { "name": { "location": "path", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", "description": "Required. The name of the Schedule resource to be resumed. Format: `projects/{project}/locations/{location}/schedules/{schedule}`" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$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.", "path": "v1/{+name}:resume", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}:resume", "request": { "$ref": "GoogleCloudAiplatformV1ResumeScheduleRequest" }, "id": "aiplatform.projects.locations.schedules.resume", "httpMethod": "POST" }, "patch": { "parameters": { "updateMask": { "type": "string", "format": "google-fieldmask", "location": "query", "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask." }, "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", "type": "string", "description": "Immutable. The resource name of the Schedule.", "location": "path" } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.schedules.patch", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}", "response": { "$ref": "GoogleCloudAiplatformV1Schedule" }, "description": "Updates an active or paused Schedule. When the Schedule is updated, new runs will be scheduled starting from the updated next execution time after the update time based on the time_specification in the updated Schedule. All unstarted runs before the update time will be skipped while already created runs will NOT be paused or canceled.", "request": { "$ref": "GoogleCloudAiplatformV1Schedule" }, "httpMethod": "PATCH", "parameterOrder": [ "name" ] }, "create": { "httpMethod": "POST", "response": { "$ref": "GoogleCloudAiplatformV1Schedule" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1Schedule" }, "path": "v1/{+parent}/schedules", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules", "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.schedules.create", "description": "Creates a Schedule.", "parameters": { "parent": { "location": "path", "required": true, "description": "Required. The resource name of the Location to create the Schedule in. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$" } } }, "delete": { "parameters": { "name": { "description": "Required. The name of the Schedule resource to be deleted. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", "required": true, "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}", "id": "aiplatform.projects.locations.schedules.delete", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "path": "v1/{+name}", "description": "Deletes a Schedule.", "httpMethod": "DELETE" }, "pause": { "response": { "$ref": "GoogleProtobufEmpty" }, "request": { "$ref": "GoogleCloudAiplatformV1PauseScheduleRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}:pause", "httpMethod": "POST", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.schedules.pause", "parameters": { "name": { "type": "string", "location": "path", "description": "Required. The name of the Schedule resource to be paused. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}: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." }, "get": { "description": "Gets a Schedule.", "parameterOrder": [ "name" ], "httpMethod": "GET", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "description": "Required. The name of the Schedule resource. Format: `projects/{project}/locations/{location}/schedules/{schedule}`", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", "location": "path", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}", "response": { "$ref": "GoogleCloudAiplatformV1Schedule" }, "id": "aiplatform.projects.locations.schedules.get" }, "list": { "parameterOrder": [ "parent" ], "description": "Lists Schedules in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1ListSchedulesResponse" }, "parameters": { "filter": { "location": "query", "description": "Lists the Schedules that match the filter expression. The following fields are supported: * `display_name`: Supports `=`, `!=` comparisons, and `:` wildcard. * `state`: Supports `=` and `!=` comparisons. * `request`: Supports existence of the check. (e.g. `create_pipeline_job_request:*` --\u003e Schedule has create_pipeline_job_request). * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `start_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `end_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, `\u003e=` comparisons and `:*` existence check. Values must be in RFC 3339 format. * `next_run_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. Filter expressions can be combined together using logical operators (`NOT`, `AND` & `OR`). The syntax to define filter expression is based on https://google.aip.dev/160. Examples: * `state=\"ACTIVE\" AND display_name:\"my_schedule_*\"` * `NOT display_name=\"my_schedule\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `end_time\u003e\"2021-05-18T00:00:00Z\" OR NOT end_time:*` * `create_pipeline_job_request:*`", "type": "string" }, "parent": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location to list the Schedules from. Format: `projects/{project}/locations/{location}`", "location": "path" }, "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": { "description": "The standard list page token. Typically obtained via ListSchedulesResponse.next_page_token of the previous ScheduleService.ListSchedules call.", "location": "query", "type": "string" }, "pageSize": { "format": "int32", "description": "The standard list page size. Default to 100 if not specified.", "type": "integer", "location": "query" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.schedules.list", "path": "v1/{+parent}/schedules" } }, "resources": { "operations": { "methods": { "wait": { "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "location": "query" } }, "id": "aiplatform.projects.locations.schedules.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "httpMethod": "POST", "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}:wait" }, "cancel": { "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", "required": true } }, "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.schedules.operations.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`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "httpMethod": "POST" }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted." } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}", "path": "v1/{+name}", "id": "aiplatform.projects.locations.schedules.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`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "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`.", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.schedules.operations.list", "path": "v1/{+name}/operations", "parameters": { "pageSize": { "type": "integer", "format": "int32", "description": "The standard list page size.", "location": "query" }, "name": { "description": "The name of the operation's parent resource.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+$", "location": "path" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "filter": { "description": "The standard list filter.", "type": "string", "location": "query" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "get": { "id": "aiplatform.projects.locations.schedules.operations.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/schedules/{schedulesId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/schedules/[^/]+/operations/[^/]+$", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1/{+name}" } } } } }, "customJobs": { "methods": { "list": { "httpMethod": "GET", "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists CustomJobs in a Location.", "id": "aiplatform.projects.locations.customJobs.list", "response": { "$ref": "GoogleCloudAiplatformV1ListCustomJobsResponse" }, "parameters": { "pageSize": { "location": "query", "type": "integer", "description": "The standard list page size.", "format": "int32" }, "parent": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location to list the CustomJobs from. Format: `projects/{project}/locations/{location}`", "location": "path" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token. Typically obtained via ListCustomJobsResponse.next_page_token of the previous JobService.ListCustomJobs call." }, "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask" }, "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" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs", "path": "v1/{+parent}/customJobs" }, "cancel": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1CancelCustomJobRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}:cancel", "path": "v1/{+name}:cancel", "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", "description": "Required. The name of the CustomJob to cancel. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`", "location": "path" } }, "description": "Cancels a CustomJob. Starts asynchronous cancellation on the CustomJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetCustomJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the CustomJob is not deleted; instead it becomes a job with a CustomJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and CustomJob.state is set to `CANCELLED`.", "id": "aiplatform.projects.locations.customJobs.cancel" }, "get": { "id": "aiplatform.projects.locations.customJobs.get", "parameterOrder": [ "name" ], "path": "v1/{+name}", "parameters": { "name": { "description": "Required. The name of the CustomJob resource. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", "location": "path" } }, "httpMethod": "GET", "description": "Gets a CustomJob.", "response": { "$ref": "GoogleCloudAiplatformV1CustomJob" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}" }, "create": { "path": "v1/{+parent}/customJobs", "description": "Creates a CustomJob. A created CustomJob right away will be attempted to be run.", "parameterOrder": [ "parent" ], "parameters": { "parent": { "description": "Required. The resource name of the Location to create the CustomJob in. Format: `projects/{project}/locations/{location}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "type": "string" } }, "id": "aiplatform.projects.locations.customJobs.create", "response": { "$ref": "GoogleCloudAiplatformV1CustomJob" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs", "request": { "$ref": "GoogleCloudAiplatformV1CustomJob" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST" }, "delete": { "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", "description": "Required. The name of the CustomJob resource to be deleted. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}`", "location": "path" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a CustomJob.", "id": "aiplatform.projects.locations.customJobs.delete", "httpMethod": "DELETE" } }, "resources": { "operations": { "methods": { "get": { "httpMethod": "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.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}", "parameters": { "name": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource." } }, "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.customJobs.operations.get", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string" }, "timeout": { "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "format": "google-duration" } }, "id": "aiplatform.projects.locations.customJobs.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/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.", "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "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.", "type": "string", "location": "query" }, "name": { "description": "The name of the operation's parent resource.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+$", "location": "path" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "pageSize": { "type": "integer", "format": "int32", "location": "query", "description": "The standard list page size." } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.customJobs.operations.list", "path": "v1/{+name}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "httpMethod": "GET" }, "cancel": { "path": "v1/{+name}:cancel", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.customJobs.operations.cancel", "httpMethod": "POST", "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": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}:cancel", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$" } }, "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/customJobs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "required": true, "type": "string" } }, "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/customJobs/{customJobsId}/operations/{operationsId}", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.customJobs.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`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE" } } } } }, "persistentResources": { "methods": { "reboot": { "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "Required. The name of the PersistentResource resource. Format: `projects/{project_id_or_number}/locations/{location_id}/persistentResources/{persistent_resource_id}`", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", "location": "path", "type": "string", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}:reboot", "path": "v1/{+name}:reboot", "request": { "$ref": "GoogleCloudAiplatformV1RebootPersistentResourceRequest" }, "httpMethod": "POST", "id": "aiplatform.projects.locations.persistentResources.reboot", "parameterOrder": [ "name" ], "description": "Reboots a PersistentResource.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}", "request": { "$ref": "GoogleCloudAiplatformV1PersistentResource" }, "parameterOrder": [ "name" ], "httpMethod": "PATCH", "description": "Updates a PersistentResource.", "id": "aiplatform.projects.locations.persistentResources.patch", "parameters": { "updateMask": { "format": "google-fieldmask", "location": "query", "type": "string", "description": "Required. Specify the fields to be overwritten in the PersistentResource by the update method." }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", "location": "path", "description": "Immutable. Resource name of a PersistentResource.", "required": true, "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}" }, "create": { "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.persistentResources.create", "httpMethod": "POST", "description": "Creates a PersistentResource.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "request": { "$ref": "GoogleCloudAiplatformV1PersistentResource" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources", "path": "v1/{+parent}/persistentResources", "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to create the PersistentResource in. Format: `projects/{project}/locations/{location}`", "type": "string", "location": "path" }, "persistentResourceId": { "description": "Required. The ID to use for the PersistentResource, which become the final component of the PersistentResource's resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.", "type": "string", "location": "query" } } }, "delete": { "path": "v1/{+name}", "id": "aiplatform.projects.locations.persistentResources.delete", "httpMethod": "DELETE", "description": "Deletes a PersistentResource.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "required": true, "description": "Required. The name of the PersistentResource to be deleted. Format: `projects/{project}/locations/{location}/persistentResources/{persistent_resource}`", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", "location": "path", "type": "string" } } }, "get": { "parameters": { "name": { "type": "string", "description": "Required. The name of the PersistentResource resource. Format: `projects/{project_id_or_number}/locations/{location_id}/persistentResources/{persistent_resource_id}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", "location": "path" } }, "path": "v1/{+name}", "description": "Gets a PersistentResource.", "response": { "$ref": "GoogleCloudAiplatformV1PersistentResource" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}", "id": "aiplatform.projects.locations.persistentResources.get", "httpMethod": "GET", "parameterOrder": [ "name" ] }, "list": { "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.persistentResources.list", "httpMethod": "GET", "parameters": { "parent": { "description": "Required. The resource name of the Location to list the PersistentResources from. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "required": true }, "pageSize": { "type": "integer", "description": "Optional. The standard list page size.", "format": "int32", "location": "query" }, "pageToken": { "location": "query", "type": "string", "description": "Optional. The standard list page token. Typically obtained via ListPersistentResourcesResponse.next_page_token of the previous PersistentResourceService.ListPersistentResource call." } }, "path": "v1/{+parent}/persistentResources", "description": "Lists PersistentResources in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1ListPersistentResourcesResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources" } }, "resources": { "operations": { "methods": { "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}", "httpMethod": "GET", "id": "aiplatform.projects.locations.persistentResources.operations.get", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", "type": "string" } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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." }, "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "httpMethod": "GET", "parameters": { "pageSize": { "description": "The standard list page size.", "location": "query", "type": "integer", "format": "int32" }, "name": { "type": "string", "description": "The name of the operation's parent resource.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+$", "location": "path" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "filter": { "description": "The standard list filter.", "type": "string", "location": "query" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations", "path": "v1/{+name}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.projects.locations.persistentResources.operations.list" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}", "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", "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`.", "path": "v1/{+name}", "id": "aiplatform.projects.locations.persistentResources.operations.delete" }, "cancel": { "httpMethod": "POST", "parameters": { "name": { "required": true, "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", "type": "string", "location": "path" } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.persistentResources.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "path": "v1/{+name}:cancel", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}:cancel" }, "wait": { "id": "aiplatform.projects.locations.persistentResources.operations.wait", "parameters": { "timeout": { "format": "google-duration", "type": "string", "location": "query", "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." }, "name": { "type": "string", "required": true, "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/persistentResources/[^/]+/operations/[^/]+$", "location": "path" } }, "httpMethod": "POST", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/persistentResources/{persistentResourcesId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait" } } } } }, "tensorboards": { "methods": { "readUsage": { "path": "v1/{+tensorboard}:readUsage", "parameterOrder": [ "tensorboard" ], "httpMethod": "GET", "description": "Returns a list of monthly active users for a given TensorBoard instance.", "parameters": { "tensorboard": { "required": true, "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "type": "string", "location": "path" } }, "id": "aiplatform.projects.locations.tensorboards.readUsage", "response": { "$ref": "GoogleCloudAiplatformV1ReadTensorboardUsageResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:readUsage" }, "get": { "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}", "path": "v1/{+name}", "response": { "$ref": "GoogleCloudAiplatformV1Tensorboard" }, "description": "Gets a Tensorboard.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "id": "aiplatform.projects.locations.tensorboards.get", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "location": "path", "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "type": "string", "required": true } }, "parameterOrder": [ "name" ] }, "create": { "httpMethod": "POST", "id": "aiplatform.projects.locations.tensorboards.create", "request": { "$ref": "GoogleCloudAiplatformV1Tensorboard" }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/tensorboards", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards", "description": "Creates a Tensorboard.", "parameters": { "parent": { "description": "Required. The resource name of the Location to create the Tensorboard in. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } } }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a Tensorboard.", "parameters": { "name": { "description": "Required. The name of the Tensorboard to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "required": true, "type": "string", "location": "path" } }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}", "httpMethod": "DELETE", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.tensorboards.delete", "path": "v1/{+name}" }, "patch": { "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "PATCH", "description": "Updates a Tensorboard.", "id": "aiplatform.projects.locations.tensorboards.patch", "request": { "$ref": "GoogleCloudAiplatformV1Tensorboard" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "required": true, "description": "Output only. Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$" }, "updateMask": { "location": "query", "type": "string", "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.", "format": "google-fieldmask" } } }, "batchRead": { "response": { "$ref": "GoogleCloudAiplatformV1BatchReadTensorboardTimeSeriesDataResponse" }, "parameterOrder": [ "tensorboard" ], "id": "aiplatform.projects.locations.tensorboards.batchRead", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:batchRead", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "tensorboard": { "location": "path", "type": "string", "required": true, "description": "Required. The resource name of the Tensorboard containing TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`. The TensorboardTimeSeries referenced by time_series must be sub resources of this Tensorboard.", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$" }, "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}`", "type": "string", "repeated": true } }, "httpMethod": "GET", "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.", "path": "v1/{+tensorboard}:batchRead" }, "readSize": { "parameterOrder": [ "tensorboard" ], "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}:readSize", "parameters": { "tensorboard": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "type": "string", "description": "Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "location": "path" } }, "response": { "$ref": "GoogleCloudAiplatformV1ReadTensorboardSizeResponse" }, "path": "v1/{+tensorboard}:readSize", "description": "Returns the storage size for a given TensorBoard instance.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.tensorboards.readSize" }, "list": { "description": "Lists Tensorboards in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "id": "aiplatform.projects.locations.tensorboards.list", "httpMethod": "GET", "parameterOrder": [ "parent" ], "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.", "format": "int32", "location": "query", "type": "integer" }, "filter": { "description": "Lists the Tensorboards that match the filter expression.", "type": "string", "location": "query" }, "readMask": { "location": "query", "type": "string", "format": "google-fieldmask", "description": "Mask specifying which fields to read." }, "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "description": "Required. The resource name of the Location to list Tensorboards. Format: `projects/{project}/locations/{location}`", "type": "string" }, "orderBy": { "location": "query", "type": "string", "description": "Field to use to sort the list." }, "pageToken": { "location": "query", "description": "A page token, received from a previous TensorboardService.ListTensorboards call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboards must match the call that provided the page token.", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards", "response": { "$ref": "GoogleCloudAiplatformV1ListTensorboardsResponse" }, "path": "v1/{+parent}/tensorboards" } }, "resources": { "operations": { "methods": { "cancel": { "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}:cancel", "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "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`.", "httpMethod": "POST", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.tensorboards.operations.cancel" }, "list": { "path": "v1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.projects.locations.tensorboards.operations.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation's parent resource.", "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "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." }, "pageSize": { "location": "query", "type": "integer", "format": "int32", "description": "The standard list page size." } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "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`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}", "path": "v1/{+name}", "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "DELETE", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.tensorboards.operations.delete" }, "wait": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.tensorboards.operations.wait", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$" }, "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" } }, "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": { "httpMethod": "GET", "id": "aiplatform.projects.locations.tensorboards.operations.get", "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.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "response": { "$ref": "GoogleLongrunningOperation" } } } }, "experiments": { "methods": { "write": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Write time series data points of multiple TensorboardTimeSeries in multiple TensorboardRun's. If any data fail to be ingested, an error is returned.", "response": { "$ref": "GoogleCloudAiplatformV1WriteTensorboardExperimentDataResponse" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}:write", "path": "v1/{+tensorboardExperiment}:write", "request": { "$ref": "GoogleCloudAiplatformV1WriteTensorboardExperimentDataRequest" }, "parameters": { "tensorboardExperiment": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "location": "path", "description": "Required. The resource name of the TensorboardExperiment to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "type": "string", "required": true } }, "id": "aiplatform.projects.locations.tensorboards.experiments.write", "parameterOrder": [ "tensorboardExperiment" ] }, "get": { "parameterOrder": [ "name" ], "path": "v1/{+name}", "parameters": { "name": { "required": true, "type": "string", "description": "Required. The name of the TensorboardExperiment resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}", "httpMethod": "GET", "description": "Gets a TensorboardExperiment.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "response": { "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" }, "id": "aiplatform.projects.locations.tensorboards.experiments.get" }, "list": { "response": { "$ref": "GoogleCloudAiplatformV1ListTensorboardExperimentsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments", "path": "v1/{+parent}/experiments", "description": "Lists TensorboardExperiments in a Location.", "httpMethod": "GET", "parameters": { "pageToken": { "type": "string", "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" }, "readMask": { "type": "string", "location": "query", "description": "Mask specifying which fields to read.", "format": "google-fieldmask" }, "parent": { "required": true, "description": "Required. The resource name of the Tensorboard to list TensorboardExperiments. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "location": "path", "type": "string" }, "filter": { "type": "string", "location": "query", "description": "Lists the TensorboardExperiments that match the filter expression." }, "pageSize": { "location": "query", "format": "int32", "description": "The maximum number of TensorboardExperiments to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardExperiments are returned. The maximum value is 1000; values above 1000 are coerced to 1000.", "type": "integer" }, "orderBy": { "type": "string", "location": "query", "description": "Field to use to sort the list." } }, "id": "aiplatform.projects.locations.tensorboards.experiments.list", "parameterOrder": [ "parent" ] }, "create": { "request": { "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" }, "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+$", "required": true, "type": "string", "description": "Required. The resource name of the Tensorboard to create the TensorboardExperiment in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`", "location": "path" }, "tensorboardExperimentId": { "type": "string", "location": "query", "description": "Required. The ID to use for the Tensorboard experiment, which becomes the final component of the Tensorboard experiment's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`." } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.tensorboards.experiments.create", "httpMethod": "POST", "description": "Creates a TensorboardExperiment.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments", "path": "v1/{+parent}/experiments", "response": { "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" } }, "delete": { "path": "v1/{+name}", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "description": "Required. The name of the TensorboardExperiment to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "required": true } }, "description": "Deletes a TensorboardExperiment.", "id": "aiplatform.projects.locations.tensorboards.experiments.delete", "httpMethod": "DELETE", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}" }, "patch": { "request": { "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}", "parameters": { "name": { "required": true, "type": "string", "description": "Output only. Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$" }, "updateMask": { "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.", "type": "string", "location": "query", "format": "google-fieldmask" } }, "id": "aiplatform.projects.locations.tensorboards.experiments.patch", "description": "Updates a TensorboardExperiment.", "response": { "$ref": "GoogleCloudAiplatformV1TensorboardExperiment" }, "path": "v1/{+name}", "httpMethod": "PATCH", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] }, "batchCreate": { "description": "Batch create TensorboardTimeSeries that belong to a TensorboardExperiment.", "request": { "$ref": "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesRequest" }, "parameters": { "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "type": "string", "location": "path", "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}` The TensorboardRuns referenced by the parent fields in the CreateTensorboardTimeSeriesRequest messages must be sub resources of this TensorboardExperiment." } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.tensorboards.experiments.batchCreate", "path": "v1/{+parent}:batchCreate", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}:batchCreate", "response": { "$ref": "GoogleCloudAiplatformV1BatchCreateTensorboardTimeSeriesResponse" }, "httpMethod": "POST" } }, "resources": { "operations": { "methods": { "wait": { "parameters": { "timeout": { "location": "query", "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", "format": "google-duration" }, "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "location": "path" } }, "id": "aiplatform.projects.locations.tensorboards.experiments.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "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": { "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "description": "The name of the operation resource.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "id": "aiplatform.projects.locations.tensorboards.experiments.operations.get", "httpMethod": "GET", "path": "v1/{+name}" }, "cancel": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "httpMethod": "POST", "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "required": true } }, "id": "aiplatform.projects.locations.tensorboards.experiments.operations.cancel" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "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`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "description": "The name of the operation resource to be deleted." } }, "id": "aiplatform.projects.locations.tensorboards.experiments.operations.delete", "parameterOrder": [ "name" ], "path": "v1/{+name}" }, "list": { "parameters": { "pageSize": { "type": "integer", "location": "query", "description": "The standard list page size.", "format": "int32" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "location": "path" }, "returnPartialSuccess": { "location": "query", "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/operations", "path": "v1/{+name}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.tensorboards.experiments.operations.list" } } }, "runs": { "resources": { "operations": { "methods": { "wait": { "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.wait", "httpMethod": "POST", "parameterOrder": [ "name" ], "parameters": { "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" }, "name": { "type": "string", "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "required": true } }, "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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." }, "delete": { "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted." } }, "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/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`.", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.delete", "parameterOrder": [ "name" ], "path": "v1/{+name}", "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource.", "type": "string" } }, "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.get", "path": "v1/{+name}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}", "httpMethod": "GET", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/operations/[^/]+$", "type": "string", "location": "path" } }, "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.cancel", "path": "v1/{+name}:cancel" }, "list": { "parameters": { "filter": { "description": "The standard list filter.", "type": "string", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "location": "path", "description": "The name of the operation's parent resource." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "pageSize": { "format": "int32", "type": "integer", "description": "The standard list page size.", "location": "query" } }, "path": "v1/{+name}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.projects.locations.tensorboards.experiments.runs.operations.list" } } }, "timeSeries": { "methods": { "readBlobData": { "response": { "$ref": "GoogleCloudAiplatformV1ReadTensorboardBlobDataResponse" }, "httpMethod": "GET", "parameterOrder": [ "timeSeries" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:readBlobData", "path": "v1/{+timeSeries}:readBlobData", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "timeSeries": { "required": true, "description": "Required. The resource name of the TensorboardTimeSeries to list Blobs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$" }, "blobIds": { "description": "IDs of the blobs to read.", "location": "query", "type": "string", "repeated": true } }, "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.", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.readBlobData" }, "get": { "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.get", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "location": "path", "description": "Required. The name of the TensorboardTimeSeries resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`" } }, "path": "v1/{+name}", "description": "Gets a TensorboardTimeSeries.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}", "response": { "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" }, "parameterOrder": [ "name" ], "httpMethod": "GET" }, "list": { "path": "v1/{+parent}/timeSeries", "description": "Lists TensorboardTimeSeries in a Location.", "httpMethod": "GET", "response": { "$ref": "GoogleCloudAiplatformV1ListTensorboardTimeSeriesResponse" }, "parameters": { "pageToken": { "location": "query", "type": "string", "description": "A page token, received from a previous TensorboardService.ListTensorboardTimeSeries call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardTimeSeries must match the call that provided the page token." }, "orderBy": { "location": "query", "type": "string", "description": "Field to use to sort the list." }, "parent": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "location": "path", "description": "Required. The resource name of the TensorboardRun to list TensorboardTimeSeries. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`" }, "pageSize": { "type": "integer", "format": "int32", "location": "query", "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." }, "readMask": { "type": "string", "format": "google-fieldmask", "location": "query", "description": "Mask specifying which fields to read." }, "filter": { "description": "Lists the TensorboardTimeSeries that match the filter expression.", "type": "string", "location": "query" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.list", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameterOrder": [ "parent" ] }, "exportTensorboardTimeSeries": { "response": { "$ref": "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:exportTensorboardTimeSeries", "parameters": { "tensorboardTimeSeries": { "description": "Required. The resource name of the TensorboardTimeSeries to export data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", "type": "string", "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$" } }, "parameterOrder": [ "tensorboardTimeSeries" ], "description": "Exports a TensorboardTimeSeries' data. Data is returned in paginated responses.", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.exportTensorboardTimeSeries", "httpMethod": "POST", "path": "v1/{+tensorboardTimeSeries}:exportTensorboardTimeSeries", "request": { "$ref": "GoogleCloudAiplatformV1ExportTensorboardTimeSeriesDataRequest" } }, "patch": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}", "parameterOrder": [ "name" ], "description": "Updates a TensorboardTimeSeries.", "request": { "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" }, "response": { "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" }, "httpMethod": "PATCH", "path": "v1/{+name}", "parameters": { "updateMask": { "location": "query", "format": "google-fieldmask", "description": "Required. Field mask is used to specify the fields to be overwritten in the TensorboardTimeSeries resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", "type": "string" }, "name": { "location": "path", "description": "Output only. Name of the TensorboardTimeSeries.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "required": true } }, "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.patch" }, "create": { "description": "Creates a TensorboardTimeSeries.", "httpMethod": "POST", "path": "v1/{+parent}/timeSeries", "response": { "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.create", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1TensorboardTimeSeries" }, "parameterOrder": [ "parent" ], "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "type": "string", "description": "Required. The resource name of the TensorboardRun to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", "required": true }, "tensorboardTimeSeriesId": { "type": "string", "description": "Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match \"a-z0-9{0, 127}\"", "location": "query" } } }, "delete": { "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "required": true, "description": "Required. The name of the TensorboardTimeSeries to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`", "location": "path", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.delete", "description": "Deletes a TensorboardTimeSeries.", "parameterOrder": [ "name" ], "httpMethod": "DELETE" }, "read": { "description": "Reads a TensorboardTimeSeries' data. By default, if the number of data points stored is less than 1000, all data is returned. Otherwise, 1000 data points is randomly selected from this time series and returned. This value can be changed by changing max_data_points, which can't be greater than 10k.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "response": { "$ref": "GoogleCloudAiplatformV1ReadTensorboardTimeSeriesDataResponse" }, "parameters": { "maxDataPoints": { "location": "query", "type": "integer", "format": "int32", "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." }, "tensorboardTimeSeries": { "location": "path", "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}`", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "required": true, "type": "string" }, "filter": { "location": "query", "description": "Reads the TensorboardTimeSeries' data that match the filter expression.", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}:read", "path": "v1/{+tensorboardTimeSeries}:read", "parameterOrder": [ "tensorboardTimeSeries" ], "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.read", "httpMethod": "GET" } }, "resources": { "operations": { "methods": { "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "pageSize": { "format": "int32", "type": "integer", "description": "The standard list page size.", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+$", "type": "string", "description": "The name of the operation's parent resource.", "required": true, "location": "path" } }, "path": "v1/{+name}/operations", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.list", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.delete", "path": "v1/{+name}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "required": true, "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "type": "string", "location": "path" } } }, "get": { "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.get", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ], "path": "v1/{+name}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." }, "cancel": { "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "type": "string", "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`.", "path": "v1/{+name}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" } }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "id": "aiplatform.projects.locations.tensorboards.experiments.runs.timeSeries.operations.wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}/timeSeries/{timeSeriesId}/operations/{operationsId}:wait", "parameters": { "timeout": { "format": "google-duration", "location": "query", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." }, "name": { "location": "path", "type": "string", "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+/timeSeries/[^/]+/operations/[^/]+$" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait" } } } } } }, "methods": { "patch": { "id": "aiplatform.projects.locations.tensorboards.experiments.runs.patch", "parameters": { "updateMask": { "format": "google-fieldmask", "type": "string", "description": "Required. Field mask is used to specify the fields to be overwritten in the TensorboardRun resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified.", "location": "query" }, "name": { "description": "Output only. Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "required": true } }, "description": "Updates a TensorboardRun.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}", "request": { "$ref": "GoogleCloudAiplatformV1TensorboardRun" }, "response": { "$ref": "GoogleCloudAiplatformV1TensorboardRun" }, "path": "v1/{+name}", "parameterOrder": [ "name" ], "httpMethod": "PATCH" }, "list": { "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.tensorboards.experiments.runs.list", "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs", "response": { "$ref": "GoogleCloudAiplatformV1ListTensorboardRunsResponse" }, "path": "v1/{+parent}/runs", "description": "Lists TensorboardRuns in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "pageToken": { "location": "query", "description": "A page token, received from a previous TensorboardService.ListTensorboardRuns call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardRuns must match the call that provided the page token.", "type": "string" }, "filter": { "type": "string", "description": "Lists the TensorboardRuns that match the filter expression.", "location": "query" }, "readMask": { "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask", "type": "string" }, "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "description": "Required. The resource name of the TensorboardExperiment to list TensorboardRuns. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "required": true, "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.", "type": "integer", "location": "query", "format": "int32" }, "orderBy": { "description": "Field to use to sort the list.", "location": "query", "type": "string" } } }, "create": { "id": "aiplatform.projects.locations.tensorboards.experiments.runs.create", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/runs", "description": "Creates a TensorboardRun.", "parameters": { "parent": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$", "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`", "location": "path", "required": true }, "tensorboardRunId": { "location": "query", "description": "Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.", "type": "string" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1TensorboardRun" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs", "response": { "$ref": "GoogleCloudAiplatformV1TensorboardRun" } }, "delete": { "id": "aiplatform.projects.locations.tensorboards.experiments.runs.delete", "httpMethod": "DELETE", "parameterOrder": [ "name" ], "description": "Deletes a TensorboardRun.", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}", "parameters": { "name": { "location": "path", "type": "string", "description": "Required. The name of the TensorboardRun to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "required": true } } }, "get": { "id": "aiplatform.projects.locations.tensorboards.experiments.runs.get", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "required": true, "description": "Required. The name of the TensorboardRun resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`", "location": "path", "type": "string" } }, "parameterOrder": [ "name" ], "description": "Gets a TensorboardRun.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}", "path": "v1/{+name}", "httpMethod": "GET", "response": { "$ref": "GoogleCloudAiplatformV1TensorboardRun" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ] }, "batchCreate": { "request": { "$ref": "GoogleCloudAiplatformV1BatchCreateTensorboardRunsRequest" }, "path": "v1/{+parent}/runs:batchCreate", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs:batchCreate", "httpMethod": "POST", "response": { "$ref": "GoogleCloudAiplatformV1BatchCreateTensorboardRunsResponse" }, "parameters": { "parent": { "description": "Required. The resource name of the TensorboardExperiment to create the TensorboardRuns in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}` The parent field in the CreateTensorboardRunRequest messages must match this field.", "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+$" } }, "id": "aiplatform.projects.locations.tensorboards.experiments.runs.batchCreate", "parameterOrder": [ "parent" ], "description": "Batch create TensorboardRuns.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "write": { "parameters": { "tensorboardRun": { "pattern": "^projects/[^/]+/locations/[^/]+/tensorboards/[^/]+/experiments/[^/]+/runs/[^/]+$", "location": "path", "required": true, "type": "string", "description": "Required. The resource name of the TensorboardRun to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`" } }, "id": "aiplatform.projects.locations.tensorboards.experiments.runs.write", "request": { "$ref": "GoogleCloudAiplatformV1WriteTensorboardRunDataRequest" }, "description": "Write time series data points into multiple TensorboardTimeSeries under a TensorboardRun. If any data fail to be ingested, an error is returned.", "response": { "$ref": "GoogleCloudAiplatformV1WriteTensorboardRunDataResponse" }, "parameterOrder": [ "tensorboardRun" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/tensorboards/{tensorboardsId}/experiments/{experimentsId}/runs/{runsId}:write", "httpMethod": "POST", "path": "v1/{+tensorboardRun}:write" } } } } } } }, "featureGroups": { "methods": { "setIamPolicy": { "path": "v1/{+resource}:setIamPolicy", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featureGroups.setIamPolicy", "httpMethod": "POST", "parameterOrder": [ "resource" ], "parameters": { "resource": { "type": "string", "required": true, "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "location": "path" } }, "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}:setIamPolicy", "response": { "$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." }, "patch": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "updateMask": { "description": "Field mask is used to specify the fields to be overwritten in the FeatureGroup resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `description` * `big_query` * `big_query.entity_id_columns` * `service_agent_type`", "type": "string", "format": "google-fieldmask", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "location": "path", "type": "string", "required": true, "description": "Identifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featureGroups.patch", "path": "v1/{+name}", "description": "Updates the parameters of a single FeatureGroup.", "request": { "$ref": "GoogleCloudAiplatformV1FeatureGroup" }, "parameterOrder": [ "name" ], "httpMethod": "PATCH" }, "get": { "parameters": { "name": { "description": "Required. The name of the FeatureGroup resource.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "location": "path" } }, "description": "Gets details of a single FeatureGroup.", "path": "v1/{+name}", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}", "response": { "$ref": "GoogleCloudAiplatformV1FeatureGroup" }, "httpMethod": "GET", "id": "aiplatform.projects.locations.featureGroups.get", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "getIamPolicy": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}:getIamPolicy", "path": "v1/{+resource}:getIamPolicy", "response": { "$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", "type": "integer", "format": "int32" }, "resource": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.featureGroups.getIamPolicy", "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "parameterOrder": [ "resource" ] }, "testIamPermissions": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featureGroups.testIamPermissions", "parameterOrder": [ "resource" ], "parameters": { "permissions": { "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", "type": "string", "location": "query", "repeated": true }, "resource": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "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.", "required": true } }, "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.", "path": "v1/{+resource}:testIamPermissions", "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}:testIamPermissions", "httpMethod": "POST" }, "create": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups", "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1FeatureGroup" }, "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "path": "v1/{+parent}/featureGroups", "description": "Creates a new FeatureGroup in a given project and location.", "parameters": { "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "type": "string", "description": "Required. The resource name of the Location to create FeatureGroups. Format: `projects/{project}/locations/{location}`" }, "featureGroupId": { "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.", "type": "string" } }, "id": "aiplatform.projects.locations.featureGroups.create" }, "delete": { "description": "Deletes a single FeatureGroup.", "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}", "parameters": { "force": { "location": "query", "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.)", "type": "boolean" }, "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "description": "Required. The name of the FeatureGroup to be deleted. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.featureGroups.delete" }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "id": "aiplatform.projects.locations.featureGroups.list", "path": "v1/{+parent}/featureGroups", "description": "Lists FeatureGroups in a given project and location.", "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups", "response": { "$ref": "GoogleCloudAiplatformV1ListFeatureGroupsResponse" }, "parameters": { "filter": { "description": "Lists the FeatureGroups that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, and `\u003e=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. Examples: * `create_time \u003e \"2020-01-01\" OR update_time \u003e \"2020-01-01\"` FeatureGroups created or updated after 2020-01-01. * `labels.env = \"prod\"` FeatureGroups with label \"env\" set to \"prod\".", "location": "query", "type": "string" }, "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "description": "Required. The resource name of the Location to list FeatureGroups. Format: `projects/{project}/locations/{location}`", "type": "string" }, "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" }, "pageToken": { "location": "query", "type": "string", "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." }, "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" } } } }, "resources": { "operations": { "methods": { "delete": { "parameterOrder": [ "name" ], "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$" } }, "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`.", "id": "aiplatform.projects.locations.featureGroups.operations.delete", "path": "v1/{+name}" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featureGroups.operations.wait", "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", "location": "path" }, "timeout": { "format": "google-duration", "location": "query", "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." } } }, "get": { "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource." } }, "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/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.", "httpMethod": "GET", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featureGroups.operations.get" }, "listWait": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/operations/{operationsId}:wait", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "required": true }, "filter": { "description": "The standard list filter.", "type": "string", "location": "query" }, "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" }, "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "pageSize": { "description": "The standard list page size.", "location": "query", "type": "integer", "format": "int32" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "aiplatform.projects.locations.featureGroups.operations.listWait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait", "httpMethod": "GET" } } }, "features": { "resources": { "operations": { "methods": { "delete": { "id": "aiplatform.projects.locations.featureGroups.features.operations.delete", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", "path": "v1/{+name}", "httpMethod": "DELETE", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string" } } }, "listWait": { "parameters": { "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "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.", "type": "boolean", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "pageSize": { "description": "The standard list page size.", "format": "int32", "type": "integer", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "required": true, "description": "The name of the operation's parent resource." } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait", "id": "aiplatform.projects.locations.featureGroups.features.operations.listWait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET", "parameterOrder": [ "name" ] }, "get": { "parameterOrder": [ "name" ], "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "id": "aiplatform.projects.locations.featureGroups.features.operations.get", "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "required": true } } }, "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+/operations/[^/]+$" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration", "location": "query" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameterOrder": [ "name" ], "path": "v1/{+name}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "id": "aiplatform.projects.locations.featureGroups.features.operations.wait" } } } }, "methods": { "get": { "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1Feature" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}", "httpMethod": "GET", "description": "Gets details of a single Feature.", "id": "aiplatform.projects.locations.featureGroups.features.get", "parameters": { "name": { "required": true, "type": "string", "description": "Required. The name of the Feature resource. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}" }, "batchCreate": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features:batchCreate", "parameters": { "parent": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "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}`", "required": true } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1BatchCreateFeaturesRequest" }, "path": "v1/{+parent}/features:batchCreate", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featureGroups.features.batchCreate", "httpMethod": "POST", "description": "Creates a batch of Features in a given FeatureGroup." }, "list": { "httpMethod": "GET", "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features", "response": { "$ref": "GoogleCloudAiplatformV1ListFeaturesResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/features", "description": "Lists Features in a given FeatureGroup.", "id": "aiplatform.projects.locations.featureGroups.features.list", "parameters": { "latestStatsCount": { "type": "integer", "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." }, "filter": { "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.", "type": "string", "location": "query" }, "pageToken": { "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", "location": "query" }, "pageSize": { "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.", "type": "integer" }, "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: * `feature_id` * `value_type` (Not supported for FeatureRegistry Feature) * `create_time` * `update_time`", "location": "query", "type": "string" }, "readMask": { "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "location": "query", "type": "string" }, "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "type": "string", "required": true, "description": "Required. The resource name of the Location to list Features. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`" } } }, "patch": { "httpMethod": "PATCH", "id": "aiplatform.projects.locations.featureGroups.features.patch", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}", "path": "v1/{+name}", "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1Feature" }, "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", "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.", "required": true, "type": "string" }, "updateMask": { "location": "query", "format": "google-fieldmask", "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)" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates the parameters of a single Feature." }, "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "path": "v1/{+parent}/features", "parameters": { "parent": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+$", "description": "Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}`", "location": "path" }, "featureId": { "location": "query", "description": "Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.", "type": "string" } }, "id": "aiplatform.projects.locations.featureGroups.features.create", "request": { "$ref": "GoogleCloudAiplatformV1Feature" }, "description": "Creates a new Feature in a given FeatureGroup.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features", "httpMethod": "POST" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureGroups/{featureGroupsId}/features/{featuresId}", "parameters": { "name": { "description": "Required. The name of the Features to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureGroups/[^/]+/features/[^/]+$", "location": "path", "type": "string" } }, "description": "Deletes a single Feature.", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.featureGroups.features.delete", "parameterOrder": [ "name" ] } } } } }, "interactions": { "methods": { "createStream": { "path": "v1/projects/{projectsId}/locations/{locationsId}/interactions:createStream", "parameterOrder": [ "projectsId", "locationsId" ], "id": "aiplatform.projects.locations.interactions.createStream", "description": "Creates an interaction and streams the response.", "httpMethod": "POST", "parameters": { "locationsId": { "required": true, "location": "path", "type": "string" }, "projectsId": { "required": true, "type": "string", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GenaiVertexV1InteractionStreamingEvent" }, "request": { "$ref": "GenaiVertexV1CreateInteractionRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/interactions:createStream" }, "create": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/interactions:create", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates an interaction.", "httpMethod": "POST", "id": "aiplatform.projects.locations.interactions.create", "response": { "$ref": "GenaiVertexV1Interaction" }, "request": { "$ref": "GenaiVertexV1CreateInteractionRequest" }, "path": "v1/projects/{projectsId}/locations/{locationsId}/interactions:create", "parameters": { "projectsId": { "type": "string", "required": true, "location": "path" }, "locationsId": { "type": "string", "location": "path", "required": true } }, "parameterOrder": [ "projectsId", "locationsId" ] }, "delete": { "response": { "$ref": "GenaiVertexV1DeleteInteractionResponse" }, "id": "aiplatform.projects.locations.interactions.delete", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/interactions/{interactionsId}", "path": "v1/{+name}", "httpMethod": "DELETE", "deprecated": true, "parameters": { "name": { "type": "string", "description": "Required. The name of the interaction to delete. Format: interactions/{interaction}", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/interactions/[^/]+$", "required": true } }, "description": "Deletes an interaction.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "datasets": { "resources": { "datasetVersions": { "methods": { "create": { "path": "v1/{+parent}/datasetVersions", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.datasets.datasetVersions.create", "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions", "request": { "$ref": "GoogleCloudAiplatformV1DatasetVersion" }, "parameters": { "parent": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "required": true } }, "description": "Create a version from a Dataset." }, "delete": { "parameters": { "name": { "location": "path", "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", "required": true } }, "path": "v1/{+name}", "id": "aiplatform.projects.locations.datasets.datasetVersions.delete", "parameterOrder": [ "name" ], "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Deletes a Dataset version.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}" }, "get": { "path": "v1/{+name}", "httpMethod": "GET", "description": "Gets a Dataset version.", "parameters": { "name": { "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", "location": "path" }, "readMask": { "description": "Mask specifying which fields to read.", "type": "string", "format": "google-fieldmask", "location": "query" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.datasets.datasetVersions.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", "response": { "$ref": "GoogleCloudAiplatformV1DatasetVersion" } }, "list": { "path": "v1/{+parent}/datasetVersions", "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.datasetVersions.list", "description": "Lists DatasetVersions in a Dataset.", "response": { "$ref": "GoogleCloudAiplatformV1ListDatasetVersionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions", "parameters": { "pageToken": { "description": "Optional. The standard list page token.", "location": "query", "type": "string" }, "orderBy": { "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", "type": "string" }, "pageSize": { "format": "int32", "description": "Optional. The standard list page size.", "location": "query", "type": "integer" }, "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "description": "Required. The resource name of the Dataset to list DatasetVersions from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "type": "string" }, "readMask": { "type": "string", "location": "query", "description": "Optional. Mask specifying which fields to read.", "format": "google-fieldmask" }, "filter": { "location": "query", "type": "string", "description": "Optional. The standard list filter." } } }, "patch": { "parameters": { "updateMask": { "location": "query", "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name`", "format": "google-fieldmask", "type": "string" }, "name": { "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", "description": "Output only. Identifier. The resource name of the DatasetVersion. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "request": { "$ref": "GoogleCloudAiplatformV1DatasetVersion" }, "id": "aiplatform.projects.locations.datasets.datasetVersions.patch", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", "httpMethod": "PATCH", "parameterOrder": [ "name" ], "description": "Updates a DatasetVersion.", "response": { "$ref": "GoogleCloudAiplatformV1DatasetVersion" } }, "restore": { "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/datasetVersions/[^/]+$", "required": true, "description": "Required. The name of the DatasetVersion resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`" } }, "description": "Restores a dataset version.", "parameterOrder": [ "name" ], "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.datasets.datasetVersions.restore", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}:restore", "path": "v1/{+name}:restore" } } }, "annotationSpecs": { "resources": { "operations": { "methods": { "wait": { "path": "v1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "timeout": { "format": "google-duration", "location": "query", "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." }, "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to wait on.", "type": "string" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:wait" }, "cancel": { "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:cancel", "httpMethod": "POST", "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}:cancel", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." }, "get": { "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.get", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "delete": { "parameters": { "name": { "required": true, "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } }, "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" ], "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "httpMethod": "DELETE", "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.delete" }, "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "description": "The standard list filter.", "type": "string", "location": "query" }, "returnPartialSuccess": { "location": "query", "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "pageSize": { "type": "integer", "location": "query", "description": "The standard list page size.", "format": "int32" }, "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+$", "description": "The name of the operation's parent resource.", "location": "path", "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "id": "aiplatform.projects.locations.datasets.annotationSpecs.operations.list", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations", "httpMethod": "GET", "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." } } } }, "methods": { "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1AnnotationSpec" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}", "parameterOrder": [ "name" ], "path": "v1/{+name}", "parameters": { "readMask": { "format": "google-fieldmask", "type": "string", "location": "query", "description": "Mask specifying which fields to read." }, "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/annotationSpecs/[^/]+$", "description": "Required. The name of the AnnotationSpec resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}`", "required": true, "type": "string" } }, "description": "Gets an AnnotationSpec.", "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.annotationSpecs.get" } } }, "operations": { "methods": { "get": { "parameters": { "name": { "description": "The name of the operation resource.", "type": "string", "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.operations.get" }, "wait": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "timeout": { "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", "location": "query" }, "name": { "location": "path", "type": "string", "required": true, "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$" } }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "id": "aiplatform.projects.locations.datasets.operations.wait", "httpMethod": "POST", "parameterOrder": [ "name" ] }, "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}/operations", "parameters": { "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean", "location": "query" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "name": { "location": "path", "type": "string", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "pageSize": { "description": "The standard list page size.", "type": "integer", "location": "query", "format": "int32" } }, "id": "aiplatform.projects.locations.datasets.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "httpMethod": "GET" }, "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "httpMethod": "DELETE", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.datasets.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", "required": true, "location": "path", "type": "string" } }, "path": "v1/{+name}" }, "cancel": { "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.datasets.operations.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`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "httpMethod": "POST", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/operations/{operationsId}:cancel" } } }, "dataItems": { "resources": { "annotations": { "methods": { "list": { "description": "Lists Annotations belongs to a dataitem.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "location": "query", "format": "int32", "type": "integer", "description": "The standard list page size." }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "readMask": { "location": "query", "type": "string", "format": "google-fieldmask", "description": "Mask specifying which fields to read." }, "orderBy": { "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", "type": "string" }, "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+$", "type": "string", "location": "path", "description": "Required. The resource name of the DataItem to list Annotations from. Format: `projects/{project}/locations/{location}/datasets/{dataset}/dataItems/{data_item}`" }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." } }, "id": "aiplatform.projects.locations.datasets.dataItems.annotations.list", "response": { "$ref": "GoogleCloudAiplatformV1ListAnnotationsResponse" }, "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations", "path": "v1/{+parent}/annotations", "httpMethod": "GET" } }, "resources": { "operations": { "methods": { "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/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`.", "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource to be deleted.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.delete", "httpMethod": "DELETE", "path": "v1/{+name}" }, "wait": { "parameters": { "timeout": { "format": "google-duration", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" }, "name": { "required": true, "description": "The name of the operation resource to wait on.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$" } }, "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:wait", "path": "v1/{+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": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST" }, "cancel": { "response": { "$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`.", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:cancel", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}:cancel", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.cancel" }, "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}", "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "path": "v1/{+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.", "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.get", "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource." } } }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+$", "type": "string", "required": true }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "pageSize": { "type": "integer", "format": "int32", "location": "query", "description": "The standard list page size." }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" } }, "id": "aiplatform.projects.locations.datasets.dataItems.annotations.operations.list" } } } } }, "operations": { "methods": { "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.datasets.dataItems.operations.wait" }, "cancel": { "path": "v1/{+name}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:cancel", "id": "aiplatform.projects.locations.datasets.dataItems.operations.cancel", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "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.", "type": "boolean", "location": "query" }, "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+$", "location": "path", "required": true, "description": "The name of the operation's parent resource." }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "pageSize": { "description": "The standard list page size.", "type": "integer", "location": "query", "format": "int32" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations", "parameterOrder": [ "name" ], "httpMethod": "GET", "id": "aiplatform.projects.locations.datasets.dataItems.operations.list" }, "delete": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string" } }, "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": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "httpMethod": "DELETE", "path": "v1/{+name}", "id": "aiplatform.projects.locations.datasets.dataItems.operations.delete" }, "get": { "httpMethod": "GET", "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.datasets.dataItems.operations.get", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}" } } } }, "methods": { "list": { "response": { "$ref": "GoogleCloudAiplatformV1ListDataItemsResponse" }, "id": "aiplatform.projects.locations.datasets.dataItems.list", "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/dataItems", "parameterOrder": [ "parent" ], "path": "v1/{+parent}/dataItems", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists DataItems 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." }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "parent": { "location": "path", "required": true, "description": "Required. The resource name of the Dataset to list DataItems from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "type": "string" }, "pageSize": { "format": "int32", "location": "query", "description": "The standard list page size.", "type": "integer" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "readMask": { "description": "Mask specifying which fields to read.", "type": "string", "format": "google-fieldmask", "location": "query" } } } } }, "savedQueries": { "methods": { "delete": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "id": "aiplatform.projects.locations.datasets.savedQueries.delete", "parameters": { "name": { "required": true, "description": "Required. The resource name of the SavedQuery to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+$" } }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}", "description": "Deletes a SavedQuery.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" } }, "list": { "path": "v1/{+parent}/savedQueries", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1ListSavedQueriesResponse" }, "parameters": { "readMask": { "description": "Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask", "type": "string" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "location": "query", "format": "int32", "type": "integer", "description": "The standard list page size." }, "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.", "type": "string" }, "parent": { "location": "path", "type": "string", "description": "Required. The resource name of the Dataset to list SavedQueries from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries", "id": "aiplatform.projects.locations.datasets.savedQueries.list", "description": "Lists SavedQueries in a Dataset." } }, "resources": { "operations": { "methods": { "list": { "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "pageSize": { "format": "int32", "location": "query", "type": "integer", "description": "The standard list page size." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+$", "required": true }, "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" } }, "id": "aiplatform.projects.locations.datasets.savedQueries.operations.list", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations", "path": "v1/{+name}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "httpMethod": "GET" }, "get": { "id": "aiplatform.projects.locations.datasets.savedQueries.operations.get", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource.", "type": "string", "location": "path" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "httpMethod": "GET" }, "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$" } }, "parameterOrder": [ "name" ], "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.datasets.savedQueries.operations.cancel", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:cancel", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "timeout": { "format": "google-duration", "type": "string", "location": "query", "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." }, "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to wait on.", "required": true } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.datasets.savedQueries.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait", "httpMethod": "POST" }, "delete": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "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`.", "parameterOrder": [ "name" ], "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", "id": "aiplatform.projects.locations.datasets.savedQueries.operations.delete", "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "DELETE" } } } } } }, "methods": { "export": { "request": { "$ref": "GoogleCloudAiplatformV1ExportDataRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:export", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "path": "v1/{+name}:export", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Exports data from a Dataset.", "parameters": { "name": { "type": "string", "location": "path", "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true } }, "id": "aiplatform.projects.locations.datasets.export" }, "patch": { "parameterOrder": [ "name" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.datasets.patch", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "description": "Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "type": "string", "location": "path" }, "updateMask": { "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name` * `description` * `labels`", "type": "string", "location": "query", "format": "google-fieldmask" } }, "request": { "$ref": "GoogleCloudAiplatformV1Dataset" }, "response": { "$ref": "GoogleCloudAiplatformV1Dataset" }, "httpMethod": "PATCH", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates a Dataset." }, "getIamPolicy": { "id": "aiplatform.projects.locations.datasets.getIamPolicy", "httpMethod": "POST", "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "parameters": { "options.requestedPolicyVersion": { "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "location": "query", "format": "int32", "type": "integer" }, "resource": { "location": "path", "type": "string", "required": true, "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:getIamPolicy", "parameterOrder": [ "resource" ], "response": { "$ref": "GoogleIamV1Policy" }, "path": "v1/{+resource}:getIamPolicy", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "import": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true } }, "path": "v1/{+name}:import", "request": { "$ref": "GoogleCloudAiplatformV1ImportDataRequest" }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:import", "description": "Imports data into a Dataset.", "id": "aiplatform.projects.locations.datasets.import", "httpMethod": "POST" }, "get": { "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "description": "Required. The name of the Dataset resource.", "required": true, "type": "string" }, "readMask": { "location": "query", "format": "google-fieldmask", "description": "Mask specifying which fields to read.", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "path": "v1/{+name}", "httpMethod": "GET", "description": "Gets a Dataset.", "response": { "$ref": "GoogleCloudAiplatformV1Dataset" }, "id": "aiplatform.projects.locations.datasets.get", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}" }, "list": { "parameters": { "parent": { "required": true, "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The name of the Dataset's parent resource. Format: `projects/{project}/locations/{location}`" }, "pageSize": { "type": "integer", "format": "int32", "description": "The standard list page size.", "location": "query" }, "readMask": { "location": "query", "type": "string", "format": "google-fieldmask", "description": "Mask specifying which fields to read." }, "filter": { "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `display_name`: supports = and != * `metadata_schema_uri`: supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"`", "type": "string", "location": "query" }, "orderBy": { "type": "string", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time`", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.datasets.list", "path": "v1/{+parent}/datasets", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists Datasets in a Location.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets", "httpMethod": "GET", "response": { "$ref": "GoogleCloudAiplatformV1ListDatasetsResponse" } }, "searchDataItems": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:searchDataItems", "response": { "$ref": "GoogleCloudAiplatformV1SearchDataItemsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.datasets.searchDataItems", "httpMethod": "GET", "description": "Searches DataItems in a Dataset.", "parameters": { "annotationsLimit": { "type": "integer", "format": "int32", "location": "query", "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." }, "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": { "location": "query", "deprecated": true, "type": "string", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending." }, "orderByDataItem": { "type": "string", "description": "A comma-separated list of data item fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", "location": "query" }, "fieldMask": { "format": "google-fieldmask", "description": "Mask specifying which fields of DataItemView to read.", "type": "string", "location": "query" }, "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" }, "orderByAnnotation.orderBy": { "location": "query", "type": "string", "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." }, "annotationsFilter": { "description": "An expression for filtering the Annotations that will be returned per DataItem. * `annotation_spec_id` - for = or !=.", "type": "string", "deprecated": true, "location": "query" }, "annotationFilters": { "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.", "repeated": true, "type": "string" }, "dataItemFilter": { "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)`", "type": "string", "location": "query" }, "dataset": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "location": "path", "type": "string", "description": "Required. The resource name of the Dataset from which to search DataItems. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" }, "savedQuery": { "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.", "location": "query", "type": "string", "deprecated": true }, "pageToken": { "location": "query", "type": "string", "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." }, "pageSize": { "format": "int32", "location": "query", "type": "integer", "description": "Requested page size. Server may return fewer results than requested. Default and maximum page size is 100." } }, "path": "v1/{+dataset}:searchDataItems", "parameterOrder": [ "dataset" ] }, "create": { "path": "v1/{+parent}/datasets", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "parent" ], "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets", "id": "aiplatform.projects.locations.datasets.create", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "description": "Required. The resource name of the Location to create the Dataset in. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string" } }, "description": "Creates a Dataset.", "request": { "$ref": "GoogleCloudAiplatformV1Dataset" } }, "delete": { "parameterOrder": [ "name" ], "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a Dataset.", "id": "aiplatform.projects.locations.datasets.delete", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "location": "path", "type": "string", "required": true, "description": "Required. The resource name of the Dataset to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" } }, "path": "v1/{+name}" }, "setIamPolicy": { "parameters": { "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "type": "string", "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." } }, "path": "v1/{+resource}:setIamPolicy", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "parameterOrder": [ "resource" ], "response": { "$ref": "GoogleIamV1Policy" }, "id": "aiplatform.projects.locations.datasets.setIamPolicy", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:setIamPolicy", "httpMethod": "POST", "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors." }, "testIamPermissions": { "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.", "id": "aiplatform.projects.locations.datasets.testIamPermissions", "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "parameters": { "resource": { "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/datasets/[^/]+$", "required": true, "type": "string" }, "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).", "type": "string", "repeated": true } }, "parameterOrder": [ "resource" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/datasets/{datasetsId}:testIamPermissions", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+resource}:testIamPermissions", "httpMethod": "POST" } } }, "operations": { "methods": { "get": { "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.operations.get", "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource." } } }, "cancel": { "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "path": "v1/{+name}:cancel", "response": { "$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`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}:cancel" }, "list": { "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/operations", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "The name of the operation's parent resource.", "location": "path", "type": "string" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "pageSize": { "format": "int32", "type": "integer", "description": "The standard list page size.", "location": "query" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" } }, "path": "v1/{+name}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "aiplatform.projects.locations.operations.list" }, "delete": { "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "type": "string", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.operations.delete", "response": { "$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`.", "httpMethod": "DELETE", "path": "v1/{+name}" }, "wait": { "parameters": { "name": { "description": "The name of the operation resource to wait on.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/operations/[^/]+$", "location": "path" }, "timeout": { "format": "google-duration", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/operations/{operationsId}:wait", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.operations.wait", "path": "v1/{+name}:wait" } } }, "publishers": { "resources": { "models": { "resources": { "invoke": { "methods": { "invoke": { "parameterOrder": [ "endpoint", "invokeId" ], "request": { "$ref": "GoogleCloudAiplatformV1InvokeRequest" }, "httpMethod": "POST", "parameters": { "endpoint": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "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" } }, "response": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}/invoke/{invokeId}", "path": "v1/{+endpoint}/invoke/{+invokeId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "id": "aiplatform.projects.locations.publishers.models.invoke.invoke", "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request." } } } }, "methods": { "rawPredict": { "path": "v1/{+endpoint}:rawPredict", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:rawPredict", "httpMethod": "POST", "id": "aiplatform.projects.locations.publishers.models.rawPredict", "response": { "$ref": "GoogleApiHttpBody" }, "request": { "$ref": "GoogleCloudAiplatformV1RawPredictRequest" }, "parameterOrder": [ "endpoint" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Perform an online prediction with an arbitrary HTTP payload. The response includes the following HTTP headers: * `X-Vertex-AI-Endpoint-Id`: ID of the Endpoint that served this prediction. * `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's DeployedModel that served this prediction.", "parameters": { "endpoint": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path", "type": "string" } } }, "computeTokens": { "path": "v1/{+endpoint}:computeTokens", "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:computeTokens", "request": { "$ref": "GoogleCloudAiplatformV1ComputeTokensRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1ComputeTokensResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "endpoint": { "type": "string", "location": "path", "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids.", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true } }, "description": "Return a list of tokens based on the input text.", "id": "aiplatform.projects.locations.publishers.models.computeTokens", "parameterOrder": [ "endpoint" ] }, "streamRawPredict": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "httpMethod": "POST", "parameterOrder": [ "endpoint" ], "id": "aiplatform.projects.locations.publishers.models.streamRawPredict", "response": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:streamRawPredict", "description": "Perform a streaming online prediction with an arbitrary HTTP payload.", "path": "v1/{+endpoint}:streamRawPredict", "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", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$" } }, "request": { "$ref": "GoogleCloudAiplatformV1StreamRawPredictRequest" } }, "predict": { "id": "aiplatform.projects.locations.publishers.models.predict", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:predict", "response": { "$ref": "GoogleCloudAiplatformV1PredictResponse" }, "parameterOrder": [ "endpoint" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "httpMethod": "POST", "parameters": { "endpoint": { "type": "string", "required": true, "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "location": "path" } }, "path": "v1/{+endpoint}:predict", "request": { "$ref": "GoogleCloudAiplatformV1PredictRequest" }, "description": "" }, "generateContent": { "path": "v1/{+model}:generateContent", "parameters": { "model": { "required": true, "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$" } }, "id": "aiplatform.projects.locations.publishers.models.generateContent", "parameterOrder": [ "model" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Generate content with multimodal inputs.", "request": { "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:generateContent" }, "predictLongRunning": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:predictLongRunning", "response": { "$ref": "GoogleLongrunningOperation" }, "request": { "$ref": "GoogleCloudAiplatformV1PredictLongRunningRequest" }, "httpMethod": "POST", "description": "", "id": "aiplatform.projects.locations.publishers.models.predictLongRunning", "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}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameterOrder": [ "endpoint" ], "path": "v1/{+endpoint}:predictLongRunning" }, "embedContent": { "request": { "$ref": "GoogleCloudAiplatformV1EmbedContentRequest" }, "httpMethod": "POST", "path": "v1/{+model}:embedContent", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:embedContent", "parameterOrder": [ "model" ], "response": { "$ref": "GoogleCloudAiplatformV1EmbedContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Embed content with multimodal inputs.", "parameters": { "model": { "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", "location": "path" } }, "id": "aiplatform.projects.locations.publishers.models.embedContent" }, "streamGenerateContent": { "parameterOrder": [ "model" ], "parameters": { "model": { "location": "path", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:streamGenerateContent", "path": "v1/{+model}:streamGenerateContent", "response": { "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" }, "request": { "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" }, "description": "Generate content with multimodal inputs with streaming support.", "id": "aiplatform.projects.locations.publishers.models.streamGenerateContent", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "httpMethod": "POST" }, "countTokens": { "path": "v1/{+endpoint}:countTokens", "parameters": { "endpoint": { "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "description": "Perform a token counting.", "id": "aiplatform.projects.locations.publishers.models.countTokens", "request": { "$ref": "GoogleCloudAiplatformV1CountTokensRequest" }, "parameterOrder": [ "endpoint" ], "httpMethod": "POST", "response": { "$ref": "GoogleCloudAiplatformV1CountTokensResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:countTokens", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "serverStreamingPredict": { "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1StreamingPredictRequest" }, "parameters": { "endpoint": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "required": true } }, "description": "Perform a server-side streaming online prediction request for Vertex LLM streaming.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:serverStreamingPredict", "httpMethod": "POST", "response": { "$ref": "GoogleCloudAiplatformV1StreamingPredictResponse" }, "path": "v1/{+endpoint}:serverStreamingPredict", "id": "aiplatform.projects.locations.publishers.models.serverStreamingPredict", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ] }, "fetchPredictOperation": { "id": "aiplatform.projects.locations.publishers.models.fetchPredictOperation", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:fetchPredictOperation", "httpMethod": "POST", "path": "v1/{+endpoint}:fetchPredictOperation", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "endpoint": { "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", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$" } }, "request": { "$ref": "GoogleCloudAiplatformV1FetchPredictOperationRequest" }, "parameterOrder": [ "endpoint" ], "description": "Fetch an asynchronous online prediction operation." } } }, "v1": { "methods": { "responses": { "id": "aiplatform.projects.locations.publishers.v1.responses", "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.", "httpMethod": "POST", "request": { "$ref": "GoogleApiHttpBody" }, "path": "v1/{+endpoint}/v1/responses", "parameters": { "endpoint": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+$", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path", "type": "string" }, "deployedModelId": { "type": "string", "description": "ID of the DeployedModel that serves the invoke request.", "location": "query" } }, "parameterOrder": [ "endpoint" ], "response": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/v1/responses", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ] } }, "resources": { "responses": { "methods": { "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/v1/responses/{responsesId}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleApiHttpBody" }, "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.publishers.v1.responses.delete", "description": "Deletes the response from the endpoint.", "parameters": { "name": { "required": true, "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/v1/responses/[^/]+$", "type": "string", "description": "Required. The name of the Response resource to be deleted. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}/responses/{response}`" } } }, "compact": { "parameters": { "endpoint": { "type": "string", "required": true, "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+$", "location": "path" }, "deployedModelId": { "type": "string", "description": "ID of the DeployedModel that serves the invoke request.", "location": "query" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleApiHttpBody" }, "path": "v1/{+endpoint}/v1/responses/compact", "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/v1/responses/compact", "httpMethod": "POST", "response": { "$ref": "GoogleApiHttpBody" }, "id": "aiplatform.projects.locations.publishers.v1.responses.compact" }, "get": { "httpMethod": "GET", "id": "aiplatform.projects.locations.publishers.v1.responses.get", "path": "v1/{+name}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Gets the response from the endpoint.", "response": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/v1/responses/{responsesId}", "parameters": { "name": { "location": "path", "required": true, "description": "Required. The name of the Response resource. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}/responses/{response}`", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/v1/responses/[^/]+$", "type": "string" } } } } } } } } }, "servingProfiles": { "resources": { "operations": { "methods": { "cancel": { "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/servingProfiles/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "id": "aiplatform.projects.locations.servingProfiles.operations.cancel", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/servingProfiles/{servingProfilesId}/operations/{operationsId}:cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "httpMethod": "POST" }, "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.projects.locations.servingProfiles.operations.list", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/servingProfiles/{servingProfilesId}/operations", "path": "v1/{+name}/operations", "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "parameters": { "returnPartialSuccess": { "location": "query", "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageSize": { "location": "query", "description": "The standard list page size.", "type": "integer", "format": "int32" }, "name": { "description": "The name of the operation's parent resource.", "type": "string", "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/servingProfiles/[^/]+$" } } }, "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/servingProfiles/{servingProfilesId}/operations/{operationsId}", "path": "v1/{+name}", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/servingProfiles/[^/]+/operations/[^/]+$", "location": "path", "required": true } }, "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.servingProfiles.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`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "httpMethod": "DELETE" }, "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.", "httpMethod": "GET", "parameterOrder": [ "name" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.servingProfiles.operations.get", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/servingProfiles/{servingProfilesId}/operations/{operationsId}", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/servingProfiles/[^/]+/operations/[^/]+$" } } }, "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.", "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.servingProfiles.operations.wait", "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/servingProfiles/[^/]+/operations/[^/]+$" }, "timeout": { "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "format": "google-duration" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/servingProfiles/{servingProfilesId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] } } } }, "methods": { "get": { "id": "aiplatform.projects.locations.servingProfiles.get", "path": "v1/{+name}", "httpMethod": "GET", "response": { "$ref": "GoogleCloudAiplatformV1ServingProfile" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/servingProfiles/{servingProfilesId}", "parameters": { "name": { "description": "Required. The name of the ServingProfile resource. Format: `projects/{project}/locations/{location}/servingProfiles/{serving_profile}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/servingProfiles/[^/]+$", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Gets a ServingProfile." }, "create": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/servingProfiles", "request": { "$ref": "GoogleCloudAiplatformV1ServingProfile" }, "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the Location to create the ServingProfile in. Format: `projects/{project}/locations/{location}`", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$" }, "servingProfileId": { "location": "query", "description": "Required. The ID to use for the ServingProfile, which will become the final component of the ServingProfile's resource name. This value should be 1-63 characters, and valid characters are `^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$`.", "type": "string" } }, "id": "aiplatform.projects.locations.servingProfiles.create", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/servingProfiles", "httpMethod": "POST", "description": "Creates a ServingProfile.", "parameterOrder": [ "parent" ] }, "delete": { "description": "Deletes a ServingProfile.", "parameterOrder": [ "name" ], "httpMethod": "DELETE", "id": "aiplatform.projects.locations.servingProfiles.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/servingProfiles/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the ServingProfile resource to be deleted. Format: `projects/{project}/locations/{location}/servingProfiles/{serving_profile}`", "location": "path" } }, "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/servingProfiles/{servingProfilesId}" }, "list": { "response": { "$ref": "GoogleCloudAiplatformV1ListServingProfilesResponse" }, "path": "v1/{+parent}/servingProfiles", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/servingProfiles", "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.servingProfiles.list", "parameters": { "parent": { "description": "Required. The resource name of the Location to list the ServingProfiles from. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "pageToken": { "location": "query", "description": "Optional. The standard list page token.", "type": "string" }, "pageSize": { "format": "int32", "description": "Optional. The standard list page size. If unspecified, at most 100 ServingProfiles will be returned. The maximum value is 1000; values above 1000 will be coerced to 1000.", "type": "integer", "location": "query" } }, "description": "Lists ServingProfiles in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET" }, "patch": { "description": "Updates a ServingProfile.", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1ServingProfile" }, "parameters": { "name": { "required": true, "description": "Identifier. The resource name of the ServingProfile.", "pattern": "^projects/[^/]+/locations/[^/]+/servingProfiles/[^/]+$", "type": "string", "location": "path" }, "updateMask": { "type": "string", "description": "Optional. The list of fields to update; see https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#fieldmask. If omitted, all populated (non-empty) mutable fields are updated; if set to `[\"*\"]`, all mutable fields are fully replaced (unpopulated values are cleared).", "format": "google-fieldmask", "location": "query" } }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/servingProfiles/{servingProfilesId}", "id": "aiplatform.projects.locations.servingProfiles.patch", "response": { "$ref": "GoogleCloudAiplatformV1ServingProfile" } } } }, "semanticGovernancePolicyEngine": { "methods": { "deprovision": { "path": "v1/{+name}:deprovision", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.semanticGovernancePolicyEngine.deprovision", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/semanticGovernancePolicyEngine:deprovision", "request": { "$ref": "GoogleCloudAiplatformV1DeprovisionSemanticGovernancePolicyEngineRequest" }, "parameters": { "name": { "type": "string", "required": true, "description": "Required. The resource name of the SemanticGovernancePolicyEngine to deprovision. Format: projects/{project}/locations/{location}/semanticGovernancePolicyEngine", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/semanticGovernancePolicyEngine$" } }, "description": "Deprovisions the SemanticGovernancePolicyEngine, tearing down the associated tenant project, GKE cluster, and PSC service attachments. This operation is irreversible. Returns a long-running operation; poll for completion. The response contains the SemanticGovernancePolicyEngine in DEPROVISIONING state.", "httpMethod": "POST", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "trainingPipelines": { "methods": { "list": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines", "id": "aiplatform.projects.locations.trainingPipelines.list", "parameters": { "filter": { "type": "string", "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" }, "pageSize": { "location": "query", "description": "The standard list page size.", "format": "int32", "type": "integer" }, "pageToken": { "description": "The standard list page token. Typically obtained via ListTrainingPipelinesResponse.next_page_token of the previous PipelineService.ListTrainingPipelines call.", "type": "string", "location": "query" }, "readMask": { "description": "Mask specifying which fields to read.", "type": "string", "format": "google-fieldmask", "location": "query" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "description": "Required. The resource name of the Location to list the TrainingPipelines from. Format: `projects/{project}/locations/{location}`", "required": true, "type": "string" } }, "response": { "$ref": "GoogleCloudAiplatformV1ListTrainingPipelinesResponse" }, "description": "Lists TrainingPipelines in a Location.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/trainingPipelines", "parameterOrder": [ "parent" ], "httpMethod": "GET" }, "get": { "path": "v1/{+name}", "description": "Gets a TrainingPipeline.", "id": "aiplatform.projects.locations.trainingPipelines.get", "response": { "$ref": "GoogleCloudAiplatformV1TrainingPipeline" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}", "parameters": { "name": { "description": "Required. The name of the TrainingPipeline resource. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", "required": true, "type": "string", "location": "path" } }, "parameterOrder": [ "name" ], "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}:cancel", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1CancelTrainingPipelineRequest" }, "response": { "$ref": "GoogleProtobufEmpty" }, "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`.", "id": "aiplatform.projects.locations.trainingPipelines.cancel", "httpMethod": "POST", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", "description": "Required. The name of the TrainingPipeline to cancel. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`", "type": "string", "location": "path", "required": true } }, "parameterOrder": [ "name" ], "path": "v1/{+name}:cancel" }, "create": { "parameterOrder": [ "parent" ], "parameters": { "parent": { "type": "string", "required": true, "description": "Required. The resource name of the Location to create the TrainingPipeline in. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines", "response": { "$ref": "GoogleCloudAiplatformV1TrainingPipeline" }, "path": "v1/{+parent}/trainingPipelines", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1TrainingPipeline" }, "id": "aiplatform.projects.locations.trainingPipelines.create", "httpMethod": "POST", "description": "Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run." }, "delete": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}", "parameterOrder": [ "name" ], "httpMethod": "DELETE", "path": "v1/{+name}", "id": "aiplatform.projects.locations.trainingPipelines.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a TrainingPipeline.", "parameters": { "name": { "description": "Required. The name of the TrainingPipeline resource to be deleted. Format: `projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$", "required": true, "type": "string", "location": "path" } } } }, "resources": { "operations": { "methods": { "list": { "id": "aiplatform.projects.locations.trainingPipelines.operations.list", "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "type": "string", "required": true, "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+$" }, "pageSize": { "format": "int32", "description": "The standard list page size.", "location": "query", "type": "integer" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." } }, "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "path": "v1/{+name}/operations", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.trainingPipelines.operations.get", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", "required": true, "type": "string", "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.", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.trainingPipelines.operations.delete", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "path": "v1/{+name}", "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`." }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.trainingPipelines.operations.cancel", "path": "v1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/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`." }, "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": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}:wait", "parameters": { "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/trainingPipelines/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.trainingPipelines.operations.wait", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "onlineEvaluators": { "methods": { "list": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators", "httpMethod": "GET", "description": "Lists the OnlineEvaluators for the given project and location.", "response": { "$ref": "GoogleCloudAiplatformV1ListOnlineEvaluatorsResponse" }, "parameterOrder": [ "parent" ], "parameters": { "parent": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "description": "Required. The parent resource of the OnlineEvaluators to list. Format: projects/{project}/locations/{location}." }, "filter": { "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.", "type": "string", "location": "query" }, "pageSize": { "description": "Optional. The maximum number of OnlineEvaluators to return. The service may return fewer than this value. If unspecified, at most 100 OnlineEvaluators will be returned. The maximum value is 100; values above 100 will be coerced to 100. Based on aip.dev/158.", "location": "query", "type": "integer", "format": "int32" }, "orderBy": { "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", "type": "string" }, "pageToken": { "description": "Optional. A token identifying a page of results the server should return. Based on aip.dev/158.", "type": "string", "location": "query" } }, "path": "v1/{+parent}/onlineEvaluators", "id": "aiplatform.projects.locations.onlineEvaluators.list", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "create": { "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "description": "Required. The parent resource where the OnlineEvaluator will be created. Format: projects/{project}/locations/{location}.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+parent}/onlineEvaluators", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "description": "Creates an OnlineEvaluator in the given project and location.", "id": "aiplatform.projects.locations.onlineEvaluators.create", "request": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluator" } }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}", "description": "Deletes an OnlineEvaluator.", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.onlineEvaluators.delete", "path": "v1/{+name}", "parameterOrder": [ "name" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+$", "required": true, "description": "Required. The name of the OnlineEvaluator to delete. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}.", "location": "path", "type": "string" } } }, "get": { "httpMethod": "GET", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.onlineEvaluators.get", "description": "Gets details of an OnlineEvaluator.", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluator" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The name of the OnlineEvaluator to retrieve. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}." } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}" }, "activate": { "httpMethod": "POST", "path": "v1/{+name}:activate", "description": "Activates an OnlineEvaluator.", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+$", "type": "string", "location": "path", "description": "Required. The name of the OnlineEvaluator to activate. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}." } }, "id": "aiplatform.projects.locations.onlineEvaluators.activate", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1ActivateOnlineEvaluatorRequest" }, "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}:activate" }, "patch": { "id": "aiplatform.projects.locations.onlineEvaluators.patch", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "PATCH", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}", "parameters": { "name": { "description": "Identifier. The resource name of the OnlineEvaluator. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+$", "required": true }, "updateMask": { "location": "query", "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", "format": "google-fieldmask" } }, "description": "Updates the fields of an OnlineEvaluator.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1OnlineEvaluator" } }, "suspend": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.onlineEvaluators.suspend", "description": "Suspends an OnlineEvaluator. When an OnlineEvaluator is suspended, it won't run any evaluations until it is activated again.", "request": { "$ref": "GoogleCloudAiplatformV1SuspendOnlineEvaluatorRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}:suspend", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+$", "type": "string", "location": "path", "description": "Required. The name of the OnlineEvaluator to suspend. Format: projects/{project}/locations/{location}/onlineEvaluators/{id}.", "required": true } }, "path": "v1/{+name}:suspend", "response": { "$ref": "GoogleLongrunningOperation" } } }, "resources": { "operations": { "methods": { "get": { "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+/operations/[^/]+$", "required": true } }, "path": "v1/{+name}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.onlineEvaluators.operations.get", "parameterOrder": [ "name" ] }, "list": { "path": "v1/{+name}/operations", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}/operations", "parameterOrder": [ "name" ], "parameters": { "pageSize": { "description": "The standard list page size.", "type": "integer", "format": "int32", "location": "query" }, "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/[^/]+/onlineEvaluators/[^/]+$", "required": true }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.projects.locations.onlineEvaluators.operations.list", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}:cancel", "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "POST", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+/operations/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "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`.", "id": "aiplatform.projects.locations.onlineEvaluators.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+/operations/[^/]+$", "type": "string", "location": "path" } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "id": "aiplatform.projects.locations.onlineEvaluators.operations.delete", "response": { "$ref": "GoogleProtobufEmpty" } }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/onlineEvaluators/{onlineEvaluatorsId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "id": "aiplatform.projects.locations.onlineEvaluators.operations.wait", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/onlineEvaluators/[^/]+/operations/[^/]+$", "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" ], "path": "v1/{+name}:wait" } } } } }, "notebookRuntimeTemplates": { "methods": { "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.", "parameters": { "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "required": true, "location": "path", "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "type": "string" }, "options.requestedPolicyVersion": { "location": "query", "format": "int32", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "type": "integer" } }, "path": "v1/{+resource}:getIamPolicy", "response": { "$ref": "GoogleIamV1Policy" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:getIamPolicy", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "resource" ], "id": "aiplatform.projects.locations.notebookRuntimeTemplates.getIamPolicy", "httpMethod": "POST" }, "get": { "description": "Gets a NotebookRuntimeTemplate.", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "description": "Required. The name of the NotebookRuntimeTemplate resource. Format: `projects/{project}/locations/{location}/notebookRuntimeTemplates/{notebook_runtime_template}`", "required": true, "type": "string", "location": "path" } }, "response": { "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplate" }, "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.get", "parameterOrder": [ "name" ] }, "testIamPermissions": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "path": "v1/{+resource}:testIamPermissions", "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.testIamPermissions", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:testIamPermissions", "parameterOrder": [ "resource" ], "parameters": { "resource": { "type": "string", "required": true, "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "location": "path" }, "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" } } }, "create": { "parameters": { "notebookRuntimeTemplateId": { "location": "query", "description": "Optional. User specified ID for the notebook runtime template.", "type": "string" }, "parent": { "required": true, "type": "string", "description": "Required. The resource name of the Location to create the NotebookRuntimeTemplate. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$" } }, "request": { "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplate" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates", "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.notebookRuntimeTemplates.create", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+parent}/notebookRuntimeTemplates", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a NotebookRuntimeTemplate." }, "delete": { "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", "parameters": { "name": { "location": "path", "description": "Required. The name of the NotebookRuntimeTemplate resource to be deleted. Format: `projects/{project}/locations/{location}/notebookRuntimeTemplates/{notebook_runtime_template}`", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "description": "Deletes a NotebookRuntimeTemplate.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.notebookRuntimeTemplates.delete" }, "patch": { "response": { "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplate" }, "httpMethod": "PATCH", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.patch", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}", "request": { "$ref": "GoogleCloudAiplatformV1NotebookRuntimeTemplate" }, "parameterOrder": [ "name" ], "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates a NotebookRuntimeTemplate.", "parameters": { "updateMask": { "type": "string", "location": "query", "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Input format: `{paths: \"${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`", "format": "google-fieldmask" }, "name": { "required": true, "description": "The resource name of the NotebookRuntimeTemplate.", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "location": "path", "type": "string" } } }, "list": { "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/notebookRuntimeTemplates", "httpMethod": "GET", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.list", "response": { "$ref": "GoogleCloudAiplatformV1ListNotebookRuntimeTemplatesResponse" }, "description": "Lists NotebookRuntimeTemplates in a Location.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates", "parameters": { "parent": { "type": "string", "location": "path", "description": "Required. The resource name of the Location from which to list the NotebookRuntimeTemplates. Format: `projects/{project}/locations/{location}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$" }, "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: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", "type": "string", "location": "query" }, "filter": { "type": "string", "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`", "location": "query" }, "pageToken": { "description": "Optional. The standard list page token. Typically obtained via ListNotebookRuntimeTemplatesResponse.next_page_token of the previous NotebookService.ListNotebookRuntimeTemplates call.", "location": "query", "type": "string" }, "readMask": { "description": "Optional. Mask specifying which fields to read.", "type": "string", "format": "google-fieldmask", "location": "query" }, "pageSize": { "format": "int32", "location": "query", "type": "integer", "description": "Optional. The standard list page size." } } }, "setIamPolicy": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}:setIamPolicy", "response": { "$ref": "GoogleIamV1Policy" }, "httpMethod": "POST", "path": "v1/{+resource}:setIamPolicy", "parameters": { "resource": { "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", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$" } }, "parameterOrder": [ "resource" ], "id": "aiplatform.projects.locations.notebookRuntimeTemplates.setIamPolicy", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "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." } }, "resources": { "operations": { "methods": { "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.list", "parameters": { "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "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" }, "pageSize": { "format": "int32", "location": "query", "description": "The standard list page size.", "type": "integer" }, "name": { "required": true, "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+$", "location": "path", "type": "string" } }, "parameterOrder": [ "name" ], "path": "v1/{+name}/operations", "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "get": { "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource.", "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$" } }, "path": "v1/{+name}", "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}", "path": "v1/{+name}", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.delete", "httpMethod": "DELETE", "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`." }, "cancel": { "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`.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string" } }, "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.cancel", "httpMethod": "POST" }, "wait": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimeTemplates/{notebookRuntimeTemplatesId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimeTemplates/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "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.", "format": "google-duration", "type": "string" } }, "id": "aiplatform.projects.locations.notebookRuntimeTemplates.operations.wait", "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "httpMethod": "POST", "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." } } } } }, "notebookRuntimes": { "resources": { "operations": { "methods": { "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.projects.locations.notebookRuntimes.operations.list", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations", "parameters": { "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "type": "string", "required": true }, "pageSize": { "location": "query", "format": "int32", "type": "integer", "description": "The standard list page size." }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "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" } }, "path": "v1/{+name}/operations", "httpMethod": "GET", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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`." }, "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}", "path": "v1/{+name}", "id": "aiplatform.projects.locations.notebookRuntimes.operations.delete", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "location": "path" } }, "httpMethod": "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`.", "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.", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.notebookRuntimes.operations.get", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}", "path": "v1/{+name}", "httpMethod": "GET" }, "cancel": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "httpMethod": "POST", "id": "aiplatform.projects.locations.notebookRuntimes.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "required": true } }, "path": "v1/{+name}:cancel", "parameterOrder": [ "name" ] }, "wait": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "httpMethod": "POST", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to wait on.", "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" } }, "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.", "id": "aiplatform.projects.locations.notebookRuntimes.operations.wait", "path": "v1/{+name}:wait" } } } }, "methods": { "assign": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "httpMethod": "POST", "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.", "parameters": { "parent": { "description": "Required. The resource name of the Location to get the NotebookRuntime assignment. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string", "location": "path" } }, "path": "v1/{+parent}/notebookRuntimes:assign", "id": "aiplatform.projects.locations.notebookRuntimes.assign", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes:assign", "request": { "$ref": "GoogleCloudAiplatformV1AssignNotebookRuntimeRequest" } }, "delete": { "parameterOrder": [ "name" ], "path": "v1/{+name}", "description": "Deletes a NotebookRuntime.", "id": "aiplatform.projects.locations.notebookRuntimes.delete", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "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.", "required": true, "type": "string" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "upgrade": { "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "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.", "required": true, "type": "string" } }, "request": { "$ref": "GoogleCloudAiplatformV1UpgradeNotebookRuntimeRequest" }, "parameterOrder": [ "name" ], "description": "Upgrades a NotebookRuntime.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:upgrade", "path": "v1/{+name}:upgrade", "id": "aiplatform.projects.locations.notebookRuntimes.upgrade", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST" }, "get": { "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.notebookRuntimes.get", "response": { "$ref": "GoogleCloudAiplatformV1NotebookRuntime" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}", "parameters": { "name": { "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "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." } }, "description": "Gets a NotebookRuntime." }, "stop": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:stop", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.notebookRuntimes.stop", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:stop", "parameterOrder": [ "name" ], "description": "Stops a NotebookRuntime.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$", "location": "path", "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.", "required": true } }, "request": { "$ref": "GoogleCloudAiplatformV1StopNotebookRuntimeRequest" } }, "start": { "parameters": { "name": { "location": "path", "type": "string", "description": "Required. The name of the NotebookRuntime resource to be started. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/notebookRuntimes/[^/]+$" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.notebookRuntimes.start", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes/{notebookRuntimesId}:start", "parameterOrder": [ "name" ], "description": "Starts a NotebookRuntime.", "request": { "$ref": "GoogleCloudAiplatformV1StartNotebookRuntimeRequest" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:start", "httpMethod": "POST" }, "list": { "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1ListNotebookRuntimesResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/notebookRuntimes", "httpMethod": "GET", "path": "v1/{+parent}/notebookRuntimes", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists NotebookRuntimes in a Location.", "parameters": { "pageToken": { "type": "string", "description": "Optional. The standard list page token. Typically obtained via ListNotebookRuntimesResponse.next_page_token of the previous NotebookService.ListNotebookRuntimes call.", "location": "query" }, "readMask": { "description": "Optional. Mask specifying which fields to read.", "location": "query", "format": "google-fieldmask", "type": "string" }, "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. * `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`" }, "parent": { "location": "path", "type": "string", "description": "Required. The resource name of the Location from which to list the NotebookRuntimes. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "pageSize": { "description": "Optional. The standard list page size.", "type": "integer", "location": "query", "format": "int32" }, "orderBy": { "location": "query", "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`." } }, "id": "aiplatform.projects.locations.notebookRuntimes.list" } } }, "models": { "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", "required": true, "location": "path", "type": "string", "description": "The name of the operation resource to be deleted." } }, "id": "aiplatform.projects.locations.models.operations.delete", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "path": "v1/{+name}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" } }, "list": { "path": "v1/{+name}/operations", "id": "aiplatform.projects.locations.models.operations.list", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations", "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "name": { "description": "The name of the operation's parent resource.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "location": "path" }, "pageSize": { "format": "int32", "description": "The standard list page size.", "type": "integer", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean", "location": "query" } }, "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "httpMethod": "GET", "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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.models.operations.cancel", "httpMethod": "POST", "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`.", "path": "v1/{+name}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path", "required": true } } }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameterOrder": [ "name" ], "httpMethod": "GET", "parameters": { "name": { "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", "description": "The name of the operation resource." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.models.operations.get", "path": "v1/{+name}" }, "wait": { "httpMethod": "POST", "id": "aiplatform.projects.locations.models.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "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.", "format": "google-duration", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "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." } } }, "evaluations": { "resources": { "slices": { "methods": { "batchImport": { "description": "Imports a list of externally generated EvaluatedAnnotations.", "response": { "$ref": "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsResponse" }, "path": "v1/{+parent}:batchImport", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices/{slicesId}:batchImport", "parameters": { "parent": { "type": "string", "location": "path", "description": "Required. The name of the parent ModelEvaluationSlice resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice}`", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/slices/[^/]+$", "required": true } }, "id": "aiplatform.projects.locations.models.evaluations.slices.batchImport", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1BatchImportEvaluatedAnnotationsRequest" }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "httpMethod": "GET", "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.models.evaluations.slices.list", "description": "Lists ModelEvaluationSlices in a ModelEvaluation.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices", "response": { "$ref": "GoogleCloudAiplatformV1ListModelEvaluationSlicesResponse" }, "path": "v1/{+parent}/slices", "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" }, "readMask": { "location": "query", "type": "string", "format": "google-fieldmask", "description": "Mask specifying which fields to read." }, "pageSize": { "type": "integer", "format": "int32", "location": "query", "description": "The standard list page size." }, "parent": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$", "description": "Required. The resource name of the ModelEvaluation to list the ModelEvaluationSlices from. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`", "location": "path" }, "filter": { "location": "query", "description": "The standard list filter. * `slice.dimension` - for =.", "type": "string" } } }, "get": { "id": "aiplatform.projects.locations.models.evaluations.slices.get", "httpMethod": "GET", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a ModelEvaluationSlice.", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/slices/{slicesId}", "response": { "$ref": "GoogleCloudAiplatformV1ModelEvaluationSlice" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/slices/[^/]+$", "required": true, "location": "path", "type": "string", "description": "Required. The name of the ModelEvaluationSlice resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice}`" } } } } }, "operations": { "methods": { "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}", "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": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.models.evaluations.operations.delete", "httpMethod": "DELETE" }, "cancel": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "location": "path", "required": true } }, "id": "aiplatform.projects.locations.models.evaluations.operations.cancel", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "httpMethod": "POST", "path": "v1/{+name}:cancel", "parameterOrder": [ "name" ] }, "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.projects.locations.models.evaluations.operations.list", "path": "v1/{+name}/operations", "parameters": { "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.", "type": "boolean", "location": "query" }, "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "format": "int32", "location": "query", "description": "The standard list page size.", "type": "integer" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." } }, "httpMethod": "GET", "parameterOrder": [ "name" ] }, "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "location": "path" }, "timeout": { "location": "query", "type": "string", "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." } }, "id": "aiplatform.projects.locations.models.evaluations.operations.wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:wait", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "path": "v1/{+name}:wait" }, "get": { "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "location": "path" } }, "path": "v1/{+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.", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.models.evaluations.operations.get", "response": { "$ref": "GoogleLongrunningOperation" } } } } }, "methods": { "list": { "path": "v1/{+parent}/evaluations", "httpMethod": "GET", "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1ListModelEvaluationsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.models.evaluations.list", "description": "Lists ModelEvaluations in a Model.", "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "parent": { "description": "Required. The resource name of the Model to list the ModelEvaluations from. Format: `projects/{project}/locations/{location}/models/{model}`", "type": "string", "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$" }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token. Typically obtained via ListModelEvaluationsResponse.next_page_token of the previous ModelService.ListModelEvaluations call." }, "readMask": { "location": "query", "description": "Mask specifying which fields to read.", "type": "string", "format": "google-fieldmask" } } }, "get": { "description": "Gets a ModelEvaluation.", "httpMethod": "GET", "id": "aiplatform.projects.locations.models.evaluations.get", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations/{evaluationsId}", "parameterOrder": [ "name" ], "path": "v1/{+name}", "response": { "$ref": "GoogleCloudAiplatformV1ModelEvaluation" }, "parameters": { "name": { "description": "Required. The name of the ModelEvaluation resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+/evaluations/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "import": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}/evaluations:import", "response": { "$ref": "GoogleCloudAiplatformV1ModelEvaluation" }, "path": "v1/{+parent}/evaluations:import", "description": "Imports an externally generated ModelEvaluation.", "request": { "$ref": "GoogleCloudAiplatformV1ImportModelEvaluationRequest" }, "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "parameters": { "parent": { "description": "Required. The name of the parent model resource. Format: `projects/{project}/locations/{location}/models/{model}`", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "location": "path" } }, "id": "aiplatform.projects.locations.models.evaluations.import" } } } }, "methods": { "deleteVersion": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:deleteVersion", "httpMethod": "DELETE", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.models.deleteVersion", "description": "Deletes a Model version. Model version can only be deleted if there are no DeployedModels created from it. Deleting the only version in the Model is not allowed. Use DeleteModel for deleting the Model instead.", "path": "v1/{+name}:deleteVersion", "parameters": { "name": { "type": "string", "description": "Required. The name of the model version to be deleted, with a version ID explicitly included. Example: `projects/{project}/locations/{location}/models/{model}@1234`", "location": "path", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$" } } }, "upload": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/models:upload", "request": { "$ref": "GoogleCloudAiplatformV1UploadModelRequest" }, "parameters": { "parent": { "description": "Required. The resource name of the Location into which to upload the Model. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models:upload", "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "description": "Uploads a Model artifact into Vertex AI.", "id": "aiplatform.projects.locations.models.upload" }, "list": { "path": "v1/{+parent}/models", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "id": "aiplatform.projects.locations.models.list", "description": "Lists Models in a Location.", "response": { "$ref": "GoogleCloudAiplatformV1ListModelsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models", "parameterOrder": [ "parent" ], "parameters": { "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location to list the Models from. Format: `projects/{project}/locations/{location}`", "type": "string", "location": "path" }, "pageToken": { "location": "query", "description": "The standard list page token. Typically obtained via ListModelsResponse.next_page_token of the previous ModelService.ListModels call.", "type": "string" }, "filter": { "location": "query", "type": "string", "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `model` supports = and !=. `model` represents the Model ID, i.e. the last segment of the Model's resource name. * `display_name` supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. * `base_model_name` only supports = Some examples: * `model=1234` * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"` * `baseModelName=\"text-bison\"`" }, "orderBy": { "location": "query", "type": "string", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`." }, "readMask": { "description": "Mask specifying which fields to read.", "type": "string", "location": "query", "format": "google-fieldmask" }, "pageSize": { "location": "query", "type": "integer", "description": "The standard list page size.", "format": "int32" } } }, "export": { "parameters": { "name": { "description": "Required. The resource name of the Model to export. The resource name may contain version id or version alias to specify the version, if no version is specified, the default version will be exported.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "type": "string", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.models.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": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:export", "path": "v1/{+name}:export", "request": { "$ref": "GoogleCloudAiplatformV1ExportModelRequest" }, "httpMethod": "POST" }, "listVersions": { "parameters": { "name": { "location": "path", "type": "string", "description": "Required. The name of the model to list versions for.", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token. Typically obtained via next_page_token of the previous ListModelVersions call." }, "filter": { "type": "string", "location": "query", "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `labels.myKey=\"myValue\"`" }, "orderBy": { "location": "query", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `create_time` * `update_time` Example: `update_time asc, create_time desc`.", "type": "string" }, "readMask": { "type": "string", "location": "query", "description": "Mask specifying which fields to read.", "format": "google-fieldmask" }, "pageSize": { "location": "query", "type": "integer", "format": "int32", "description": "The standard list page size." } }, "description": "Lists versions of the specified model.", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:listVersions", "response": { "$ref": "GoogleCloudAiplatformV1ListModelVersionsResponse" }, "path": "v1/{+name}:listVersions", "id": "aiplatform.projects.locations.models.listVersions", "httpMethod": "GET" }, "mergeVersionAliases": { "request": { "$ref": "GoogleCloudAiplatformV1MergeVersionAliasesRequest" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:mergeVersionAliases", "httpMethod": "POST", "response": { "$ref": "GoogleCloudAiplatformV1Model" }, "parameters": { "name": { "type": "string", "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`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "location": "path" } }, "id": "aiplatform.projects.locations.models.mergeVersionAliases", "path": "v1/{+name}:mergeVersionAliases", "parameterOrder": [ "name" ], "description": "Merges a set of aliases for a Model version." }, "getIamPolicy": { "httpMethod": "POST", "path": "v1/{+resource}:getIamPolicy", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "id": "aiplatform.projects.locations.models.getIamPolicy", "parameterOrder": [ "resource" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:getIamPolicy", "parameters": { "resource": { "type": "string", "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "location": "path" }, "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" } }, "response": { "$ref": "GoogleIamV1Policy" } }, "listCheckpoints": { "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:listCheckpoints", "response": { "$ref": "GoogleCloudAiplatformV1ListModelVersionCheckpointsResponse" }, "parameters": { "pageSize": { "location": "query", "format": "int32", "type": "integer", "description": "Optional. The standard list page size." }, "name": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "description": "Required. The name of the model version to list checkpoints for. `projects/{project}/locations/{location}/models/{model}@{version}` Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` If no version ID or alias is specified, the latest version will be used.", "required": true }, "pageToken": { "description": "Optional. The standard list page token. Typically obtained via next_page_token of the previous ListModelVersionCheckpoints call.", "location": "query", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists checkpoints of the specified model version.", "path": "v1/{+name}:listCheckpoints", "httpMethod": "GET", "id": "aiplatform.projects.locations.models.listCheckpoints" }, "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a Model.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}", "response": { "$ref": "GoogleCloudAiplatformV1Model" }, "parameters": { "name": { "location": "path", "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.", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "type": "string", "required": true } }, "id": "aiplatform.projects.locations.models.get", "httpMethod": "GET", "parameterOrder": [ "name" ], "path": "v1/{+name}" }, "patch": { "description": "Updates a Model.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.models.patch", "parameters": { "updateMask": { "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask.", "type": "string", "location": "query", "format": "google-fieldmask" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "description": "Identifier. The resource name of the Model.", "required": true, "location": "path", "type": "string" } }, "request": { "$ref": "GoogleCloudAiplatformV1Model" }, "response": { "$ref": "GoogleCloudAiplatformV1Model" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}", "httpMethod": "PATCH" }, "setIamPolicy": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "resource" ], "path": "v1/{+resource}:setIamPolicy", "response": { "$ref": "GoogleIamV1Policy" }, "id": "aiplatform.projects.locations.models.setIamPolicy", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:setIamPolicy", "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "parameters": { "resource": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "required": true, "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field." } } }, "updateExplanationDataset": { "parameterOrder": [ "model" ], "parameters": { "model": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$", "description": "Required. The resource name of the Model to update. Format: `projects/{project}/locations/{location}/models/{model}`", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:updateExplanationDataset", "description": "Incrementally update the dataset used for an examples model.", "response": { "$ref": "GoogleLongrunningOperation" }, "request": { "$ref": "GoogleCloudAiplatformV1UpdateExplanationDatasetRequest" }, "httpMethod": "POST", "id": "aiplatform.projects.locations.models.updateExplanationDataset", "path": "v1/{+model}:updateExplanationDataset" }, "copy": { "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models:copy", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.models.copy", "request": { "$ref": "GoogleCloudAiplatformV1CopyModelRequest" }, "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.", "path": "v1/{+parent}/models:copy", "parameters": { "parent": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "description": "Required. The resource name of the Location into which to copy the Model. Format: `projects/{project}/locations/{location}`" } } }, "testIamPermissions": { "id": "aiplatform.projects.locations.models.testIamPermissions", "parameters": { "resource": { "type": "string", "location": "path", "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$" }, "permissions": { "repeated": true, "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).", "type": "string" } }, "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}:testIamPermissions", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+resource}:testIamPermissions", "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "parameterOrder": [ "resource" ], "httpMethod": "POST" }, "delete": { "id": "aiplatform.projects.locations.models.delete", "parameters": { "name": { "description": "Required. The name of the Model resource to be deleted. Format: `projects/{project}/locations/{location}/models/{model}`", "type": "string", "required": true, "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/models/[^/]+$" } }, "parameterOrder": [ "name" ], "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.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}" } } }, "specialistPools": { "resources": { "operations": { "methods": { "cancel": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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`.", "id": "aiplatform.projects.locations.specialistPools.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}:cancel", "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ] }, "wait": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to wait on.", "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "type": "string", "format": "google-duration" } }, "path": "v1/{+name}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "httpMethod": "POST", "id": "aiplatform.projects.locations.specialistPools.operations.wait", "parameterOrder": [ "name" ] }, "delete": { "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.specialistPools.operations.delete", "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", "required": true } }, "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`.", "path": "v1/{+name}", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE" }, "get": { "parameterOrder": [ "name" ], "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "id": "aiplatform.projects.locations.specialistPools.operations.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.", "parameters": { "name": { "description": "The name of the operation resource.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+/operations/[^/]+$", "type": "string", "location": "path" } } }, "list": { "parameters": { "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageSize": { "type": "integer", "format": "int32", "location": "query", "description": "The standard list page size." }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", "description": "The name of the operation's parent resource.", "required": true, "type": "string", "location": "path" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.specialistPools.operations.list", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}/operations", "httpMethod": "GET", "parameterOrder": [ "name" ] } } } }, "methods": { "get": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a SpecialistPool.", "httpMethod": "GET", "path": "v1/{+name}", "parameters": { "name": { "description": "Required. The name of the SpecialistPool resource. The form is `projects/{project}/locations/{location}/specialistPools/{specialist_pool}`.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", "location": "path", "type": "string" } }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}", "id": "aiplatform.projects.locations.specialistPools.get", "response": { "$ref": "GoogleCloudAiplatformV1SpecialistPool" } }, "create": { "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.specialistPools.create", "parameters": { "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "description": "Required. The parent Project name for the new SpecialistPool. The form is `projects/{project}/locations/{location}`.", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools", "request": { "$ref": "GoogleCloudAiplatformV1SpecialistPool" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a SpecialistPool.", "path": "v1/{+parent}/specialistPools", "parameterOrder": [ "parent" ], "httpMethod": "POST" }, "delete": { "httpMethod": "DELETE", "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", "location": "path", "description": "Required. The resource name of the SpecialistPool to delete. Format: `projects/{project}/locations/{location}/specialistPools/{specialist_pool}`" }, "force": { "location": "query", "description": "If set to true, any specialist managers in this SpecialistPool will also be deleted. (Otherwise, the request will only work if the SpecialistPool has no specialist managers.)", "type": "boolean" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}", "path": "v1/{+name}", "id": "aiplatform.projects.locations.specialistPools.delete", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "description": "Deletes a SpecialistPool as well as all Specialists in the pool.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.specialistPools.patch", "description": "Updates a SpecialistPool.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools/{specialistPoolsId}", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "PATCH", "parameters": { "name": { "type": "string", "required": true, "description": "Required. The resource name of the SpecialistPool.", "pattern": "^projects/[^/]+/locations/[^/]+/specialistPools/[^/]+$", "location": "path" }, "updateMask": { "location": "query", "description": "Required. The update mask applies to the resource.", "type": "string", "format": "google-fieldmask" } }, "request": { "$ref": "GoogleCloudAiplatformV1SpecialistPool" } }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "readMask": { "description": "Mask specifying which fields to read. FieldMask represents a set of", "format": "google-fieldmask", "location": "query", "type": "string" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token. Typically obtained by ListSpecialistPoolsResponse.next_page_token of the previous SpecialistPoolService.ListSpecialistPools call. Return first page if empty." }, "pageSize": { "format": "int32", "location": "query", "description": "The standard list page size.", "type": "integer" }, "parent": { "required": true, "type": "string", "description": "Required. The name of the SpecialistPool's parent resource. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/specialistPools", "response": { "$ref": "GoogleCloudAiplatformV1ListSpecialistPoolsResponse" }, "path": "v1/{+parent}/specialistPools", "description": "Lists SpecialistPools in a Location.", "id": "aiplatform.projects.locations.specialistPools.list", "parameterOrder": [ "parent" ], "httpMethod": "GET" } } }, "featureOnlineStores": { "resources": { "featureViews": { "methods": { "directWrite": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "featureView": { "required": true, "type": "string", "description": "FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "location": "path" } }, "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.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:directWrite", "httpMethod": "POST", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.directWrite", "parameterOrder": [ "featureView" ], "request": { "$ref": "GoogleCloudAiplatformV1FeatureViewDirectWriteRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1FeatureViewDirectWriteResponse" }, "path": "v1/{+featureView}:directWrite" }, "searchNearestEntities": { "httpMethod": "POST", "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.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.searchNearestEntities", "parameterOrder": [ "featureView" ], "response": { "$ref": "GoogleCloudAiplatformV1SearchNearestEntitiesResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:searchNearestEntities", "path": "v1/{+featureView}:searchNearestEntities", "request": { "$ref": "GoogleCloudAiplatformV1SearchNearestEntitiesRequest" }, "parameters": { "featureView": { "description": "Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true } } }, "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "path": "v1/{+parent}/featureViews", "response": { "$ref": "GoogleCloudAiplatformV1ListFeatureViewsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews", "description": "Lists FeatureViews in a given FeatureOnlineStore.", "parameters": { "pageSize": { "type": "integer", "location": "query", "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.", "format": "int32" }, "pageToken": { "type": "string", "location": "query", "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." }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "location": "path", "type": "string", "description": "Required. The resource name of the FeatureOnlineStore to list FeatureViews. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}`", "required": true }, "orderBy": { "type": "string", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `feature_view_id` * `create_time` * `update_time`", "location": "query" }, "filter": { "description": "Lists the FeatureViews that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\" OR update_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e FeatureViews created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --\u003e FeatureViews having both (active: yes) and (env: prod) labels. * `labels.env: *` --\u003e Any FeatureView which has a label with 'env' as the key.", "location": "query", "type": "string" } }, "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.list", "parameterOrder": [ "parent" ] }, "get": { "httpMethod": "GET", "path": "v1/{+name}", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.get", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "location": "path", "type": "string", "required": true, "description": "Required. The name of the FeatureView resource. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`" } }, "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}", "response": { "$ref": "GoogleCloudAiplatformV1FeatureView" }, "description": "Gets details of a single FeatureView." }, "testIamPermissions": { "parameterOrder": [ "resource" ], "path": "v1/{+resource}:testIamPermissions", "httpMethod": "POST", "response": { "$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.", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.testIamPermissions", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:testIamPermissions", "parameters": { "resource": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "description": "REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "required": true }, "permissions": { "repeated": true, "location": "query", "type": "string", "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions)." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "sync": { "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.sync", "httpMethod": "POST", "parameterOrder": [ "featureView" ], "path": "v1/{+featureView}:sync", "description": "Triggers on-demand sync for the FeatureView.", "parameters": { "featureView": { "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "required": true, "description": "Required. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", "type": "string", "location": "path" } }, "request": { "$ref": "GoogleCloudAiplatformV1SyncFeatureViewRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1SyncFeatureViewResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:sync" }, "patch": { "request": { "$ref": "GoogleCloudAiplatformV1FeatureView" }, "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.patch", "parameters": { "name": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "location": "path", "description": "Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`" }, "updateMask": { "type": "string", "format": "google-fieldmask", "location": "query", "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`" } }, "description": "Updates the parameters of a single FeatureView.", "httpMethod": "PATCH", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "getIamPolicy": { "path": "v1/{+resource}:getIamPolicy", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:getIamPolicy", "response": { "$ref": "GoogleIamV1Policy" }, "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.getIamPolicy", "parameters": { "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.", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "type": "string", "required": true }, "options.requestedPolicyVersion": { "location": "query", "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "format": "int32", "type": "integer" } }, "httpMethod": "POST", "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "parameterOrder": [ "resource" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "setIamPolicy": { "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.setIamPolicy", "path": "v1/{+resource}:setIamPolicy", "httpMethod": "POST", "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "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" ], "parameterOrder": [ "resource" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:setIamPolicy", "response": { "$ref": "GoogleIamV1Policy" }, "parameters": { "resource": { "type": "string", "required": true, "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$" } } }, "generateFetchAccessToken": { "parameters": { "featureView": { "description": "FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "location": "path" } }, "response": { "$ref": "GoogleCloudAiplatformV1GenerateFetchAccessTokenResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:generateFetchAccessToken", "description": "RPC to generate an access token for the given feature view. FeatureViews under the same FeatureOnlineStore share the same access token.", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.generateFetchAccessToken", "parameterOrder": [ "featureView" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1GenerateFetchAccessTokenRequest" }, "path": "v1/{+featureView}:generateFetchAccessToken" }, "create": { "parameters": { "runSyncImmediately": { "location": "query", "description": "Immutable. If set to true, one on demand sync will be run immediately, regardless whether the FeatureView.sync_config is configured or not.", "type": "boolean" }, "parent": { "description": "Required. The resource name of the FeatureOnlineStore to create FeatureViews. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}`", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "location": "path", "type": "string", "required": true }, "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.", "type": "string", "location": "query" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "GoogleCloudAiplatformV1FeatureView" }, "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.create", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/featureViews", "description": "Creates a new FeatureView in a given FeatureOnlineStore.", "httpMethod": "POST" }, "delete": { "description": "Deletes a single FeatureView.", "parameters": { "name": { "location": "path", "type": "string", "description": "Required. The name of the FeatureView to be deleted. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "DELETE", "path": "v1/{+name}" }, "fetchFeatureValues": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}:fetchFeatureValues", "request": { "$ref": "GoogleCloudAiplatformV1FetchFeatureValuesRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1FetchFeatureValuesResponse" }, "description": "Fetch feature values under a FeatureView.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.fetchFeatureValues", "parameters": { "featureView": { "required": true, "description": "Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$" } }, "parameterOrder": [ "featureView" ], "path": "v1/{+featureView}:fetchFeatureValues", "httpMethod": "POST" } }, "resources": { "featureViewSyncs": { "methods": { "list": { "parameters": { "filter": { "description": "Lists the FeatureViewSyncs that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `\u003c`, `\u003e`, `\u003e=`, and `\u003c=` comparisons. Values must be in RFC 3339 format. Examples: * `create_time \u003e \\\"2020-01-31T15:30:00.000000Z\\\"` --\u003e FeatureViewSyncs created after 2020-01-31T15:30:00.000000Z.", "type": "string", "location": "query" }, "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+$", "type": "string", "location": "path", "description": "Required. The resource name of the FeatureView to list FeatureViewSyncs. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`" }, "pageSize": { "location": "query", "type": "integer", "format": "int32", "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." }, "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`", "location": "query", "type": "string" }, "pageToken": { "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.", "type": "string" } }, "path": "v1/{+parent}/featureViewSyncs", "response": { "$ref": "GoogleCloudAiplatformV1ListFeatureViewSyncsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/featureViewSyncs", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.featureViewSyncs.list", "description": "Lists FeatureViewSyncs in a given FeatureView.", "parameterOrder": [ "parent" ], "httpMethod": "GET" }, "get": { "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/featureViewSyncs/[^/]+$", "description": "Required. The name of the FeatureViewSync resource. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1FeatureViewSync" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/featureViewSyncs/{featureViewSyncsId}", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.featureViewSyncs.get", "description": "Gets details of a single FeatureViewSync.", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "operations": { "methods": { "get": { "httpMethod": "GET", "parameterOrder": [ "name" ], "path": "v1/{+name}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.get", "parameters": { "name": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource." } } }, "wait": { "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.wait", "path": "v1/{+name}:wait", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "required": true }, "timeout": { "format": "google-duration", "location": "query", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." }, "listWait": { "parameters": { "name": { "description": "The name of the operation's parent resource.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "location": "path" }, "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.", "type": "boolean", "location": "query" }, "pageSize": { "format": "int32", "type": "integer", "location": "query", "description": "The standard list page size." }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.listWait", "httpMethod": "GET", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}:wait" }, "delete": { "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/featureViews/{featureViewsId}/operations/{operationsId}", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featureOnlineStores.featureViews.operations.delete", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/featureViews/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." } } } } }, "operations": { "methods": { "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "httpMethod": "POST", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.featureOnlineStores.operations.wait", "path": "v1/{+name}:wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource to wait on.", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration", "type": "string", "location": "query" } } }, "listWait": { "parameterOrder": [ "name" ], "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featureOnlineStores.operations.listWait", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "name": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation's parent resource." }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "pageSize": { "description": "The standard list page size.", "location": "query", "type": "integer", "format": "int32" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" } }, "path": "v1/{+name}:wait" }, "get": { "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "required": true } }, "id": "aiplatform.projects.locations.featureOnlineStores.operations.get", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "httpMethod": "GET", "parameterOrder": [ "name" ] }, "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+/operations/[^/]+$" } }, "path": "v1/{+name}", "id": "aiplatform.projects.locations.featureOnlineStores.operations.delete", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." } } } }, "methods": { "getIamPolicy": { "parameters": { "options.requestedPolicyVersion": { "description": "Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).", "type": "integer", "location": "query", "format": "int32" }, "resource": { "location": "path", "type": "string", "required": true, "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$" } }, "response": { "$ref": "GoogleIamV1Policy" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}:getIamPolicy", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.", "parameterOrder": [ "resource" ], "id": "aiplatform.projects.locations.featureOnlineStores.getIamPolicy", "httpMethod": "POST", "path": "v1/{+resource}:getIamPolicy" }, "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}", "response": { "$ref": "GoogleCloudAiplatformV1FeatureOnlineStore" }, "parameters": { "name": { "description": "Required. The name of the FeatureOnlineStore resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "required": true } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "description": "Gets details of a single FeatureOnlineStore.", "id": "aiplatform.projects.locations.featureOnlineStores.get", "httpMethod": "GET" }, "create": { "path": "v1/{+parent}/featureOnlineStores", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores", "id": "aiplatform.projects.locations.featureOnlineStores.create", "httpMethod": "POST", "parameterOrder": [ "parent" ], "description": "Creates a new FeatureOnlineStore in a given project and location.", "parameters": { "featureOnlineStoreId": { "type": "string", "location": "query", "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." }, "parent": { "location": "path", "description": "Required. The resource name of the Location to create FeatureOnlineStores. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1FeatureOnlineStore" } }, "delete": { "id": "aiplatform.projects.locations.featureOnlineStores.delete", "parameters": { "force": { "location": "query", "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.)", "type": "boolean" }, "name": { "type": "string", "required": true, "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/[^/]+$" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "description": "Deletes a single FeatureOnlineStore. The FeatureOnlineStore must not contain any FeatureViews.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE" }, "list": { "parameters": { "pageToken": { "location": "query", "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.", "type": "string" }, "filter": { "type": "string", "location": "query", "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\"." }, "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: * `create_time` * `update_time`", "type": "string" }, "parent": { "type": "string", "description": "Required. The resource name of the Location to list FeatureOnlineStores. Format: `projects/{project}/locations/{location}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path" }, "pageSize": { "format": "int32", "description": "The maximum number of FeatureOnlineStores to return. The service may return fewer than this value. If unspecified, at most 100 FeatureOnlineStores will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100.", "type": "integer", "location": "query" } }, "path": "v1/{+parent}/featureOnlineStores", "id": "aiplatform.projects.locations.featureOnlineStores.list", "description": "Lists FeatureOnlineStores in a given project and location.", "response": { "$ref": "GoogleCloudAiplatformV1ListFeatureOnlineStoresResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "parameterOrder": [ "parent" ] }, "patch": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}", "response": { "$ref": "GoogleLongrunningOperation" }, "request": { "$ref": "GoogleCloudAiplatformV1FeatureOnlineStore" }, "parameters": { "updateMask": { "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", "format": "google-fieldmask", "location": "query" }, "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "type": "string", "location": "path", "description": "Identifier. Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`" } }, "path": "v1/{+name}", "httpMethod": "PATCH", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featureOnlineStores.patch", "description": "Updates the parameters of a single FeatureOnlineStore.", "parameterOrder": [ "name" ] }, "testIamPermissions": { "id": "aiplatform.projects.locations.featureOnlineStores.testIamPermissions", "parameterOrder": [ "resource" ], "httpMethod": "POST", "path": "v1/{+resource}:testIamPermissions", "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "permissions": { "location": "query", "type": "string", "description": "The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).", "repeated": true }, "resource": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "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.", "required": true, "type": "string" } }, "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}:testIamPermissions" }, "setIamPolicy": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/featureOnlineStores/{featureOnlineStoresId}:setIamPolicy", "path": "v1/{+resource}:setIamPolicy", "response": { "$ref": "GoogleIamV1Policy" }, "parameters": { "resource": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/featureOnlineStores/[^/]+$", "description": "REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "required": true } }, "parameterOrder": [ "resource" ], "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.featureOnlineStores.setIamPolicy", "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "httpMethod": "POST" } } }, "batchPredictionJobs": { "methods": { "list": { "id": "aiplatform.projects.locations.batchPredictionJobs.list", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs", "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1ListBatchPredictionJobsResponse" }, "parameters": { "pageToken": { "location": "query", "type": "string", "description": "The standard list page token. Typically obtained via ListBatchPredictionJobsResponse.next_page_token of the previous JobService.ListBatchPredictionJobs call." }, "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "format": "google-fieldmask", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `model_display_name` supports `=`, `!=` comparisons. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`" }, "parent": { "required": true, "description": "Required. The resource name of the Location to list the BatchPredictionJobs from. Format: `projects/{project}/locations/{location}`", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path" }, "pageSize": { "location": "query", "description": "The standard list page size.", "type": "integer", "format": "int32" } }, "description": "Lists BatchPredictionJobs in a Location.", "httpMethod": "GET", "path": "v1/{+parent}/batchPredictionJobs", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "create": { "response": { "$ref": "GoogleCloudAiplatformV1BatchPredictionJob" }, "path": "v1/{+parent}/batchPredictionJobs", "request": { "$ref": "GoogleCloudAiplatformV1BatchPredictionJob" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs", "parameterOrder": [ "parent" ], "parameters": { "parent": { "description": "Required. The resource name of the Location to create the BatchPredictionJob in. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "description": "Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start.", "id": "aiplatform.projects.locations.batchPredictionJobs.create", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", "description": "Required. The name of the BatchPredictionJob resource to be deleted. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`", "type": "string", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}", "httpMethod": "DELETE", "id": "aiplatform.projects.locations.batchPredictionJobs.delete", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a BatchPredictionJob. Can only be called on jobs that already finished." }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Cancels a BatchPredictionJob. Starts asynchronous cancellation on the BatchPredictionJob. The server makes the best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetBatchPredictionJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On a successful cancellation, the BatchPredictionJob is not deleted;instead its BatchPredictionJob.state is set to `CANCELLED`. Any files already outputted by the job are not deleted.", "path": "v1/{+name}:cancel", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.batchPredictionJobs.cancel", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1CancelBatchPredictionJobRequest" }, "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", "required": true, "type": "string", "description": "Required. The name of the BatchPredictionJob to cancel. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" } }, "get": { "httpMethod": "GET", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/batchPredictionJobs/[^/]+$", "required": true, "description": "Required. The name of the BatchPredictionJob resource. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}`", "type": "string" } }, "description": "Gets a BatchPredictionJob", "id": "aiplatform.projects.locations.batchPredictionJobs.get", "response": { "$ref": "GoogleCloudAiplatformV1BatchPredictionJob" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/batchPredictionJobs/{batchPredictionJobsId}" } } }, "modelDeploymentMonitoringJobs": { "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.delete", "response": { "$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`.", "parameterOrder": [ "name" ], "httpMethod": "DELETE" }, "list": { "path": "v1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.list", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameters": { "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "pageSize": { "location": "query", "format": "int32", "description": "The standard list page size.", "type": "integer" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "required": true }, "filter": { "description": "The standard list filter.", "type": "string", "location": "query" } } }, "cancel": { "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.cancel", "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be cancelled.", "required": true, "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "timeout": { "format": "google-duration", "type": "string", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." }, "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "location": "path", "type": "string" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST" }, "get": { "httpMethod": "GET", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.operations.get", "path": "v1/{+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.", "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation resource.", "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+/operations/[^/]+$", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" } } } } }, "methods": { "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "location": "path", "description": "Required. The parent of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}`", "type": "string" }, "pageSize": { "format": "int32", "location": "query", "type": "integer", "description": "The standard list page size." }, "filter": { "location": "query", "description": "The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`\u003c`, `\u003c=`,`\u003e`, `\u003e=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state=\"JOB_STATE_SUCCEEDED\" AND display_name:\"my_job_*\"` * `state!=\"JOB_STATE_FAILED\" OR display_name=\"my_job\"` * `NOT display_name=\"my_job\"` * `create_time\u003e\"2021-05-18T00:00:00Z\"` * `labels.keyA=valueA` * `labels.keyB:*`", "type": "string" }, "readMask": { "description": "Mask specifying which fields to read", "location": "query", "type": "string", "format": "google-fieldmask" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "httpMethod": "GET", "response": { "$ref": "GoogleCloudAiplatformV1ListModelDeploymentMonitoringJobsResponse" }, "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.list", "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs", "description": "Lists ModelDeploymentMonitoringJobs in a Location.", "path": "v1/{+parent}/modelDeploymentMonitoringJobs" }, "create": { "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob" }, "description": "Creates a ModelDeploymentMonitoringJob. It will run periodically on a configured interval.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs", "httpMethod": "POST", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.create", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "type": "string", "required": true, "description": "Required. The parent of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}`" } }, "path": "v1/{+parent}/modelDeploymentMonitoringJobs", "request": { "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob" } }, "delete": { "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "path": "v1/{+name}", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.delete", "description": "Deletes a ModelDeploymentMonitoringJob.", "parameters": { "name": { "description": "Required. The resource name of the model monitoring job to delete. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "type": "string", "required": true } } }, "searchModelDeploymentMonitoringStatsAnomalies": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:searchModelDeploymentMonitoringStatsAnomalies", "response": { "$ref": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesResponse" }, "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1SearchModelDeploymentMonitoringStatsAnomaliesRequest" }, "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.searchModelDeploymentMonitoringStatsAnomalies", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+modelDeploymentMonitoringJob}:searchModelDeploymentMonitoringStatsAnomalies", "description": "Searches Model Monitoring Statistics generated within a given time window.", "parameterOrder": [ "modelDeploymentMonitoringJob" ], "parameters": { "modelDeploymentMonitoringJob": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "location": "path", "description": "Required. ModelDeploymentMonitoring Job resource name. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`" } } }, "resume": { "path": "v1/{+name}:resume", "httpMethod": "POST", "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.resume", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:resume", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "request": { "$ref": "GoogleCloudAiplatformV1ResumeModelDeploymentMonitoringJobRequest" }, "parameters": { "name": { "required": true, "description": "Required. The resource name of the ModelDeploymentMonitoringJob to resume. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "location": "path", "type": "string" } }, "description": "Resumes a paused ModelDeploymentMonitoringJob. It will start to run from next scheduled time. A deleted ModelDeploymentMonitoringJob can't be resumed.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "description": "Gets a ModelDeploymentMonitoringJob.", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.get", "httpMethod": "GET", "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The resource name of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "required": true } }, "response": { "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob" } }, "pause": { "path": "v1/{+name}:pause", "request": { "$ref": "GoogleCloudAiplatformV1PauseModelDeploymentMonitoringJobRequest" }, "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.pause", "parameterOrder": [ "name" ], "httpMethod": "POST", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "type": "string", "description": "Required. The resource name of the ModelDeploymentMonitoringJob to pause. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`", "location": "path" } }, "description": "Pauses a ModelDeploymentMonitoringJob. If the job is running, the server makes a best effort to cancel the job. Will mark ModelDeploymentMonitoringJob.state to 'PAUSED'.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}:pause", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" } }, "patch": { "id": "aiplatform.projects.locations.modelDeploymentMonitoringJobs.patch", "request": { "$ref": "GoogleCloudAiplatformV1ModelDeploymentMonitoringJob" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/modelDeploymentMonitoringJobs/{modelDeploymentMonitoringJobsId}", "httpMethod": "PATCH", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "parameters": { "name": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/modelDeploymentMonitoringJobs/[^/]+$", "description": "Output only. Resource name of a ModelDeploymentMonitoringJob.", "location": "path" }, "updateMask": { "type": "string", "description": "Required. The update mask is used to specify the fields to be overwritten in the ModelDeploymentMonitoringJob resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. For the objective config, the user can either provide the update mask for model_deployment_monitoring_objective_configs or any combination of its nested fields, such as: model_deployment_monitoring_objective_configs.objective_config.training_dataset. Updatable fields: * `display_name` * `model_deployment_monitoring_schedule_config` * `model_monitoring_alert_config` * `logging_sampling_strategy` * `labels` * `log_ttl` * `enable_monitoring_pipeline_logs` . and * `model_deployment_monitoring_objective_configs` . or * `model_deployment_monitoring_objective_configs.objective_config.training_dataset` * `model_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_config` * `model_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config`", "location": "query", "format": "google-fieldmask" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Updates a ModelDeploymentMonitoringJob." } } }, "studies": { "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", "required": true } }, "id": "aiplatform.projects.locations.studies.operations.delete", "parameterOrder": [ "name" ], "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." }, "wait": { "id": "aiplatform.projects.locations.studies.operations.wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "parameterOrder": [ "name" ], "path": "v1/{+name}:wait", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "type": "string" }, "timeout": { "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}:cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", "location": "path" } }, "parameterOrder": [ "name" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.studies.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel" }, "list": { "id": "aiplatform.projects.locations.studies.operations.list", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "pageSize": { "format": "int32", "location": "query", "type": "integer", "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.", "type": "boolean", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "filter": { "description": "The standard list filter.", "type": "string", "location": "query" }, "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "description": "The name of the operation's parent resource.", "type": "string", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations", "path": "v1/{+name}/operations" }, "get": { "id": "aiplatform.projects.locations.studies.operations.get", "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/operations/{operationsId}", "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.", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/operations/[^/]+$", "required": true } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] } } }, "trials": { "methods": { "complete": { "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:complete", "description": "Marks a Trial as complete.", "response": { "$ref": "GoogleCloudAiplatformV1Trial" }, "request": { "$ref": "GoogleCloudAiplatformV1CompleteTrialRequest" }, "parameterOrder": [ "name" ], "path": "v1/{+name}:complete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "type": "string", "required": true } }, "id": "aiplatform.projects.locations.studies.trials.complete" }, "suggest": { "path": "v1/{+parent}/trials:suggest", "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.", "parameters": { "parent": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "description": "Required. The project and location that the Study belongs to. Format: `projects/{project}/locations/{location}/studies/{study}`", "location": "path" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials:suggest", "parameterOrder": [ "parent" ], "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1SuggestTrialsRequest" }, "id": "aiplatform.projects.locations.studies.trials.suggest" }, "stop": { "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", "required": true, "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.studies.trials.stop", "request": { "$ref": "GoogleCloudAiplatformV1StopTrialRequest" }, "path": "v1/{+name}:stop", "description": "Stops a Trial.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:stop", "httpMethod": "POST", "response": { "$ref": "GoogleCloudAiplatformV1Trial" }, "parameterOrder": [ "name" ] }, "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials", "description": "Adds a user provided Trial to a Study.", "response": { "$ref": "GoogleCloudAiplatformV1Trial" }, "path": "v1/{+parent}/trials", "id": "aiplatform.projects.locations.studies.trials.create", "parameterOrder": [ "parent" ], "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1Trial" }, "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "description": "Required. The resource name of the Study to create the Trial in. Format: `projects/{project}/locations/{location}/studies/{study}`", "type": "string", "required": true } } }, "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}", "id": "aiplatform.projects.locations.studies.trials.delete", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "required": true, "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a Trial.", "httpMethod": "DELETE" }, "get": { "parameterOrder": [ "name" ], "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}", "path": "v1/{+name}", "response": { "$ref": "GoogleCloudAiplatformV1Trial" }, "id": "aiplatform.projects.locations.studies.trials.get", "description": "Gets a Trial.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "description": "Required. The name of the Trial resource. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", "location": "path", "type": "string", "required": true } } }, "addTrialMeasurement": { "description": "Adds a measurement of the objective metrics to a Trial. This measurement is assumed to have been taken before the Trial is complete.", "path": "v1/{+trialName}:addTrialMeasurement", "id": "aiplatform.projects.locations.studies.trials.addTrialMeasurement", "parameterOrder": [ "trialName" ], "parameters": { "trialName": { "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "location": "path", "type": "string", "description": "Required. The name of the trial to add measurement. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1Trial" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:addTrialMeasurement", "request": { "$ref": "GoogleCloudAiplatformV1AddTrialMeasurementRequest" } }, "listOptimalTrials": { "parameters": { "parent": { "description": "Required. The name of the Study that the optimal Trial belongs to.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "location": "path" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials:listOptimalTrials", "response": { "$ref": "GoogleCloudAiplatformV1ListOptimalTrialsResponse" }, "parameterOrder": [ "parent" ], "path": "v1/{+parent}/trials:listOptimalTrials", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1ListOptimalTrialsRequest" }, "description": "Lists the pareto-optimal Trials for multi-objective Study or the optimal Trials for single-objective Study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency", "httpMethod": "POST", "id": "aiplatform.projects.locations.studies.trials.listOptimalTrials" }, "checkTrialEarlyStoppingState": { "id": "aiplatform.projects.locations.studies.trials.checkTrialEarlyStoppingState", "parameterOrder": [ "trialName" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1CheckTrialEarlyStoppingStateRequest" }, "description": "Checks whether a Trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}:checkTrialEarlyStoppingState", "parameters": { "trialName": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$", "required": true, "description": "Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}`" } }, "path": "v1/{+trialName}:checkTrialEarlyStoppingState" }, "list": { "path": "v1/{+parent}/trials", "id": "aiplatform.projects.locations.studies.trials.list", "parameters": { "pageSize": { "description": "Optional. The number of Trials to retrieve per \"page\" of results. If unspecified, the service will pick an appropriate default.", "format": "int32", "location": "query", "type": "integer" }, "pageToken": { "description": "Optional. A page token to request the next page of results. If unspecified, there are no subsequent pages.", "type": "string", "location": "query" }, "parent": { "type": "string", "description": "Required. The resource name of the Study to list the Trial from. Format: `projects/{project}/locations/{location}/studies/{study}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "required": true } }, "httpMethod": "GET", "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists the Trials associated with a Study.", "response": { "$ref": "GoogleCloudAiplatformV1ListTrialsResponse" } } }, "resources": { "operations": { "methods": { "cancel": { "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "path": "v1/{+name}:cancel", "parameters": { "name": { "type": "string", "location": "path", "required": true, "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$" } }, "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`.", "id": "aiplatform.projects.locations.studies.trials.operations.cancel" }, "list": { "path": "v1/{+name}/operations", "id": "aiplatform.projects.locations.studies.trials.operations.list", "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "parameters": { "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "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.", "type": "boolean", "location": "query" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "description": "The standard list page size.", "format": "int32", "location": "query", "type": "integer" }, "name": { "required": true, "type": "string", "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+$" } }, "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.studies.trials.operations.delete", "httpMethod": "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`.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}" }, "wait": { "parameters": { "timeout": { "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.", "location": "query", "type": "string" }, "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "type": "string" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/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.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.studies.trials.operations.wait", "httpMethod": "POST", "parameterOrder": [ "name" ], "path": "v1/{+name}:wait" }, "get": { "httpMethod": "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": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.studies.trials.operations.get", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+/trials/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "type": "string", "required": true } } } } } } } }, "methods": { "list": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists all the studies in a region for an associated project.", "path": "v1/{+parent}/studies", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies", "response": { "$ref": "GoogleCloudAiplatformV1ListStudiesResponse" }, "parameters": { "pageSize": { "format": "int32", "type": "integer", "location": "query", "description": "Optional. The maximum number of studies to return per \"page\" of results. If unspecified, service will pick an appropriate default." }, "parent": { "location": "path", "description": "Required. The resource name of the Location to list the Study from. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" }, "pageToken": { "location": "query", "type": "string", "description": "Optional. A page token to request the next page of results. If unspecified, there are no subsequent pages." } }, "parameterOrder": [ "parent" ], "httpMethod": "GET", "id": "aiplatform.projects.locations.studies.list" }, "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}", "response": { "$ref": "GoogleCloudAiplatformV1Study" }, "httpMethod": "GET", "path": "v1/{+name}", "parameterOrder": [ "name" ], "description": "Gets a Study by name.", "parameters": { "name": { "description": "Required. The name of the Study resource. Format: `projects/{project}/locations/{location}/studies/{study}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$", "type": "string", "required": true } }, "id": "aiplatform.projects.locations.studies.get", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "create": { "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1Study" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "description": "Required. The resource name of the Location to create the CustomJob in. Format: `projects/{project}/locations/{location}`" } }, "response": { "$ref": "GoogleCloudAiplatformV1Study" }, "id": "aiplatform.projects.locations.studies.create", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies", "path": "v1/{+parent}/studies", "parameterOrder": [ "parent" ], "description": "Creates a Study. A resource name will be generated after creation of the Study." }, "delete": { "httpMethod": "DELETE", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.studies.delete", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies/{studiesId}", "description": "Deletes a Study.", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "description": "Required. The name of the Study resource to be deleted. Format: `projects/{project}/locations/{location}/studies/{study}`", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/studies/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "lookup": { "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1LookupStudyRequest" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.studies.lookup", "description": "Looks a study up using the user-defined display_name field instead of the fully qualified resource name.", "response": { "$ref": "GoogleCloudAiplatformV1Study" }, "parameterOrder": [ "parent" ], "path": "v1/{+parent}/studies:lookup", "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "description": "Required. The resource name of the Location to get the Study from. Format: `projects/{project}/locations/{location}`", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/studies:lookup" } } }, "evaluationRuns": { "methods": { "cancel": { "request": { "$ref": "GoogleCloudAiplatformV1CancelEvaluationRunRequest" }, "parameterOrder": [ "name" ], "httpMethod": "POST", "path": "v1/{+name}:cancel", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/evaluationRuns/[^/]+$", "required": true, "location": "path", "type": "string", "description": "Required. The name of the EvaluationRun resource to be cancelled. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}`" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationRuns/{evaluationRunsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Cancels an Evaluation Run. Attempts to cancel a running Evaluation Run asynchronously. Status of run can be checked via GetEvaluationRun.", "id": "aiplatform.projects.locations.evaluationRuns.cancel" }, "get": { "description": "Gets an Evaluation Run.", "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationRuns/[^/]+$", "type": "string", "description": "Required. The name of the EvaluationRun resource. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}`", "required": true } }, "path": "v1/{+name}", "id": "aiplatform.projects.locations.evaluationRuns.get", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1EvaluationRun" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationRuns/{evaluationRunsId}" }, "create": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationRuns", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/evaluationRuns", "response": { "$ref": "GoogleCloudAiplatformV1EvaluationRun" }, "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1EvaluationRun" }, "parameterOrder": [ "parent" ], "id": "aiplatform.projects.locations.evaluationRuns.create", "description": "Creates an Evaluation Run.", "parameters": { "parent": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location to create the Evaluation Run in. Format: `projects/{project}/locations/{location}`", "type": "string", "location": "path" } } }, "delete": { "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationRuns/{evaluationRunsId}", "parameters": { "name": { "description": "Required. The name of the EvaluationRun resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}`", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationRuns/[^/]+$", "required": true } }, "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes an Evaluation Run.", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.evaluationRuns.delete" }, "list": { "parameterOrder": [ "parent" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationRuns", "httpMethod": "GET", "id": "aiplatform.projects.locations.evaluationRuns.list", "response": { "$ref": "GoogleCloudAiplatformV1ListEvaluationRunsResponse" }, "path": "v1/{+parent}/evaluationRuns", "description": "Lists Evaluation Runs.", "parameters": { "pageSize": { "location": "query", "type": "integer", "description": "Optional. The maximum number of Evaluation Runs to return.", "format": "int32" }, "pageToken": { "type": "string", "description": "Optional. A page token, received from a previous `ListEvaluationRuns` call. Provide this to retrieve the subsequent page.", "location": "query" }, "parent": { "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "description": "Required. The resource name of the Location from which to list the Evaluation Runs. Format: `projects/{project}/locations/{location}`", "required": true, "type": "string" }, "orderBy": { "location": "query", "type": "string", "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." }, "filter": { "location": "query", "type": "string", "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)." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "evaluationItems": { "methods": { "create": { "id": "aiplatform.projects.locations.evaluationItems.create", "request": { "$ref": "GoogleCloudAiplatformV1EvaluationItem" }, "description": "Creates an Evaluation Item.", "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationItems", "path": "v1/{+parent}/evaluationItems", "parameters": { "parent": { "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location to create the Evaluation Item in. Format: `projects/{project}/locations/{location}`" } }, "response": { "$ref": "GoogleCloudAiplatformV1EvaluationItem" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ] }, "delete": { "httpMethod": "DELETE", "path": "v1/{+name}", "description": "Deletes an Evaluation Item.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationItems/{evaluationItemsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.evaluationItems.delete", "parameters": { "name": { "required": true, "description": "Required. The name of the EvaluationItem resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}`", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationItems/[^/]+$", "type": "string", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] }, "list": { "description": "Lists Evaluation Items.", "id": "aiplatform.projects.locations.evaluationItems.list", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/evaluationItems", "response": { "$ref": "GoogleCloudAiplatformV1ListEvaluationItemsResponse" }, "parameters": { "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": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location from which to list the Evaluation Items. Format: `projects/{project}/locations/{location}`", "required": true }, "orderBy": { "type": "string", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending.", "location": "query" }, "pageToken": { "type": "string", "description": "Optional. A page token, received from a previous `ListEvaluationItems` call. Provide this to retrieve the subsequent page.", "location": "query" }, "pageSize": { "type": "integer", "description": "Optional. The maximum number of Evaluation Items to return.", "location": "query", "format": "int32" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationItems", "parameterOrder": [ "parent" ] }, "get": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/evaluationItems/{evaluationItemsId}", "httpMethod": "GET", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1EvaluationItem" }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "Required. The name of the EvaluationItem resource. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}`", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/evaluationItems/[^/]+$", "location": "path" } }, "id": "aiplatform.projects.locations.evaluationItems.get", "description": "Gets an Evaluation Item." } } }, "deploymentResourcePools": { "methods": { "patch": { "description": "Update a DeploymentResourcePool.", "request": { "$ref": "GoogleCloudAiplatformV1DeploymentResourcePool" }, "parameterOrder": [ "name" ], "path": "v1/{+name}", "parameters": { "name": { "location": "path", "description": "Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", "type": "string", "required": true }, "updateMask": { "format": "google-fieldmask", "description": "Required. The list of fields to update.", "type": "string", "location": "query" } }, "id": "aiplatform.projects.locations.deploymentResourcePools.patch", "httpMethod": "PATCH", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" } }, "queryDeployedModels": { "response": { "$ref": "GoogleCloudAiplatformV1QueryDeployedModelsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}:queryDeployedModels", "httpMethod": "GET", "description": "List DeployedModels that have been deployed on this DeploymentResourcePool.", "parameterOrder": [ "deploymentResourcePool" ], "id": "aiplatform.projects.locations.deploymentResourcePools.queryDeployedModels", "parameters": { "deploymentResourcePool": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", "location": "path", "description": "Required. The name of the target DeploymentResourcePool to query. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`" }, "pageSize": { "description": "The maximum number of DeployedModels to return. The service may return fewer than this value.", "format": "int32", "location": "query", "type": "integer" }, "pageToken": { "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.", "location": "query", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+deploymentResourcePool}:queryDeployedModels" }, "create": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools", "response": { "$ref": "GoogleLongrunningOperation" }, "request": { "$ref": "GoogleCloudAiplatformV1CreateDeploymentResourcePoolRequest" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.deploymentResourcePools.create", "parameters": { "parent": { "type": "string", "location": "path", "description": "Required. The parent location resource where this DeploymentResourcePool will be created. Format: `projects/{project}/locations/{location}`", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true } }, "description": "Create a DeploymentResourcePool.", "parameterOrder": [ "parent" ], "path": "v1/{+parent}/deploymentResourcePools" }, "delete": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Delete a DeploymentResourcePool.", "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the DeploymentResourcePool to delete. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "httpMethod": "DELETE", "id": "aiplatform.projects.locations.deploymentResourcePools.delete", "path": "v1/{+name}" }, "list": { "id": "aiplatform.projects.locations.deploymentResourcePools.list", "path": "v1/{+parent}/deploymentResourcePools", "description": "List DeploymentResourcePools in a location.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools", "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1ListDeploymentResourcePoolsResponse" }, "parameters": { "parent": { "required": true, "type": "string", "description": "Required. The parent Location which owns this collection of DeploymentResourcePools. Format: `projects/{project}/locations/{location}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$" }, "pageToken": { "location": "query", "description": "A page token, received from a previous `ListDeploymentResourcePools` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `ListDeploymentResourcePools` must match the call that provided the page token.", "type": "string" }, "pageSize": { "description": "The maximum number of DeploymentResourcePools to return. The service may return fewer than this value.", "type": "integer", "format": "int32", "location": "query" } }, "httpMethod": "GET" }, "get": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", "required": true, "description": "Required. The name of the DeploymentResourcePool to retrieve. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`", "type": "string", "location": "path" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.deploymentResourcePools.get", "response": { "$ref": "GoogleCloudAiplatformV1DeploymentResourcePool" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}", "description": "Get a DeploymentResourcePool.", "path": "v1/{+name}", "httpMethod": "GET" } }, "resources": { "operations": { "methods": { "wait": { "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:wait", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to wait on.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "format": "google-duration", "location": "query" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.deploymentResourcePools.operations.wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "path": "v1/{+name}:wait" }, "get": { "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "type": "string", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.deploymentResourcePools.operations.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.", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}", "httpMethod": "GET" }, "list": { "path": "v1/{+name}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+$", "type": "string", "required": true, "description": "The name of the operation's parent resource." }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "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" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "pageSize": { "type": "integer", "format": "int32", "description": "The standard list page size.", "location": "query" } }, "id": "aiplatform.projects.locations.deploymentResourcePools.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations", "parameterOrder": [ "name" ] }, "cancel": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}:cancel", "httpMethod": "POST", "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.projects.locations.deploymentResourcePools.operations.cancel", "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "required": true, "type": "string", "location": "path" } }, "parameterOrder": [ "name" ] }, "delete": { "parameterOrder": [ "name" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/deploymentResourcePools/[^/]+/operations/[^/]+$", "type": "string", "required": true, "location": "path", "description": "The name of the operation resource to be deleted." } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/deploymentResourcePools/{deploymentResourcePoolsId}/operations/{operationsId}", "id": "aiplatform.projects.locations.deploymentResourcePools.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": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "DELETE" } } } } }, "endpoints": { "resources": { "deployedModels": { "resources": { "invoke": { "methods": { "invoke": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "id": "aiplatform.projects.locations.endpoints.deployedModels.invoke.invoke", "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request.", "request": { "$ref": "GoogleCloudAiplatformV1InvokeRequest" }, "path": "v1/{+endpoint}/deployedModels/{deployedModelId}/invoke/{+invokeId}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/deployedModels/{deployedModelId}/invoke/{invokeId}", "parameters": { "deployedModelId": { "type": "string", "description": "ID of the DeployedModel that serves the invoke request.", "required": true, "location": "path" }, "endpoint": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" }, "invokeId": { "required": true, "type": "string", "location": "path" } }, "response": { "$ref": "GoogleApiHttpBody" }, "parameterOrder": [ "endpoint", "deployedModelId", "invokeId" ] } } } } }, "responses": { "methods": { "get": { "response": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/responses/{responsesId}", "parameters": { "name": { "description": "Required. The name of the Response resource. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}/responses/{response}`", "location": "path", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/responses/[^/]+$" } }, "description": "Gets the response from the endpoint.", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "httpMethod": "GET", "id": "aiplatform.projects.locations.endpoints.responses.get", "path": "v1/{+name}" }, "delete": { "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "description": "Deletes the response from the endpoint.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleApiHttpBody" }, "parameters": { "name": { "description": "Required. The name of the Response resource to be deleted. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}/responses/{response}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/responses/[^/]+$", "type": "string", "required": true } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/responses/{responsesId}", "path": "v1/{+name}", "id": "aiplatform.projects.locations.endpoints.responses.delete" } } }, "chat": { "methods": { "completions": { "description": "Exposes an OpenAI-compatible endpoint for chat completions.", "parameterOrder": [ "endpoint" ], "parameters": { "endpoint": { "type": "string", "location": "path", "description": "Required. The name of the endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "path": "v1/{+endpoint}/chat/completions", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.chat.completions", "response": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/chat/completions", "request": { "$ref": "GoogleApiHttpBody" } } } }, "invoke": { "methods": { "invoke": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/invoke/{invokeId}", "response": { "$ref": "GoogleApiHttpBody" }, "id": "aiplatform.projects.locations.endpoints.invoke.invoke", "parameters": { "endpoint": { "type": "string", "required": true, "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/[^/]+$" }, "invokeId": { "required": true, "type": "string", "location": "path" } }, "parameterOrder": [ "endpoint", "invokeId" ], "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1InvokeRequest" }, "path": "v1/{+endpoint}/invoke/{+invokeId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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." } } }, "operations": { "methods": { "wait": { "parameters": { "timeout": { "format": "google-duration", "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" }, "name": { "description": "The name of the operation resource to wait on.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", "location": "path" } }, "id": "aiplatform.projects.locations.endpoints.operations.wait", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "response": { "$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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "parameterOrder": [ "name" ] }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}", "parameterOrder": [ "name" ], "httpMethod": "DELETE", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "required": true, "description": "The name of the operation resource to be deleted.", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", "type": "string", "location": "path" } }, "id": "aiplatform.projects.locations.endpoints.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}" }, "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`.", "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}:cancel", "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.endpoints.operations.cancel", "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$", "required": true } }, "parameterOrder": [ "name" ] }, "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "parameters": { "name": { "description": "The name of the operation resource.", "required": true, "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+/operations/[^/]+$" } }, "path": "v1/{+name}", "id": "aiplatform.projects.locations.endpoints.operations.get", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations/{operationsId}", "httpMethod": "GET", "parameterOrder": [ "name" ] }, "list": { "parameters": { "pageSize": { "location": "query", "type": "integer", "format": "int32", "description": "The standard list page size." }, "name": { "location": "path", "type": "string", "description": "The name of the operation's parent resource.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.endpoints.operations.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}/operations", "httpMethod": "GET" } } }, "google": { "resources": { "science": { "methods": { "inference": { "response": { "$ref": "GoogleApiHttpBody" }, "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request.", "id": "aiplatform.projects.locations.endpoints.google.science.inference", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/google/science/inference", "request": { "$ref": "GoogleApiHttpBody" }, "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "path": "v1/{+endpoint}/science/inference", "parameters": { "deployedModelId": { "location": "query", "type": "string", "description": "ID of the DeployedModel that serves the invoke request." }, "endpoint": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/google$", "required": true, "type": "string", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "parameterOrder": [ "endpoint" ] } } } } }, "openapi": { "methods": { "responses": { "parameterOrder": [ "endpoint" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/openapi/responses", "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.openapi.responses", "path": "v1/{+endpoint}/responses", "response": { "$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.", "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/openapi$", "type": "string", "required": true }, "deployedModelId": { "type": "string", "description": "ID of the DeployedModel that serves the invoke request.", "location": "query" } }, "request": { "$ref": "GoogleApiHttpBody" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ] }, "embeddings": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "deployedModelId": { "type": "string", "location": "query", "description": "ID of the DeployedModel that serves the invoke request." }, "endpoint": { "type": "string", "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/openapi$" } }, "description": "Forwards arbitrary HTTP requests for both streaming and non-streaming cases. To use this method, invoke_route_prefix must be set to allow the paths that will be specified in the request.", "path": "v1/{+endpoint}/embeddings", "id": "aiplatform.projects.locations.endpoints.openapi.embeddings", "parameterOrder": [ "endpoint" ], "response": { "$ref": "GoogleApiHttpBody" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/openapi/embeddings", "request": { "$ref": "GoogleApiHttpBody" } }, "completions": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/openapi/completions", "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/openapi$" }, "deployedModelId": { "location": "query", "type": "string", "description": "ID of the DeployedModel that serves the invoke request." } }, "response": { "$ref": "GoogleApiHttpBody" }, "path": "v1/{+endpoint}/completions", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "request": { "$ref": "GoogleApiHttpBody" }, "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.", "id": "aiplatform.projects.locations.endpoints.openapi.completions", "httpMethod": "POST" } } } }, "methods": { "get": { "httpMethod": "GET", "description": "Gets an Endpoint.", "parameterOrder": [ "name" ], "id": "aiplatform.projects.locations.endpoints.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "description": "Required. The name of the Endpoint resource. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "required": true } }, "response": { "$ref": "GoogleCloudAiplatformV1Endpoint" }, "path": "v1/{+name}" }, "create": { "path": "v1/{+parent}/endpoints", "parameterOrder": [ "parent" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.create", "request": { "$ref": "GoogleCloudAiplatformV1Endpoint" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "description": "Required. The resource name of the Location to create the Endpoint in. Format: `projects/{project}/locations/{location}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true }, "endpointId": { "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.", "type": "string", "location": "query" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints", "description": "Creates an Endpoint.", "response": { "$ref": "GoogleLongrunningOperation" } }, "delete": { "path": "v1/{+name}", "parameterOrder": [ "name" ], "httpMethod": "DELETE", "description": "Deletes an Endpoint.", "id": "aiplatform.projects.locations.endpoints.delete", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}", "parameters": { "name": { "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "description": "Required. The name of the Endpoint resource to be deleted. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string", "location": "path" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "httpMethod": "GET", "path": "v1/{+parent}/endpoints", "parameterOrder": [ "parent" ], "response": { "$ref": "GoogleCloudAiplatformV1ListEndpointsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints", "description": "Lists Endpoints in a Location.", "parameters": { "parent": { "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location from which to list the Endpoints. Format: `projects/{project}/locations/{location}`", "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" }, "pageToken": { "description": "Optional. The standard list page token. Typically obtained via ListEndpointsResponse.next_page_token of the previous EndpointService.ListEndpoints call.", "type": "string", "location": "query" }, "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The standard list page size." }, "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: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.", "type": "string", "location": "query" }, "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" }, "readMask": { "description": "Optional. Mask specifying which fields to read.", "location": "query", "type": "string", "format": "google-fieldmask" } }, "id": "aiplatform.projects.locations.endpoints.list" }, "rawPredict": { "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.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:rawPredict", "httpMethod": "POST", "response": { "$ref": "GoogleApiHttpBody" }, "parameterOrder": [ "endpoint" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "id": "aiplatform.projects.locations.endpoints.rawPredict", "path": "v1/{+endpoint}:rawPredict", "parameters": { "endpoint": { "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path", "required": true, "type": "string" } }, "request": { "$ref": "GoogleCloudAiplatformV1RawPredictRequest" } }, "streamRawPredict": { "httpMethod": "POST", "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1StreamRawPredictRequest" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "id": "aiplatform.projects.locations.endpoints.streamRawPredict", "path": "v1/{+endpoint}:streamRawPredict", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:streamRawPredict", "response": { "$ref": "GoogleApiHttpBody" }, "description": "Perform a streaming online prediction with an arbitrary HTTP payload.", "parameters": { "endpoint": { "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", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" } } }, "generateContent": { "parameters": { "model": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "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}`", "required": true } }, "id": "aiplatform.projects.locations.endpoints.generateContent", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" }, "description": "Generate content with multimodal inputs.", "parameterOrder": [ "model" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:generateContent", "path": "v1/{+model}:generateContent", "response": { "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" } }, "directRawPredict": { "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1DirectRawPredictRequest" }, "description": "Perform an unary online prediction request to a gRPC model server for custom containers.", "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:directRawPredict", "parameters": { "endpoint": { "type": "string", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true } }, "response": { "$ref": "GoogleCloudAiplatformV1DirectRawPredictResponse" }, "id": "aiplatform.projects.locations.endpoints.directRawPredict", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "path": "v1/{+endpoint}:directRawPredict" }, "streamGenerateContent": { "response": { "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" }, "id": "aiplatform.projects.locations.endpoints.streamGenerateContent", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:streamGenerateContent", "httpMethod": "POST", "description": "Generate content with multimodal inputs with streaming support.", "request": { "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" }, "parameterOrder": [ "model" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "path": "v1/{+model}:streamGenerateContent", "parameters": { "model": { "required": true, "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "location": "path", "type": "string" } } }, "countTokens": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.projects.locations.endpoints.countTokens", "parameterOrder": [ "endpoint" ], "parameters": { "endpoint": { "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "location": "path", "type": "string" } }, "path": "v1/{+endpoint}:countTokens", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:countTokens", "response": { "$ref": "GoogleCloudAiplatformV1CountTokensResponse" }, "request": { "$ref": "GoogleCloudAiplatformV1CountTokensRequest" }, "description": "Perform a token counting.", "httpMethod": "POST" }, "update": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:update", "request": { "$ref": "GoogleCloudAiplatformV1UpdateEndpointLongRunningRequest" }, "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "description": "Updates an Endpoint with a long running operation.", "parameterOrder": [ "name" ], "path": "v1/{+name}:update", "id": "aiplatform.projects.locations.endpoints.update", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "location": "path", "description": "Identifier. The resource name of the Endpoint.", "required": true, "type": "string" } } }, "predict": { "response": { "$ref": "GoogleCloudAiplatformV1PredictResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:predict", "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1PredictRequest" }, "id": "aiplatform.projects.locations.endpoints.predict", "parameters": { "endpoint": { "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", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "path": "v1/{+endpoint}:predict", "description": "", "parameterOrder": [ "endpoint" ] }, "explain": { "parameters": { "endpoint": { "description": "Required. The name of the Endpoint requested to serve the explanation. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "required": true, "type": "string", "location": "path" } }, "id": "aiplatform.projects.locations.endpoints.explain", "response": { "$ref": "GoogleCloudAiplatformV1ExplainResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:explain", "request": { "$ref": "GoogleCloudAiplatformV1ExplainRequest" }, "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "path": "v1/{+endpoint}:explain", "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.", "parameterOrder": [ "endpoint" ] }, "fetchPredictOperation": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "httpMethod": "POST", "path": "v1/{+endpoint}:fetchPredictOperation", "request": { "$ref": "GoogleCloudAiplatformV1FetchPredictOperationRequest" }, "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:fetchPredictOperation", "id": "aiplatform.projects.locations.endpoints.fetchPredictOperation", "description": "Fetch an asynchronous online prediction operation.", "parameters": { "endpoint": { "location": "path", "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}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" } }, "parameterOrder": [ "endpoint" ] }, "computeTokens": { "id": "aiplatform.projects.locations.endpoints.computeTokens", "httpMethod": "POST", "parameterOrder": [ "endpoint" ], "response": { "$ref": "GoogleCloudAiplatformV1ComputeTokensResponse" }, "description": "Return a list of tokens based on the input text.", "parameters": { "endpoint": { "location": "path", "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids.", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:computeTokens", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1ComputeTokensRequest" }, "path": "v1/{+endpoint}:computeTokens" }, "serverStreamingPredict": { "description": "Perform a server-side streaming online prediction request for Vertex LLM streaming.", "response": { "$ref": "GoogleCloudAiplatformV1StreamingPredictResponse" }, "httpMethod": "POST", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:serverStreamingPredict", "request": { "$ref": "GoogleCloudAiplatformV1StreamingPredictRequest" }, "path": "v1/{+endpoint}:serverStreamingPredict", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameterOrder": [ "endpoint" ], "id": "aiplatform.projects.locations.endpoints.serverStreamingPredict", "parameters": { "endpoint": { "location": "path", "type": "string", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$" } } }, "directPredict": { "description": "Perform an unary online prediction request to a gRPC model server for Vertex first-party products and frameworks.", "httpMethod": "POST", "path": "v1/{+endpoint}:directPredict", "id": "aiplatform.projects.locations.endpoints.directPredict", "parameters": { "endpoint": { "location": "path", "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`" } }, "request": { "$ref": "GoogleCloudAiplatformV1DirectPredictRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1DirectPredictResponse" }, "parameterOrder": [ "endpoint" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:directPredict" }, "predictLongRunning": { "parameterOrder": [ "endpoint" ], "httpMethod": "POST", "description": "", "id": "aiplatform.projects.locations.endpoints.predictLongRunning", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+endpoint}:predictLongRunning", "request": { "$ref": "GoogleCloudAiplatformV1PredictLongRunningRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:predictLongRunning", "parameters": { "endpoint": { "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "type": "string", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "required": true, "location": "path" } } }, "patch": { "request": { "$ref": "GoogleCloudAiplatformV1Endpoint" }, "parameters": { "name": { "required": true, "description": "Identifier. The resource name of the Endpoint.", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "type": "string", "location": "path" }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "Required. The update mask applies to the resource. See google.protobuf.FieldMask." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}", "response": { "$ref": "GoogleCloudAiplatformV1Endpoint" }, "id": "aiplatform.projects.locations.endpoints.patch", "description": "Updates an Endpoint.", "httpMethod": "PATCH", "path": "v1/{+name}" }, "deployModel": { "parameters": { "endpoint": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "description": "Required. The name of the Endpoint resource into which to deploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path" } }, "request": { "$ref": "GoogleCloudAiplatformV1DeployModelRequest" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+endpoint}:deployModel", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:deployModel", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "endpoint" ], "description": "Deploys a Model into this Endpoint, creating a DeployedModel within it.", "id": "aiplatform.projects.locations.endpoints.deployModel" }, "undeployModel": { "request": { "$ref": "GoogleCloudAiplatformV1UndeployModelRequest" }, "httpMethod": "POST", "id": "aiplatform.projects.locations.endpoints.undeployModel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:undeployModel", "parameterOrder": [ "endpoint" ], "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "endpoint": { "description": "Required. The name of the Endpoint resource from which to undeploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/endpoints/[^/]+$", "type": "string", "required": true } }, "path": "v1/{+endpoint}:undeployModel" }, "mutateDeployedModel": { "parameterOrder": [ "endpoint" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+endpoint}:mutateDeployedModel", "httpMethod": "POST", "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).", "parameters": { "endpoint": { "location": "path", "type": "string", "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/[^/]+$", "required": true } }, "request": { "$ref": "GoogleCloudAiplatformV1MutateDeployedModelRequest" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}:mutateDeployedModel", "id": "aiplatform.projects.locations.endpoints.mutateDeployedModel", "response": { "$ref": "GoogleLongrunningOperation" } } } }, "indexes": { "resources": { "operations": { "methods": { "cancel": { "path": "v1/{+name}:cancel", "id": "aiplatform.projects.locations.indexes.operations.cancel", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$" } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameterOrder": [ "name" ] }, "delete": { "parameterOrder": [ "name" ], "httpMethod": "DELETE", "path": "v1/{+name}", "response": { "$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": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}", "id": "aiplatform.projects.locations.indexes.operations.delete", "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted." } } }, "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "name": { "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation's parent resource.", "required": true }, "pageSize": { "format": "int32", "location": "query", "type": "integer", "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": { "description": "The standard list filter.", "type": "string", "location": "query" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations", "id": "aiplatform.projects.locations.indexes.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "path": "v1/{+name}/operations", "httpMethod": "GET" }, "wait": { "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}:wait", "id": "aiplatform.projects.locations.indexes.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "path": "v1/{+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.", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource to wait on.", "type": "string", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", "required": true }, "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } } }, "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "description": "The name of the operation resource.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+/operations/[^/]+$", "location": "path" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}/operations/{operationsId}", "id": "aiplatform.projects.locations.indexes.operations.get", "httpMethod": "GET", "path": "v1/{+name}" } } } }, "methods": { "list": { "path": "v1/{+parent}/indexes", "id": "aiplatform.projects.locations.indexes.list", "parameterOrder": [ "parent" ], "description": "Lists Indexes in a Location.", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "description": "Required. The resource name of the Location from which to list the Indexes. Format: `projects/{project}/locations/{location}`", "required": true, "type": "string" }, "readMask": { "format": "google-fieldmask", "type": "string", "description": "Mask specifying which fields to read.", "location": "query" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token. Typically obtained via ListIndexesResponse.next_page_token of the previous IndexService.ListIndexes call." }, "pageSize": { "location": "query", "type": "integer", "format": "int32", "description": "The standard list page size." } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes", "response": { "$ref": "GoogleCloudAiplatformV1ListIndexesResponse" } }, "get": { "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets an Index.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1Index" }, "id": "aiplatform.projects.locations.indexes.get", "parameters": { "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "location": "path", "description": "Required. The name of the Index resource. Format: `projects/{project}/locations/{location}/indexes/{index}`" } }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}", "path": "v1/{+name}" }, "create": { "path": "v1/{+parent}/indexes", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.indexes.create", "request": { "$ref": "GoogleCloudAiplatformV1Index" }, "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates an Index.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes", "parameters": { "parent": { "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "type": "string", "description": "Required. The resource name of the Location to create the Index in. Format: `projects/{project}/locations/{location}`", "required": true } }, "parameterOrder": [ "parent" ] }, "delete": { "path": "v1/{+name}", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}", "httpMethod": "DELETE", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.indexes.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The name of the Index resource to be deleted. Format: `projects/{project}/locations/{location}/indexes/{index}`", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "required": true, "type": "string" } }, "description": "Deletes an Index. An Index can only be deleted when all its DeployedIndexes had been undeployed." }, "upsertDatapoints": { "httpMethod": "POST", "parameterOrder": [ "index" ], "path": "v1/{+index}:upsertDatapoints", "parameters": { "index": { "location": "path", "description": "Required. The name of the Index resource to be updated. Format: `projects/{project}/locations/{location}/indexes/{index}`", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "type": "string", "required": true } }, "request": { "$ref": "GoogleCloudAiplatformV1UpsertDatapointsRequest" }, "id": "aiplatform.projects.locations.indexes.upsertDatapoints", "response": { "$ref": "GoogleCloudAiplatformV1UpsertDatapointsResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}:upsertDatapoints", "description": "Add/update Datapoints into an Index.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "removeDatapoints": { "path": "v1/{+index}:removeDatapoints", "httpMethod": "POST", "id": "aiplatform.projects.locations.indexes.removeDatapoints", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1RemoveDatapointsRequest" }, "parameterOrder": [ "index" ], "description": "Remove Datapoints from an Index.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}:removeDatapoints", "response": { "$ref": "GoogleCloudAiplatformV1RemoveDatapointsResponse" }, "parameters": { "index": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "description": "Required. The name of the Index resource to be updated. Format: `projects/{project}/locations/{location}/indexes/{index}`", "location": "path" } } }, "patch": { "id": "aiplatform.projects.locations.indexes.patch", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "httpMethod": "PATCH", "request": { "$ref": "GoogleCloudAiplatformV1Index" }, "path": "v1/{+name}", "description": "Updates an Index.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/indexes/{indexesId}", "parameters": { "updateMask": { "format": "google-fieldmask", "description": "The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask.", "type": "string", "location": "query" }, "name": { "type": "string", "required": true, "description": "Output only. The resource name of the Index.", "pattern": "^projects/[^/]+/locations/[^/]+/indexes/[^/]+$", "location": "path" } } } } }, "ragEngineConfig": { "resources": { "operations": { "methods": { "list": { "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations", "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" }, "pageSize": { "description": "The standard list page size.", "format": "int32", "type": "integer", "location": "query" }, "name": { "type": "string", "required": true, "description": "The name of the operation's parent resource.", "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig$", "location": "path" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." } }, "id": "aiplatform.projects.locations.ragEngineConfig.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig/operations/[^/]+$", "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "httpMethod": "DELETE", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "id": "aiplatform.projects.locations.ragEngineConfig.operations.delete" }, "cancel": { "parameters": { "name": { "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string", "required": true } }, "httpMethod": "POST", "path": "v1/{+name}:cancel", "id": "aiplatform.projects.locations.ragEngineConfig.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameterOrder": [ "name" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig/operations/{operationsId}:cancel" }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource." } }, "id": "aiplatform.projects.locations.ragEngineConfig.operations.get", "httpMethod": "GET", "path": "v1/{+name}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameterOrder": [ "name" ] }, "wait": { "parameterOrder": [ "name" ], "httpMethod": "POST", "id": "aiplatform.projects.locations.ragEngineConfig.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragEngineConfig/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.", "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/ragEngineConfig/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration", "type": "string" } } } } } } }, "agents": { "methods": { "create": { "request": { "$ref": "GoogleCloudAiplatformV1Agent" }, "path": "v1/{+parent}/agents", "parameters": { "parent": { "required": true, "description": "Required. The resource name of the location to create the agent in. Format: `projects/{project}/locations/{location}`.", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.projects.locations.agents.create", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/agents", "description": "Creates an agent.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ], "httpMethod": "POST" }, "delete": { "parameters": { "force": { "type": "boolean", "location": "query", "description": "Optional. If true, any `Task` belonging to this agent is deleted along with it. If false or unset and the agent still has at least one `Task`, the request fails with `FAILED_PRECONDITION` and nothing is deleted. This governs `Task` and nothing else. Resources the agent owns but a caller never named -- its AI Application and the tenant project bound to it, its Workspace identity, its service-extension binding -- are torn down with the agent on every delete, whatever this field says." }, "name": { "type": "string", "required": true, "description": "Required. The resource name of the agent to delete. Format: `projects/{project}/locations/{location}/agents/{agent}`.", "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+$", "location": "path" } }, "id": "aiplatform.projects.locations.agents.delete", "description": "Deletes an agent.", "parameterOrder": [ "name" ], "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "DELETE", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}" }, "get": { "description": "Retrieves an agent.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}", "response": { "$ref": "GoogleCloudAiplatformV1Agent" }, "parameters": { "name": { "type": "string", "description": "Required. The resource name of the agent to retrieve. Format: `projects/{project}/locations/{location}/agents/{agent}`.", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+$", "location": "path" } }, "httpMethod": "GET", "id": "aiplatform.projects.locations.agents.get", "path": "v1/{+name}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "httpMethod": "GET", "path": "v1/{+parent}/agents", "id": "aiplatform.projects.locations.agents.list", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/agents", "description": "Lists the agents in a location that belong to the caller. An agent belongs to the end user recorded as its owner when it was created, so the response holds that caller's agents and no others. It is empty for a caller that is not an end user, and an agent with no recorded owner is listed for nobody.", "response": { "$ref": "GoogleCloudAiplatformV1ListAgentsResponse" }, "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageSize": { "location": "query", "type": "integer", "description": "Optional. The maximum number of agents to return. The service may return fewer than this value. The maximum page size is 100; values above 100 will be coerced to 100. If unspecified, the default page size is 10.", "format": "int32" }, "pageToken": { "description": "Optional. A page token, received from a previous AgentService.ListAgents call. Provide this to retrieve the subsequent page.", "type": "string", "location": "query" }, "parent": { "description": "Required. The resource name of the location to list agents from. Format: `projects/{project}/locations/{location}`.", "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path" }, "orderBy": { "location": "query", "type": "string", "description": "Optional. A comma-separated list of fields to order by. Supported fields: * `created` * `updated` Use `desc` after a field name for descending order. Example: `created desc`." }, "filter": { "type": "string", "description": "Optional. An [AIP-160](https://google.aip.dev/160) filter over the returned agents. An empty filter returns the unfiltered collection. Supported fields, and the operators each accepts: * `created` * `updated` * `base_agent` * `metadata.agent_type` `created` and `updated` are timestamps and take an RFC-3339 value, for example `2026-08-01T00:00:00Z`. Supported operators: `=`, `!=`, `\u003c`, `\u003e`, `\u003c=`, `\u003e=`, `:`, `AND`, `OR`, `NOT` (equivalently `-`), and parentheses. Note that `OR` binds more tightly than `AND`, so `a AND b OR c` means `a AND (b OR c)`; parentheses are recommended, not required. `metadata.agent_type` accepts only the value `\"default_agent\"`, matched exactly: `metadata.agent_type:\"default_agent\"` selects the caller's default agent, of which there is at most one, and the negated form selects the rest. Any other value is `INVALID_ARGUMENT` rather than an empty page -- `metadata` is an opaque blob, so only this one marker is indexed, and the server cannot answer a question about the others. An agent designated before the server began recording the marker is not matched by the positive form; there is no backfill. `base_agent` accepts `=` and `!=` against the value an agent was created with, and selects only among the agents you own: an agent that belongs to the project rather than to a user is never returned by a filter naming it, including the negated form. An agent created before the server began recording the value is not matched either. Example: `created \u003e \"2026-08-01T00:00:00Z\" AND updated \u003c \"2026-08-09T00:00:00Z\"`. IMPORTANT -- `base_agent` and `metadata.agent_type` select only among the agents you own. An agent that belongs to the project rather than to a user is never returned by a filter naming either of them, including a negated one: `base_agent != \"some-value\"` returns your matching agents and no project-owned agents at all. Filtering on `created` or `updated` alone is unaffected and still spans both. If you want every agent in the project, do not filter on these two fields. Not supported: any field other than those listed above, wildcards other than `field:*`, bare literals with no field name, functions, and the regular-expression operators `=~` and `!~`. A filter that names an unsupported field, exceeds 1000 characters, or nests parentheses more than 5 deep fails with `INVALID_ARGUMENT`.", "location": "query" } } }, "getIamPolicy": { "parameters": { "options.requestedPolicyVersion": { "location": "query", "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).", "format": "int32" }, "resource": { "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+$", "description": "REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field.", "required": true } }, "path": "v1/{+resource}:getIamPolicy", "response": { "$ref": "GoogleIamV1Policy" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}:getIamPolicy", "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.", "httpMethod": "POST", "id": "aiplatform.projects.locations.agents.getIamPolicy" }, "setIamPolicy": { "request": { "$ref": "GoogleIamV1SetIamPolicyRequest" }, "description": "Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.", "parameters": { "resource": { "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+$", "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", "type": "string" } }, "path": "v1/{+resource}:setIamPolicy", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}:setIamPolicy", "parameterOrder": [ "resource" ], "response": { "$ref": "GoogleIamV1Policy" }, "httpMethod": "POST", "id": "aiplatform.projects.locations.agents.setIamPolicy" }, "patch": { "httpMethod": "PATCH", "parameterOrder": [ "name" ], "description": "Updates an agent.", "request": { "$ref": "GoogleCloudAiplatformV1Agent" }, "id": "aiplatform.projects.locations.agents.patch", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}", "parameters": { "updateMask": { "format": "google-fieldmask", "description": "Optional. The list of fields to update. If not present, all fields are updated.", "location": "query", "type": "string" }, "name": { "required": true, "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+$", "description": "Identifier. The resource name of the agent. Format: `projects/{project}/locations/{location}/agents/{agent}`.", "location": "path" } }, "path": "v1/{+name}" }, "testIamPermissions": { "parameters": { "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": "string", "location": "query", "repeated": true }, "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.", "type": "string", "required": true, "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+/agents/[^/]+$" } }, "path": "v1/{+resource}:testIamPermissions", "parameterOrder": [ "resource" ], "description": "Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may \"fail open\" without warning.", "id": "aiplatform.projects.locations.agents.testIamPermissions", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/agents/{agentsId}:testIamPermissions", "httpMethod": "POST", "response": { "$ref": "GoogleIamV1TestIamPermissionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } } } }, "indexes": { "resources": { "operations": { "methods": { "wait": { "parameters": { "name": { "location": "path", "type": "string", "pattern": "^indexes/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "required": true }, "timeout": { "type": "string", "format": "google-duration", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameterOrder": [ "name" ], "id": "aiplatform.indexes.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/indexes/{indexesId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait", "httpMethod": "POST" }, "get": { "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^indexes/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.indexes.operations.get", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/indexes/{indexesId}/operations/{operationsId}", "path": "v1/{+name}", "httpMethod": "GET" }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "flatPath": "v1/indexes/{indexesId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "httpMethod": "DELETE", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^indexes/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "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`.", "id": "aiplatform.indexes.operations.delete" }, "list": { "httpMethod": "GET", "path": "v1/{+name}/operations", "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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.indexes.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "description": "The name of the operation's parent resource.", "required": true, "pattern": "^indexes/[^/]+$", "location": "path" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "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" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "pageSize": { "format": "int32", "type": "integer", "description": "The standard list page size.", "location": "query" } }, "flatPath": "v1/indexes/{indexesId}/operations" }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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`.", "parameters": { "name": { "required": true, "pattern": "^indexes/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "flatPath": "v1/indexes/{indexesId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "id": "aiplatform.indexes.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}:cancel", "httpMethod": "POST" } } } } }, "operations": { "methods": { "cancel": { "id": "aiplatform.operations.cancel", "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "required": true, "pattern": "^operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "flatPath": "v1/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "httpMethod": "POST", "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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "id": "aiplatform.operations.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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`.", "parameterOrder": [], "parameters": { "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." }, "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "type": "integer", "location": "query", "description": "The standard list page size.", "format": "int32" }, "name": { "location": "query", "type": "string", "description": "The name of the operation's parent resource." } }, "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/operations", "flatPath": "v1/operations" }, "delete": { "path": "v1/{+name}", "id": "aiplatform.operations.delete", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1/operations/{operationsId}", "parameters": { "name": { "type": "string", "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^operations/[^/]+$", "required": true } }, "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "parameterOrder": [ "name" ] }, "wait": { "path": "v1/{+name}:wait", "httpMethod": "POST", "id": "aiplatform.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "flatPath": "v1/operations/{operationsId}:wait", "response": { "$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.", "parameters": { "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.", "format": "google-duration", "location": "query" }, "name": { "location": "path", "pattern": "^operations/[^/]+$", "description": "The name of the operation resource to wait on.", "required": true, "type": "string" } } }, "get": { "parameterOrder": [ "name" ], "path": "v1/{+name}", "id": "aiplatform.operations.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "type": "string", "location": "path", "description": "The name of the operation resource.", "pattern": "^operations/[^/]+$" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "GET", "flatPath": "v1/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." } } }, "publishers": { "resources": { "models": { "methods": { "countTokens": { "httpMethod": "POST", "description": "Perform a token counting.", "request": { "$ref": "GoogleCloudAiplatformV1CountTokensRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1CountTokensResponse" }, "parameterOrder": [ "endpoint" ], "id": "aiplatform.publishers.models.countTokens", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/publishers/{publishersId}/models/{modelsId}:countTokens", "path": "v1/{+endpoint}:countTokens", "parameters": { "endpoint": { "required": true, "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "type": "string", "location": "path", "pattern": "^publishers/[^/]+/models/[^/]+$" } } }, "predict": { "httpMethod": "POST", "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1PredictRequest" }, "id": "aiplatform.publishers.models.predict", "path": "v1/{+endpoint}:predict", "flatPath": "v1/publishers/{publishersId}/models/{modelsId}:predict", "response": { "$ref": "GoogleCloudAiplatformV1PredictResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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", "required": true, "type": "string", "pattern": "^publishers/[^/]+/models/[^/]+$" } }, "description": "" }, "generateContent": { "description": "Generate content with multimodal inputs.", "parameterOrder": [ "model" ], "request": { "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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}`", "required": true, "type": "string", "pattern": "^publishers/[^/]+/models/[^/]+$", "location": "path" } }, "httpMethod": "POST", "flatPath": "v1/publishers/{publishersId}/models/{modelsId}:generateContent", "id": "aiplatform.publishers.models.generateContent", "response": { "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" }, "path": "v1/{+model}:generateContent" }, "computeTokens": { "path": "v1/{+endpoint}:computeTokens", "response": { "$ref": "GoogleCloudAiplatformV1ComputeTokensResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "flatPath": "v1/publishers/{publishersId}/models/{modelsId}:computeTokens", "parameters": { "endpoint": { "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true, "location": "path", "type": "string", "description": "Required. The name of the Endpoint requested to get lists of tokens and token ids." } }, "description": "Return a list of tokens based on the input text.", "request": { "$ref": "GoogleCloudAiplatformV1ComputeTokensRequest" }, "id": "aiplatform.publishers.models.computeTokens", "parameterOrder": [ "endpoint" ] }, "get": { "path": "v1/{+name}", "id": "aiplatform.publishers.models.get", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "type": "string", "pattern": "^publishers/[^/]+/models/[^/]+$", "required": true, "description": "Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}`" }, "view": { "location": "query", "description": "Optional. PublisherModel view specifying which fields to read.", "enum": [ "PUBLISHER_MODEL_VIEW_UNSPECIFIED", "PUBLISHER_MODEL_VIEW_BASIC", "PUBLISHER_MODEL_VIEW_FULL", "PUBLISHER_MODEL_VERSION_VIEW_BASIC" ], "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." ] }, "isHuggingFaceModel": { "description": "Optional. Boolean indicates whether the requested model is a Hugging Face model.", "type": "boolean", "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" }, "huggingFaceToken": { "location": "query", "description": "Optional. Token used to access Hugging Face gated models.", "type": "string" } }, "httpMethod": "GET", "flatPath": "v1/publishers/{publishersId}/models/{modelsId}", "description": "Gets a Model Garden publisher model.", "response": { "$ref": "GoogleCloudAiplatformV1PublisherModel" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "streamGenerateContent": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameters": { "model": { "type": "string", "location": "path", "pattern": "^publishers/[^/]+/models/[^/]+$", "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}`", "required": true } }, "httpMethod": "POST", "flatPath": "v1/publishers/{publishersId}/models/{modelsId}:streamGenerateContent", "parameterOrder": [ "model" ], "id": "aiplatform.publishers.models.streamGenerateContent", "response": { "$ref": "GoogleCloudAiplatformV1GenerateContentResponse" }, "description": "Generate content with multimodal inputs with streaming support.", "path": "v1/{+model}:streamGenerateContent", "request": { "$ref": "GoogleCloudAiplatformV1GenerateContentRequest" } }, "predictLongRunning": { "parameters": { "endpoint": { "type": "string", "location": "path", "pattern": "^publishers/[^/]+/models/[^/]+$", "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`", "required": true } }, "id": "aiplatform.publishers.models.predictLongRunning", "path": "v1/{+endpoint}:predictLongRunning", "request": { "$ref": "GoogleCloudAiplatformV1PredictLongRunningRequest" }, "description": "", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/publishers/{publishersId}/models/{modelsId}:predictLongRunning", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameterOrder": [ "endpoint" ], "httpMethod": "POST" }, "fetchPredictOperation": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform", "https://www.googleapis.com/auth/cloud-platform.read-only" ], "parameterOrder": [ "endpoint" ], "id": "aiplatform.publishers.models.fetchPredictOperation", "parameters": { "endpoint": { "required": true, "pattern": "^publishers/[^/]+/models/[^/]+$", "type": "string", "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}`" } }, "path": "v1/{+endpoint}:fetchPredictOperation", "request": { "$ref": "GoogleCloudAiplatformV1FetchPredictOperationRequest" }, "flatPath": "v1/publishers/{publishersId}/models/{modelsId}:fetchPredictOperation", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Fetch an asynchronous online prediction operation." } } } } }, "featureGroups": { "resources": { "operations": { "methods": { "get": { "parameterOrder": [ "name" ], "id": "aiplatform.featureGroups.operations.get", "path": "v1/{+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.", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "required": true, "pattern": "^featureGroups/[^/]+/operations/[^/]+$", "type": "string" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/featureGroups/{featureGroupsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "parameterOrder": [ "name" ], "httpMethod": "DELETE", "flatPath": "v1/featureGroups/{featureGroupsId}/operations/{operationsId}", "path": "v1/{+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`.", "parameters": { "name": { "required": true, "type": "string", "location": "path", "description": "The name of the operation resource to be deleted.", "pattern": "^featureGroups/[^/]+/operations/[^/]+$" } }, "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.featureGroups.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "id": "aiplatform.featureGroups.operations.wait", "path": "v1/{+name}:wait", "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.", "httpMethod": "POST", "parameters": { "timeout": { "type": "string", "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.", "location": "query" }, "name": { "required": true, "description": "The name of the operation resource to wait on.", "type": "string", "location": "path", "pattern": "^featureGroups/[^/]+/operations/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/featureGroups/{featureGroupsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" } }, "listWait": { "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "httpMethod": "GET", "parameters": { "pageSize": { "format": "int32", "location": "query", "type": "integer", "description": "The standard list page size." }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "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": "^featureGroups/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "type": "string", "location": "path" } }, "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.featureGroups.operations.listWait", "flatPath": "v1/featureGroups/{featureGroupsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningListOperationsResponse" } } } }, "features": { "resources": { "operations": { "methods": { "delete": { "httpMethod": "DELETE", "path": "v1/{+name}", "flatPath": "v1/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.featureGroups.features.operations.delete", "parameters": { "name": { "location": "path", "pattern": "^featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to be deleted." } }, "parameterOrder": [ "name" ] }, "get": { "parameters": { "name": { "location": "path", "pattern": "^featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "required": true, "type": "string" } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}", "id": "aiplatform.featureGroups.features.operations.get", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "httpMethod": "GET" }, "wait": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.featureGroups.features.operations.wait", "parameters": { "name": { "required": true, "pattern": "^featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "format": "google-duration", "location": "query", "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." } }, "flatPath": "v1/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "path": "v1/{+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." }, "listWait": { "parameterOrder": [ "name" ], "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "aiplatform.featureGroups.features.operations.listWait", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}:wait", "flatPath": "v1/featureGroups/{featureGroupsId}/features/{featuresId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "name": { "description": "The name of the operation's parent resource.", "pattern": "^featureGroups/[^/]+/features/[^/]+/operations/[^/]+$", "required": true, "type": "string", "location": "path" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "location": "query", "description": "The standard list page size.", "format": "int32", "type": "integer" } } } } } } } } }, "models": { "resources": { "operations": { "methods": { "get": { "path": "v1/{+name}", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^models/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "required": true } }, "id": "aiplatform.models.operations.get", "flatPath": "v1/models/{modelsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "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.", "httpMethod": "GET" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/models/{modelsId}/operations/{operationsId}:wait", "id": "aiplatform.models.operations.wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameterOrder": [ "name" ], "parameters": { "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "format": "google-duration" }, "name": { "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^models/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } } }, "list": { "flatPath": "v1/models/{modelsId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations", "id": "aiplatform.models.operations.list", "httpMethod": "GET", "parameters": { "returnPartialSuccess": { "type": "boolean", "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation." }, "name": { "pattern": "^models/[^/]+$", "required": true, "description": "The name of the operation's parent resource.", "type": "string", "location": "path" }, "pageSize": { "format": "int32", "location": "query", "type": "integer", "description": "The standard list page size." }, "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." } }, "parameterOrder": [ "name" ] }, "delete": { "httpMethod": "DELETE", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/models/{modelsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "type": "string", "required": true, "pattern": "^models/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted." } }, "id": "aiplatform.models.operations.delete", "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`." }, "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`.", "flatPath": "v1/models/{modelsId}/operations/{operationsId}:cancel", "id": "aiplatform.models.operations.cancel", "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource to be cancelled.", "required": true, "pattern": "^models/[^/]+/operations/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "parameterOrder": [ "name" ] } } }, "evaluations": { "resources": { "operations": { "methods": { "list": { "flatPath": "v1/models/{modelsId}/evaluations/{evaluationsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "name": { "location": "path", "pattern": "^models/[^/]+/evaluations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation's parent resource." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "location": "query", "description": "The standard list page size.", "format": "int32", "type": "integer" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "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" } }, "id": "aiplatform.models.evaluations.operations.list", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations" }, "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.", "parameters": { "name": { "description": "The name of the operation resource.", "type": "string", "required": true, "pattern": "^models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "location": "path" } }, "httpMethod": "GET", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.models.evaluations.operations.get", "flatPath": "v1/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}", "path": "v1/{+name}" }, "delete": { "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource to be deleted.", "required": true, "pattern": "^models/[^/]+/evaluations/[^/]+/operations/[^/]+$" } }, "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}", "parameterOrder": [ "name" ], "path": "v1/{+name}", "id": "aiplatform.models.evaluations.operations.delete", "httpMethod": "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`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "parameters": { "name": { "type": "string", "required": true, "pattern": "^models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "format": "google-duration", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.models.evaluations.operations.wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "flatPath": "v1/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:wait" }, "cancel": { "path": "v1/{+name}:cancel", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "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": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "pattern": "^models/[^/]+/evaluations/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to be cancelled." } }, "flatPath": "v1/models/{modelsId}/evaluations/{evaluationsId}/operations/{operationsId}:cancel", "id": "aiplatform.models.evaluations.operations.cancel" } } } } } } }, "studies": { "resources": { "trials": { "resources": { "operations": { "methods": { "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "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.", "required": true, "pattern": "^studies/[^/]+/trials/[^/]+/operations/[^/]+$", "location": "path", "type": "string" }, "timeout": { "type": "string", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration", "location": "query" } }, "parameterOrder": [ "name" ], "path": "v1/{+name}:wait", "flatPath": "v1/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}:wait", "id": "aiplatform.studies.trials.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" } }, "cancel": { "path": "v1/{+name}:cancel", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "description": "The name of the operation resource to be cancelled.", "pattern": "^studies/[^/]+/trials/[^/]+/operations/[^/]+$", "type": "string", "location": "path" } }, "response": { "$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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}:cancel", "httpMethod": "POST", "id": "aiplatform.studies.trials.operations.cancel" }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "parameterOrder": [ "name" ], "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "path": "v1/{+name}", "id": "aiplatform.studies.trials.operations.delete", "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation resource to be deleted.", "pattern": "^studies/[^/]+/trials/[^/]+/operations/[^/]+$", "location": "path" } } }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "GET", "flatPath": "v1/studies/{studiesId}/trials/{trialsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "id": "aiplatform.studies.trials.operations.get", "parameters": { "name": { "description": "The name of the operation resource.", "required": true, "type": "string", "location": "path", "pattern": "^studies/[^/]+/trials/[^/]+/operations/[^/]+$" } }, "path": "v1/{+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": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/studies/{studiesId}/trials/{trialsId}/operations", "id": "aiplatform.studies.trials.operations.list", "path": "v1/{+name}/operations", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^studies/[^/]+/trials/[^/]+$", "required": true }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "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." }, "pageSize": { "description": "The standard list page size.", "type": "integer", "format": "int32", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "parameterOrder": [ "name" ] } } } } }, "operations": { "methods": { "cancel": { "parameterOrder": [ "name" ], "id": "aiplatform.studies.operations.cancel", "path": "v1/{+name}:cancel", "parameters": { "name": { "location": "path", "pattern": "^studies/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to be cancelled." } }, "response": { "$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`.", "httpMethod": "POST", "flatPath": "v1/studies/{studiesId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "pattern": "^studies/[^/]+/operations/[^/]+$", "required": true } }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "flatPath": "v1/studies/{studiesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.studies.operations.delete", "path": "v1/{+name}", "parameterOrder": [ "name" ], "httpMethod": "DELETE" }, "list": { "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "flatPath": "v1/studies/{studiesId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations", "parameters": { "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^studies/[^/]+$", "type": "string", "required": true }, "pageSize": { "type": "integer", "location": "query", "description": "The standard list page size.", "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." } }, "id": "aiplatform.studies.operations.list" }, "wait": { "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path", "pattern": "^studies/[^/]+/operations/[^/]+$" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration", "type": "string", "location": "query" } }, "path": "v1/{+name}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.studies.operations.wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1/studies/{studiesId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST" }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/studies/{studiesId}/operations/{operationsId}", "id": "aiplatform.studies.operations.get", "httpMethod": "GET", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "path": "v1/{+name}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "type": "string", "pattern": "^studies/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "location": "path" } } } } } } }, "datasets": { "resources": { "datasetVersions": { "methods": { "create": { "request": { "$ref": "GoogleCloudAiplatformV1DatasetVersion" }, "flatPath": "v1/datasets/{datasetsId}/datasetVersions", "description": "Create a version from a Dataset.", "parameters": { "parent": { "type": "string", "pattern": "^datasets/[^/]+$", "required": true, "description": "Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "location": "path" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+parent}/datasetVersions", "id": "aiplatform.datasets.datasetVersions.create", "httpMethod": "POST", "parameterOrder": [ "parent" ] }, "delete": { "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.datasets.datasetVersions.delete", "description": "Deletes a Dataset version.", "httpMethod": "DELETE", "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "required": true, "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "pattern": "^datasets/[^/]+/datasetVersions/[^/]+$", "location": "path" } }, "flatPath": "v1/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", "response": { "$ref": "GoogleLongrunningOperation" } }, "get": { "description": "Gets a Dataset version.", "httpMethod": "GET", "id": "aiplatform.datasets.datasetVersions.get", "response": { "$ref": "GoogleCloudAiplatformV1DatasetVersion" }, "flatPath": "v1/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", "path": "v1/{+name}", "parameterOrder": [ "name" ], "parameters": { "name": { "pattern": "^datasets/[^/]+/datasetVersions/[^/]+$", "description": "Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "location": "path", "type": "string", "required": true }, "readMask": { "location": "query", "format": "google-fieldmask", "type": "string", "description": "Mask specifying which fields to read." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "response": { "$ref": "GoogleCloudAiplatformV1ListDatasetVersionsResponse" }, "parameters": { "parent": { "required": true, "description": "Required. The resource name of the Dataset to list DatasetVersions from. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "pattern": "^datasets/[^/]+$", "location": "path", "type": "string" }, "pageToken": { "description": "Optional. The standard list page token.", "location": "query", "type": "string" }, "pageSize": { "format": "int32", "description": "Optional. The standard list page size.", "location": "query", "type": "integer" }, "orderBy": { "location": "query", "description": "Optional. A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending.", "type": "string" }, "readMask": { "location": "query", "type": "string", "format": "google-fieldmask", "description": "Optional. Mask specifying which fields to read." }, "filter": { "type": "string", "location": "query", "description": "Optional. The standard list filter." } }, "description": "Lists DatasetVersions in a Dataset.", "flatPath": "v1/datasets/{datasetsId}/datasetVersions", "path": "v1/{+parent}/datasetVersions", "parameterOrder": [ "parent" ], "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.datasets.datasetVersions.list" }, "patch": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleCloudAiplatformV1DatasetVersion" }, "flatPath": "v1/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}", "httpMethod": "PATCH", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "required": true, "description": "Output only. Identifier. The resource name of the DatasetVersion. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "type": "string", "pattern": "^datasets/[^/]+/datasetVersions/[^/]+$" }, "updateMask": { "location": "query", "type": "string", "description": "Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name`", "format": "google-fieldmask" } }, "id": "aiplatform.datasets.datasetVersions.patch", "request": { "$ref": "GoogleCloudAiplatformV1DatasetVersion" }, "description": "Updates a DatasetVersion.", "path": "v1/{+name}" }, "restore": { "path": "v1/{+name}:restore", "id": "aiplatform.datasets.datasetVersions.restore", "parameterOrder": [ "name" ], "httpMethod": "GET", "parameters": { "name": { "description": "Required. The name of the DatasetVersion resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`", "location": "path", "pattern": "^datasets/[^/]+/datasetVersions/[^/]+$", "type": "string", "required": true } }, "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Restores a dataset version.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/datasets/{datasetsId}/datasetVersions/{datasetVersionsId}:restore" } } }, "dataItems": { "resources": { "operations": { "methods": { "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "returnPartialSuccess": { "location": "query", "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." }, "name": { "pattern": "^datasets/[^/]+/dataItems/[^/]+$", "location": "path", "description": "The name of the operation's parent resource.", "required": true, "type": "string" }, "pageSize": { "format": "int32", "description": "The standard list page size.", "type": "integer", "location": "query" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations", "flatPath": "v1/datasets/{datasetsId}/dataItems/{dataItemsId}/operations", "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "aiplatform.datasets.dataItems.operations.list" }, "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`.", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "required": true, "location": "path" } }, "parameterOrder": [ "name" ], "httpMethod": "POST", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.datasets.dataItems.operations.cancel", "path": "v1/{+name}:cancel" }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}", "httpMethod": "GET", "parameterOrder": [ "name" ], "id": "aiplatform.datasets.dataItems.operations.get", "parameters": { "name": { "required": true, "pattern": "^datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation resource." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+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." }, "delete": { "httpMethod": "DELETE", "id": "aiplatform.datasets.dataItems.operations.delete", "flatPath": "v1/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "path": "v1/{+name}", "parameters": { "name": { "required": true, "pattern": "^datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "description": "The name of the operation resource to be deleted." } } }, "wait": { "id": "aiplatform.datasets.dataItems.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "flatPath": "v1/datasets/{datasetsId}/dataItems/{dataItemsId}/operations/{operationsId}:wait", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "pattern": "^datasets/[^/]+/dataItems/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "location": "path", "type": "string" }, "timeout": { "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string" } }, "response": { "$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.", "path": "v1/{+name}:wait" } } }, "annotations": { "resources": { "operations": { "methods": { "wait": { "parameters": { "timeout": { "format": "google-duration", "location": "query", "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." }, "name": { "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "pattern": "^datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "location": "path" } }, "parameterOrder": [ "name" ], "path": "v1/{+name}:wait", "id": "aiplatform.datasets.dataItems.annotations.operations.wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" } }, "cancel": { "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`.", "id": "aiplatform.datasets.dataItems.annotations.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "required": true, "location": "path", "type": "string", "description": "The name of the operation resource to be cancelled." } }, "flatPath": "v1/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}:cancel", "httpMethod": "POST", "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}:cancel" }, "list": { "parameterOrder": [ "name" ], "flatPath": "v1/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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`.", "id": "aiplatform.datasets.dataItems.annotations.operations.list", "parameters": { "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." }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "name": { "pattern": "^datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+$", "description": "The name of the operation's parent resource.", "required": true, "location": "path", "type": "string" }, "pageSize": { "format": "int32", "type": "integer", "description": "The standard list page size.", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations", "httpMethod": "GET" }, "delete": { "parameters": { "name": { "pattern": "^datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "required": true, "description": "The name of the operation resource to be deleted." } }, "flatPath": "v1/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "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`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.datasets.dataItems.annotations.operations.delete", "path": "v1/{+name}" }, "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.datasets.dataItems.annotations.operations.get", "flatPath": "v1/datasets/{datasetsId}/dataItems/{dataItemsId}/annotations/{annotationsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource.", "type": "string", "location": "path", "required": true, "pattern": "^datasets/[^/]+/dataItems/[^/]+/annotations/[^/]+/operations/[^/]+$" } }, "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.", "httpMethod": "GET", "path": "v1/{+name}", "parameterOrder": [ "name" ] } } } } } } }, "operations": { "methods": { "get": { "flatPath": "v1/datasets/{datasetsId}/operations/{operationsId}", "parameters": { "name": { "description": "The name of the operation resource.", "required": true, "type": "string", "location": "path", "pattern": "^datasets/[^/]+/operations/[^/]+$" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "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.", "id": "aiplatform.datasets.operations.get", "httpMethod": "GET" }, "list": { "flatPath": "v1/datasets/{datasetsId}/operations", "httpMethod": "GET", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations", "id": "aiplatform.datasets.operations.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "name": { "required": true, "pattern": "^datasets/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation's parent resource." }, "pageSize": { "location": "query", "type": "integer", "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." } } }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}", "flatPath": "v1/datasets/{datasetsId}/operations/{operationsId}", "httpMethod": "DELETE", "id": "aiplatform.datasets.operations.delete", "parameters": { "name": { "location": "path", "pattern": "^datasets/[^/]+/operations/[^/]+$", "type": "string", "required": true, "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`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "parameters": { "name": { "required": true, "pattern": "^datasets/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "location": "query", "type": "string" } }, "id": "aiplatform.datasets.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/datasets/{datasetsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "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.", "path": "v1/{+name}:wait", "httpMethod": "POST" }, "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`.", "path": "v1/{+name}:cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "required": true, "pattern": "^datasets/[^/]+/operations/[^/]+$", "type": "string", "location": "path" } }, "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.datasets.operations.cancel", "parameterOrder": [ "name" ], "flatPath": "v1/datasets/{datasetsId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST" } } }, "annotationSpecs": { "resources": { "operations": { "methods": { "wait": { "httpMethod": "POST", "path": "v1/{+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.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "timeout": { "type": "string", "location": "query", "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.", "format": "google-duration" }, "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "id": "aiplatform.datasets.annotationSpecs.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:wait", "parameterOrder": [ "name" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}:cancel", "id": "aiplatform.datasets.annotationSpecs.operations.cancel", "parameters": { "name": { "required": true, "pattern": "^datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "location": "path", "type": "string" } }, "parameterOrder": [ "name" ], "httpMethod": "POST", "path": "v1/{+name}: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`." }, "delete": { "parameterOrder": [ "name" ], "httpMethod": "DELETE", "id": "aiplatform.datasets.annotationSpecs.operations.delete", "path": "v1/{+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`.", "parameters": { "name": { "required": true, "description": "The name of the operation resource to be deleted.", "pattern": "^datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}" }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "description": "The name of the operation's parent resource.", "required": true, "pattern": "^datasets/[^/]+/annotationSpecs/[^/]+$", "type": "string", "location": "path" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "pageSize": { "description": "The standard list page size.", "format": "int32", "location": "query", "type": "integer" } }, "path": "v1/{+name}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations", "id": "aiplatform.datasets.annotationSpecs.operations.list", "httpMethod": "GET", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/datasets/{datasetsId}/annotationSpecs/{annotationSpecsId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^datasets/[^/]+/annotationSpecs/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "id": "aiplatform.datasets.annotationSpecs.operations.get" } } } } }, "savedQueries": { "resources": { "operations": { "methods": { "list": { "parameters": { "returnPartialSuccess": { "location": "query", "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." }, "pageSize": { "format": "int32", "type": "integer", "location": "query", "description": "The standard list page size." }, "name": { "required": true, "type": "string", "pattern": "^datasets/[^/]+/savedQueries/[^/]+$", "location": "path", "description": "The name of the operation's parent resource." }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "id": "aiplatform.datasets.savedQueries.operations.list", "path": "v1/{+name}/operations", "flatPath": "v1/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET" }, "delete": { "httpMethod": "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`.", "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$" } }, "id": "aiplatform.datasets.savedQueries.operations.delete", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "path": "v1/{+name}", "flatPath": "v1/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "id": "aiplatform.datasets.savedQueries.operations.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "required": true, "location": "path", "description": "The name of the operation resource.", "type": "string", "pattern": "^datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$" } }, "flatPath": "v1/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}", "path": "v1/{+name}", "parameterOrder": [ "name" ], "httpMethod": "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." }, "wait": { "parameters": { "timeout": { "format": "google-duration", "type": "string", "location": "query", "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." }, "name": { "description": "The name of the operation resource to wait on.", "pattern": "^datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$", "required": true, "location": "path", "type": "string" } }, "id": "aiplatform.datasets.savedQueries.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:wait", "httpMethod": "POST", "path": "v1/{+name}:wait" }, "cancel": { "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`.", "flatPath": "v1/datasets/{datasetsId}/savedQueries/{savedQueriesId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "POST", "id": "aiplatform.datasets.savedQueries.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^datasets/[^/]+/savedQueries/[^/]+/operations/[^/]+$" } }, "path": "v1/{+name}:cancel" } } } } } }, "methods": { "patch": { "parameters": { "updateMask": { "type": "string", "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`", "location": "query" }, "name": { "description": "Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`", "type": "string", "required": true, "pattern": "^datasets/[^/]+$", "location": "path" } }, "response": { "$ref": "GoogleCloudAiplatformV1Dataset" }, "flatPath": "v1/datasets/{datasetsId}", "request": { "$ref": "GoogleCloudAiplatformV1Dataset" }, "id": "aiplatform.datasets.patch", "parameterOrder": [ "name" ], "description": "Updates a Dataset.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "PATCH", "path": "v1/{+name}" }, "get": { "id": "aiplatform.datasets.get", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1Dataset" }, "path": "v1/{+name}", "flatPath": "v1/datasets/{datasetsId}", "parameters": { "name": { "description": "Required. The name of the Dataset resource.", "location": "path", "type": "string", "pattern": "^datasets/[^/]+$", "required": true }, "readMask": { "location": "query", "format": "google-fieldmask", "type": "string", "description": "Mask specifying which fields to read." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "description": "Gets a Dataset." }, "create": { "parameterOrder": [], "httpMethod": "POST", "path": "v1/datasets", "parameters": { "parent": { "location": "query", "type": "string", "description": "Required. The resource name of the Location to create the Dataset in. Format: `projects/{project}/locations/{location}`" } }, "request": { "$ref": "GoogleCloudAiplatformV1Dataset" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/datasets", "id": "aiplatform.datasets.create", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Creates a Dataset." }, "delete": { "httpMethod": "DELETE", "description": "Deletes a Dataset.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "parameters": { "name": { "location": "path", "type": "string", "required": true, "pattern": "^datasets/[^/]+$", "description": "Required. The resource name of the Dataset to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}`" } }, "flatPath": "v1/datasets/{datasetsId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.datasets.delete" }, "list": { "parameters": { "pageSize": { "type": "integer", "description": "The standard list page size.", "location": "query", "format": "int32" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "readMask": { "type": "string", "description": "Mask specifying which fields to read.", "format": "google-fieldmask", "location": "query" }, "orderBy": { "location": "query", "type": "string", "description": "A comma-separated list of fields to order by, sorted in ascending order. Use \"desc\" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time`" }, "filter": { "location": "query", "description": "An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `display_name`: supports = and != * `metadata_schema_uri`: supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels.\"a key\"`. Some examples: * `displayName=\"myDisplayName\"` * `labels.myKey=\"myValue\"`", "type": "string" }, "parent": { "description": "Required. The name of the Dataset's parent resource. Format: `projects/{project}/locations/{location}`", "type": "string", "location": "query" } }, "flatPath": "v1/datasets", "path": "v1/datasets", "response": { "$ref": "GoogleCloudAiplatformV1ListDatasetsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists Datasets in a Location.", "httpMethod": "GET", "id": "aiplatform.datasets.list", "parameterOrder": [] } } }, "servingProfiles": { "resources": { "operations": { "methods": { "cancel": { "id": "aiplatform.servingProfiles.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/servingProfiles/{servingProfilesId}/operations/{operationsId}:cancel", "parameters": { "name": { "type": "string", "location": "path", "pattern": "^servingProfiles/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "required": true } }, "path": "v1/{+name}:cancel", "httpMethod": "POST", "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`." }, "get": { "id": "aiplatform.servingProfiles.operations.get", "path": "v1/{+name}", "flatPath": "v1/servingProfiles/{servingProfilesId}/operations/{operationsId}", "parameters": { "name": { "pattern": "^servingProfiles/[^/]+/operations/[^/]+$", "required": true, "location": "path", "description": "The name of the operation resource.", "type": "string" } }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "GET", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "wait": { "path": "v1/{+name}:wait", "httpMethod": "POST", "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": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." }, "name": { "type": "string", "required": true, "pattern": "^servingProfiles/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/servingProfiles/{servingProfilesId}/operations/{operationsId}:wait", "parameterOrder": [ "name" ], "id": "aiplatform.servingProfiles.operations.wait" }, "delete": { "httpMethod": "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`.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/servingProfiles/{servingProfilesId}/operations/{operationsId}", "id": "aiplatform.servingProfiles.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "parameters": { "name": { "type": "string", "location": "path", "required": true, "description": "The name of the operation resource to be deleted.", "pattern": "^servingProfiles/[^/]+/operations/[^/]+$" } } }, "list": { "id": "aiplatform.servingProfiles.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/servingProfiles/{servingProfilesId}/operations", "httpMethod": "GET", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}/operations", "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation's parent resource.", "pattern": "^servingProfiles/[^/]+$", "location": "path" }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "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" }, "pageSize": { "type": "integer", "location": "query", "description": "The standard list page size.", "format": "int32" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." } } } } }, "hyperparameterTuningJobs": { "resources": { "operations": { "methods": { "get": { "httpMethod": "GET", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "parameterOrder": [ "name" ], "flatPath": "v1/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.hyperparameterTuningJobs.operations.get", "parameters": { "name": { "required": true, "description": "The name of the operation resource.", "type": "string", "pattern": "^hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "location": "path" } } }, "wait": { "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "httpMethod": "POST", "parameters": { "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" }, "name": { "type": "string", "pattern": "^hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "location": "path", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.hyperparameterTuningJobs.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/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." }, "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`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "httpMethod": "POST", "id": "aiplatform.hyperparameterTuningJobs.operations.cancel", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}:cancel", "path": "v1/{+name}:cancel" }, "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "path": "v1/{+name}/operations", "parameters": { "pageToken": { "location": "query", "description": "The standard list page token.", "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" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "name": { "required": true, "type": "string", "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^hyperparameterTuningJobs/[^/]+$" } }, "parameterOrder": [ "name" ], "id": "aiplatform.hyperparameterTuningJobs.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "flatPath": "v1/hyperparameterTuningJobs/{hyperparameterTuningJobsId}/operations/{operationsId}", "httpMethod": "DELETE", "id": "aiplatform.hyperparameterTuningJobs.operations.delete", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "type": "string", "pattern": "^hyperparameterTuningJobs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "required": true } }, "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" ] } } } } }, "customJobs": { "resources": { "operations": { "methods": { "list": { "httpMethod": "GET", "parameterOrder": [ "name" ], "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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/customJobs/{customJobsId}/operations", "id": "aiplatform.customJobs.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "pageSize": { "type": "integer", "description": "The standard list page size.", "format": "int32", "location": "query" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "name": { "description": "The name of the operation's parent resource.", "required": true, "type": "string", "location": "path", "pattern": "^customJobs/[^/]+$" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" } }, "path": "v1/{+name}/operations" }, "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.", "httpMethod": "GET", "id": "aiplatform.customJobs.operations.get", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource.", "pattern": "^customJobs/[^/]+/operations/[^/]+$", "required": true, "location": "path", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/customJobs/{customJobsId}/operations/{operationsId}", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" } }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.customJobs.operations.delete", "flatPath": "v1/customJobs/{customJobsId}/operations/{operationsId}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "path": "v1/{+name}", "parameters": { "name": { "location": "path", "pattern": "^customJobs/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to be deleted." } } }, "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`.", "id": "aiplatform.customJobs.operations.cancel", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "type": "string", "pattern": "^customJobs/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "required": true } }, "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "flatPath": "v1/customJobs/{customJobsId}/operations/{operationsId}:cancel" }, "wait": { "parameterOrder": [ "name" ], "httpMethod": "POST", "id": "aiplatform.customJobs.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "flatPath": "v1/customJobs/{customJobsId}/operations/{operationsId}:wait", "parameters": { "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." }, "name": { "type": "string", "location": "path", "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^customJobs/[^/]+/operations/[^/]+$" } }, "path": "v1/{+name}:wait" } } } } }, "v1": { "methods": { "generateInstanceRubrics": { "id": "aiplatform.generateInstanceRubrics", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "path": "v1: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.", "request": { "$ref": "GoogleCloudAiplatformV1GenerateInstanceRubricsRequest" }, "flatPath": "v1:generateInstanceRubrics", "response": { "$ref": "GoogleCloudAiplatformV1GenerateInstanceRubricsResponse" }, "parameters": {}, "parameterOrder": [] }, "evaluateDataset": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1:evaluateDataset", "httpMethod": "POST", "description": "Evaluates a dataset based on a set of given metrics.", "parameters": {}, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1:evaluateDataset", "parameterOrder": [], "request": { "$ref": "GoogleCloudAiplatformV1EvaluateDatasetRequest" }, "id": "aiplatform.evaluateDataset" }, "evaluateInstances": { "request": { "$ref": "GoogleCloudAiplatformV1EvaluateInstancesRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1EvaluateInstancesResponse" }, "flatPath": "v1:evaluateInstances", "httpMethod": "POST", "parameterOrder": [], "parameters": {}, "description": "Evaluates instances based on a given metric.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1:evaluateInstances", "id": "aiplatform.evaluateInstances" } } }, "media": { "methods": { "upload": { "response": { "$ref": "GoogleCloudAiplatformV1UploadRagFileResponse" }, "flatPath": "v1/projects/{projectsId}/locations/{locationsId}/ragCorpora/{ragCorporaId}/ragFiles:upload", "parameters": { "parent": { "type": "string", "description": "Required. The name of the RagCorpus resource into which to upload the file. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "required": true, "pattern": "^projects/[^/]+/locations/[^/]+/ragCorpora/[^/]+$", "location": "path" } }, "mediaUpload": { "accept": [ "*/*" ], "protocols": { "simple": { "multipart": true, "path": "/upload/v1/{+parent}/ragFiles:upload" } } }, "request": { "$ref": "GoogleCloudAiplatformV1UploadRagFileRequest" }, "id": "aiplatform.media.upload", "path": "v1/{+parent}/ragFiles:upload", "description": "Upload a file into a RagCorpus.", "supportsMediaUpload": true, "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "parent" ] } } }, "specialistPools": { "resources": { "operations": { "methods": { "delete": { "path": "v1/{+name}", "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "DELETE", "flatPath": "v1/specialistPools/{specialistPoolsId}/operations/{operationsId}", "id": "aiplatform.specialistPools.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`.", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "pattern": "^specialistPools/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "path": "v1/{+name}:cancel", "parameters": { "name": { "location": "path", "pattern": "^specialistPools/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "type": "string", "required": true } }, "id": "aiplatform.specialistPools.operations.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`.", "parameterOrder": [ "name" ], "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/specialistPools/{specialistPoolsId}/operations/{operationsId}:cancel" }, "wait": { "id": "aiplatform.specialistPools.operations.wait", "httpMethod": "POST", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "path": "v1/{+name}:wait", "flatPath": "v1/specialistPools/{specialistPoolsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "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.", "type": "string", "format": "google-duration", "location": "query" }, "name": { "description": "The name of the operation resource to wait on.", "type": "string", "location": "path", "pattern": "^specialistPools/[^/]+/operations/[^/]+$", "required": true } } }, "get": { "path": "v1/{+name}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "flatPath": "v1/specialistPools/{specialistPoolsId}/operations/{operationsId}", "id": "aiplatform.specialistPools.operations.get", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^specialistPools/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/specialistPools/{specialistPoolsId}/operations", "path": "v1/{+name}/operations", "parameters": { "pageSize": { "type": "integer", "format": "int32", "description": "The standard list page size.", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "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." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^specialistPools/[^/]+$", "type": "string", "required": true } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "httpMethod": "GET", "id": "aiplatform.specialistPools.operations.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "trainingPipelines": { "resources": { "operations": { "methods": { "delete": { "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "required": true, "pattern": "^trainingPipelines/[^/]+/operations/[^/]+$" } }, "id": "aiplatform.trainingPipelines.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}", "parameterOrder": [ "name" ], "httpMethod": "DELETE", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." }, "wait": { "path": "v1/{+name}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}:wait", "id": "aiplatform.trainingPipelines.operations.wait", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "parameters": { "name": { "location": "path", "pattern": "^trainingPipelines/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "type": "string" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "location": "query", "format": "google-duration" } }, "parameterOrder": [ "name" ] }, "cancel": { "id": "aiplatform.trainingPipelines.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "required": true, "pattern": "^trainingPipelines/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "httpMethod": "POST", "path": "v1/{+name}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "name": { "type": "string", "required": true, "pattern": "^trainingPipelines/[^/]+$", "location": "path", "description": "The name of the operation's parent resource." }, "returnPartialSuccess": { "location": "query", "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." }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "pageSize": { "format": "int32", "description": "The standard list page size.", "type": "integer", "location": "query" } }, "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "flatPath": "v1/trainingPipelines/{trainingPipelinesId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.trainingPipelines.operations.list" }, "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameters": { "name": { "description": "The name of the operation resource.", "required": true, "type": "string", "location": "path", "pattern": "^trainingPipelines/[^/]+/operations/[^/]+$" } }, "id": "aiplatform.trainingPipelines.operations.get", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "flatPath": "v1/trainingPipelines/{trainingPipelinesId}/operations/{operationsId}", "httpMethod": "GET" } } } } }, "reasoningEngines": { "resources": { "sessions": { "resources": { "operations": { "methods": { "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageSize": { "format": "int32", "description": "The standard list page size.", "location": "query", "type": "integer" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+$", "required": true }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "path": "v1/{+name}/operations", "id": "aiplatform.reasoningEngines.sessions.operations.list", "parameterOrder": [ "name" ] }, "wait": { "id": "aiplatform.reasoningEngines.sessions.operations.wait", "path": "v1/{+name}:wait", "parameters": { "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "format": "google-duration", "location": "query" }, "name": { "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to wait on.", "location": "path", "type": "string" } }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "path": "v1/{+name}", "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.reasoningEngines.sessions.operations.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}", "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "required": true, "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "location": "path" } } }, "delete": { "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "parameterOrder": [ "name" ], "response": { "$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`.", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/operations/{operationsId}", "id": "aiplatform.reasoningEngines.sessions.operations.delete", "parameters": { "name": { "type": "string", "required": true, "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted." } } }, "cancel": { "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "POST", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sessions/{sessionsId}/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`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^reasoningEngines/[^/]+/sessions/[^/]+/operations/[^/]+$", "type": "string" } }, "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.sessions.operations.cancel", "path": "v1/{+name}:cancel" } } } } }, "sandboxEnvironmentTemplates": { "methods": { "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "location": "path", "description": "Required. The resource name of the reasoning engine to create the SandboxEnvironmentTemplate in. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`.", "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true } }, "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.create", "request": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplate" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates", "path": "v1/{+parent}/sandboxEnvironmentTemplates", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "parent" ], "description": "Creates a SandboxEnvironmentTemplate in a given reasoning engine." }, "delete": { "httpMethod": "DELETE", "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.delete", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}", "parameterOrder": [ "name" ], "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+$", "location": "path", "type": "string", "description": "Required. The resource name of the SandboxEnvironmentTemplate to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentTemplates/{sandbox_environment_template}`", "required": true } }, "description": "Deletes the specific SandboxEnvironmentTemplate.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "parameters": { "pageSize": { "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.", "location": "query", "format": "int32", "type": "integer" }, "filter": { "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" }, "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", "type": "string", "pattern": "^reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the reasoning engine to list sandbox environment templates from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "path": "v1/{+parent}/sandboxEnvironmentTemplates", "response": { "$ref": "GoogleCloudAiplatformV1ListSandboxEnvironmentTemplatesResponse" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates", "description": "Lists SandboxEnvironmentTemplates in a given reasoning engine.", "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.list", "httpMethod": "GET", "parameterOrder": [ "parent" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "httpMethod": "GET", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}", "response": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentTemplate" }, "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.get", "description": "Gets details of the specific SandboxEnvironmentTemplate.", "parameters": { "name": { "description": "Required. The resource name of the sandbox environment template. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentTemplates/{sandbox_environment_template}`", "required": true, "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+$", "location": "path" } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "operations": { "methods": { "delete": { "parameterOrder": [ "name" ], "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}", "path": "v1/{+name}", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "location": "path", "type": "string", "required": true } }, "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`.", "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.operations.delete" }, "cancel": { "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.operations.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`.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "required": true } }, "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "POST", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.operations.get", "parameterOrder": [ "name" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "required": true, "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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." }, "wait": { "httpMethod": "POST", "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.", "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.sandboxEnvironmentTemplates.operations.wait", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentTemplates/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "required": true, "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "location": "query", "format": "google-duration" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentTemplates/{sandboxEnvironmentTemplatesId}/operations/{operationsId}:wait" } } } } }, "runtimeRevisions": { "methods": { "query": { "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1QueryReasoningEngineResponse" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}:query", "parameters": { "name": { "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$", "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "required": true } }, "description": "Queries using a reasoning engine.", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.runtimeRevisions.query", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:query", "request": { "$ref": "GoogleCloudAiplatformV1QueryReasoningEngineRequest" } }, "streamQuery": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:streamQuery", "parameters": { "name": { "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "required": true, "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/runtimeRevisions/[^/]+$" } }, "id": "aiplatform.reasoningEngines.runtimeRevisions.streamQuery", "description": "Streams queries using a reasoning engine.", "parameterOrder": [ "name" ], "httpMethod": "POST", "response": { "$ref": "GoogleApiHttpBody" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/runtimeRevisions/{runtimeRevisionsId}:streamQuery", "request": { "$ref": "GoogleCloudAiplatformV1StreamQueryReasoningEngineRequest" } } } }, "sandboxEnvironmentSnapshots": { "methods": { "get": { "description": "Gets details of the specific SandboxEnvironmentSnapshot.", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}", "httpMethod": "GET", "path": "v1/{+name}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentSnapshot" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.get", "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the sandbox environment snapshot. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentSnapshots/{sandbox_environment_snapshot}`" } } }, "delete": { "parameters": { "name": { "type": "string", "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/[^/]+$", "required": true } }, "path": "v1/{+name}", "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.delete", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}", "description": "Deletes the specific SandboxEnvironmentSnapshot.", "parameterOrder": [ "name" ] }, "list": { "parameters": { "pageSize": { "location": "query", "format": "int32", "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." }, "filter": { "location": "query", "type": "string", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160)." }, "parent": { "required": true, "pattern": "^reasoningEngines/[^/]+$", "description": "Required. The resource name of the reasoning engine to list sandbox environments from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string", "location": "path" }, "pageToken": { "type": "string", "description": "Optional. The standard list page token, received from a previous `ListSandboxEnvironmentSnapshots` call. Provide this to retrieve the subsequent page.", "location": "query" } }, "description": "Lists SandboxEnvironmentSnapshots in a given reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1ListSandboxEnvironmentSnapshotsResponse" }, "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.list", "parameterOrder": [ "parent" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots", "path": "v1/{+parent}/sandboxEnvironmentSnapshots", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET" } }, "resources": { "operations": { "methods": { "delete": { "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}", "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.operations.delete", "path": "v1/{+name}", "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "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`.", "httpMethod": "DELETE" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation resource to wait on.", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "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.", "format": "google-duration", "location": "query" } }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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.", "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.operations.wait", "parameterOrder": [ "name" ], "httpMethod": "POST", "path": "v1/{+name}:wait" }, "get": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "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.", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.operations.get", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}", "parameters": { "name": { "type": "string", "description": "The name of the operation resource.", "location": "path", "required": true, "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$" } } }, "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironmentSnapshots/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironmentSnapshots/{sandboxEnvironmentSnapshotsId}/operations/{operationsId}:cancel", "path": "v1/{+name}:cancel", "id": "aiplatform.reasoningEngines.sandboxEnvironmentSnapshots.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST" } } } } }, "memories": { "resources": { "operations": { "methods": { "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.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:wait", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}:wait", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "parameters": { "timeout": { "type": "string", "format": "google-duration", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." }, "name": { "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "location": "path" } }, "id": "aiplatform.reasoningEngines.memories.operations.wait" }, "get": { "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}", "parameters": { "name": { "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "required": true } }, "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "id": "aiplatform.reasoningEngines.memories.operations.get", "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." }, "delete": { "path": "v1/{+name}", "httpMethod": "DELETE", "id": "aiplatform.reasoningEngines.memories.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`.", "parameters": { "name": { "location": "path", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to be deleted." } }, "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "pattern": "^reasoningEngines/[^/]+/memories/[^/]+/operations/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation resource to be cancelled." } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "path": "v1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.memories.operations.cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations/{operationsId}:cancel" }, "list": { "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/memories/{memoriesId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.reasoningEngines.memories.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "path": "v1/{+name}/operations", "parameters": { "name": { "location": "path", "pattern": "^reasoningEngines/[^/]+/memories/[^/]+$", "required": true, "type": "string", "description": "The name of the operation's parent resource." }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "returnPartialSuccess": { "location": "query", "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." }, "pageSize": { "format": "int32", "description": "The standard list page size.", "type": "integer", "location": "query" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." } } } } } } }, "operations": { "methods": { "get": { "parameterOrder": [ "name" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/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": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.reasoningEngines.operations.get", "httpMethod": "GET", "path": "v1/{+name}", "parameters": { "name": { "type": "string", "pattern": "^reasoningEngines/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource.", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "httpMethod": "POST", "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}:cancel", "parameters": { "name": { "location": "path", "pattern": "^reasoningEngines/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be cancelled.", "required": true, "type": "string" } }, "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`.", "path": "v1/{+name}:cancel" }, "delete": { "httpMethod": "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`.", "parameterOrder": [ "name" ], "id": "aiplatform.reasoningEngines.operations.delete", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/operations/{operationsId}", "path": "v1/{+name}", "parameters": { "name": { "type": "string", "description": "The name of the operation resource to be deleted.", "location": "path", "pattern": "^reasoningEngines/[^/]+/operations/[^/]+$", "required": true } }, "response": { "$ref": "GoogleProtobufEmpty" } }, "wait": { "httpMethod": "POST", "id": "aiplatform.reasoningEngines.operations.wait", "parameters": { "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" }, "name": { "location": "path", "description": "The name of the operation resource to wait on.", "pattern": "^reasoningEngines/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/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.", "path": "v1/{+name}:wait" }, "list": { "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "httpMethod": "GET", "id": "aiplatform.reasoningEngines.operations.list", "path": "v1/{+name}/operations", "parameters": { "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" }, "pageSize": { "type": "integer", "description": "The standard list page size.", "format": "int32", "location": "query" }, "filter": { "description": "The standard list filter.", "type": "string", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } } } } }, "sandboxEnvironments": { "methods": { "list": { "path": "v1/{+parent}/sandboxEnvironments", "parameterOrder": [ "parent" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments", "response": { "$ref": "GoogleCloudAiplatformV1ListSandboxEnvironmentsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "description": "Lists SandboxEnvironments in a given reasoning engine.", "parameters": { "parent": { "required": true, "description": "Required. The resource name of the reasoning engine to list sandbox environments from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+$" }, "pageToken": { "description": "Optional. The standard list page token, received from a previous `ListSandboxEnvironments` call. Provide this to retrieve the subsequent page.", "location": "query", "type": "string" }, "filter": { "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "location": "query", "type": "string" }, "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.", "type": "integer", "format": "int32", "location": "query" } }, "id": "aiplatform.reasoningEngines.sandboxEnvironments.list" }, "resume": { "request": { "$ref": "GoogleCloudAiplatformV1ResumeSandboxEnvironmentRequest" }, "parameters": { "name": { "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true, "type": "string", "location": "path", "description": "Required. The resource name of the sandbox environment to resume. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`" } }, "description": "Resumes the specific SandboxEnvironment.", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:resume", "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:resume", "httpMethod": "POST", "id": "aiplatform.reasoningEngines.sandboxEnvironments.resume", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "authorizeAccess": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "description": "Required. The resource name of the sandbox environment to authorize access to. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "type": "string", "required": true } }, "id": "aiplatform.reasoningEngines.sandboxEnvironments.authorizeAccess", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleCloudAiplatformV1AuthorizeSandboxEnvironmentAccessResponse" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:authorizeAccess", "path": "v1/{+name}:authorizeAccess", "httpMethod": "POST", "description": "Checks whether the caller is authorized to access the sandbox environment. Authorization is performed entirely by the API infrastructure from the `method_policy` below; the handler is a no-op. A successful response means the caller holds `sandboxEnvironments.execute` on the named sandbox. Used by the sandbox data-plane proxy, which forwards the caller's credential and proxies traffic only on success.", "request": { "$ref": "GoogleCloudAiplatformV1AuthorizeSandboxEnvironmentAccessRequest" } }, "snapshot": { "httpMethod": "POST", "description": "Snapshots the specific SandboxEnvironment resource and creates a SandboxEnvironmentSnapshot resource.", "parameterOrder": [ "name" ], "path": "v1/{+name}:snapshot", "id": "aiplatform.reasoningEngines.sandboxEnvironments.snapshot", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironmentSnapshot" }, "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:snapshot", "parameters": { "name": { "required": true, "type": "string", "description": "Required. The resource name of the sandbox environment to snapshot. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`.", "location": "path", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$" } } }, "execute": { "description": "Executes using a sandbox environment.", "response": { "$ref": "GoogleCloudAiplatformV1ExecuteSandboxEnvironmentResponse" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:execute", "request": { "$ref": "GoogleCloudAiplatformV1ExecuteSandboxEnvironmentRequest" }, "parameters": { "name": { "description": "Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "location": "path", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "type": "string", "required": true } }, "parameterOrder": [ "name" ], "httpMethod": "POST", "id": "aiplatform.reasoningEngines.sandboxEnvironments.execute", "path": "v1/{+name}:execute", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "create": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "required": true, "type": "string", "pattern": "^reasoningEngines/[^/]+$", "description": "Required. The resource name of the reasoning engine to create the SandboxEnvironment in. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`.", "location": "path" } }, "description": "Creates a SandboxEnvironment in a given reasoning engine.", "request": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironment" }, "parameterOrder": [ "parent" ], "path": "v1/{+parent}/sandboxEnvironments", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.reasoningEngines.sandboxEnvironments.create", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments" }, "delete": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}", "parameterOrder": [ "name" ], "path": "v1/{+name}", "parameters": { "name": { "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}`", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "location": "path" } }, "id": "aiplatform.reasoningEngines.sandboxEnvironments.delete", "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes the specific SandboxEnvironment." }, "get": { "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The resource name of the sandbox environment. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "required": true, "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets details of the specific SandboxEnvironment.", "id": "aiplatform.reasoningEngines.sandboxEnvironments.get", "httpMethod": "GET", "path": "v1/{+name}", "response": { "$ref": "GoogleCloudAiplatformV1SandboxEnvironment" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}" }, "pause": { "httpMethod": "POST", "request": { "$ref": "GoogleCloudAiplatformV1PauseSandboxEnvironmentRequest" }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:pause", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}:pause", "description": "Pauses the specific SandboxEnvironment.", "id": "aiplatform.reasoningEngines.sandboxEnvironments.pause", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "type": "string", "location": "path", "description": "Required. The resource name of the sandbox environment to pause. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironments/{sandbox_environment}`", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+$", "required": true } } } }, "resources": { "operations": { "methods": { "delete": { "httpMethod": "DELETE", "id": "aiplatform.reasoningEngines.sandboxEnvironments.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`.", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "response": { "$ref": "GoogleProtobufEmpty" }, "parameters": { "name": { "location": "path", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to be deleted." } }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}" }, "wait": { "parameters": { "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.", "format": "google-duration", "location": "query" }, "name": { "location": "path", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to wait on.", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.reasoningEngines.sandboxEnvironments.operations.wait", "path": "v1/{+name}:wait", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}:wait", "httpMethod": "POST", "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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "httpMethod": "GET", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/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": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "parameters": { "name": { "location": "path", "type": "string", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "required": true } }, "id": "aiplatform.reasoningEngines.sandboxEnvironments.operations.get" }, "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`.", "parameters": { "name": { "required": true, "description": "The name of the operation resource to be cancelled.", "type": "string", "location": "path", "pattern": "^reasoningEngines/[^/]+/sandboxEnvironments/[^/]+/operations/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}/sandboxEnvironments/{sandboxEnvironmentsId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "httpMethod": "POST", "id": "aiplatform.reasoningEngines.sandboxEnvironments.operations.cancel", "path": "v1/{+name}:cancel" } } } } } }, "methods": { "create": { "parameterOrder": [], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a reasoning engine.", "flatPath": "v1/reasoningEngines", "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "parent": { "description": "Required. The resource name of the Location to create the ReasoningEngine in. Format: `projects/{project}/locations/{location}`", "type": "string", "location": "query" } }, "id": "aiplatform.reasoningEngines.create", "path": "v1/reasoningEngines", "request": { "$ref": "GoogleCloudAiplatformV1ReasoningEngine" } }, "delete": { "description": "Deletes a reasoning engine.", "httpMethod": "DELETE", "path": "v1/{+name}", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.reasoningEngines.delete", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "force": { "description": "Optional. If set to true, child resources of this reasoning engine will also be deleted. Otherwise, the request will fail with FAILED_PRECONDITION error when the reasoning engine has undeleted child resources.", "type": "boolean", "location": "query" }, "name": { "location": "path", "pattern": "^reasoningEngines/[^/]+$", "type": "string", "required": true, "description": "Required. The name of the ReasoningEngine resource to be deleted. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "parameterOrder": [ "name" ] }, "query": { "request": { "$ref": "GoogleCloudAiplatformV1QueryReasoningEngineRequest" }, "id": "aiplatform.reasoningEngines.query", "path": "v1/{+name}:query", "parameterOrder": [ "name" ], "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}:query", "parameters": { "name": { "required": true, "pattern": "^reasoningEngines/[^/]+$", "location": "path", "type": "string", "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "response": { "$ref": "GoogleCloudAiplatformV1QueryReasoningEngineResponse" }, "description": "Queries using a reasoning engine." }, "executeCode": { "request": { "$ref": "GoogleCloudAiplatformV1ExecuteCodeRequest" }, "description": "Executes code statelessly.", "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "location": "path", "pattern": "^reasoningEngines/[^/]+$", "required": true, "description": "Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`" } }, "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.reasoningEngines.executeCode", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}:executeCode", "path": "v1/{+name}:executeCode", "response": { "$ref": "GoogleCloudAiplatformV1ExecuteCodeResponse" } }, "get": { "description": "Gets a reasoning engine.", "response": { "$ref": "GoogleCloudAiplatformV1ReasoningEngine" }, "parameters": { "name": { "required": true, "pattern": "^reasoningEngines/[^/]+$", "location": "path", "description": "Required. The name of the ReasoningEngine resource. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "type": "string" } }, "parameterOrder": [ "name" ], "flatPath": "v1/reasoningEngines/{reasoningEnginesId}", "id": "aiplatform.reasoningEngines.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "path": "v1/{+name}" }, "cancelAsyncQuery": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.reasoningEngines.cancelAsyncQuery", "request": { "$ref": "GoogleCloudAiplatformV1CancelAsyncQueryReasoningEngineRequest" }, "httpMethod": "POST", "path": "v1/{+name}:cancelAsyncQuery", "parameters": { "name": { "required": true, "pattern": "^reasoningEngines/[^/]+$", "type": "string", "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path" } }, "response": { "$ref": "GoogleCloudAiplatformV1CancelAsyncQueryReasoningEngineResponse" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}:cancelAsyncQuery", "parameterOrder": [ "name" ], "description": "Cancels an AsyncQueryReasoningEngine operation." }, "list": { "id": "aiplatform.reasoningEngines.list", "description": "Lists reasoning engines in a location.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "parent": { "type": "string", "description": "Required. The resource name of the Location to list the ReasoningEngines from. Format: `projects/{project}/locations/{location}`", "location": "query" }, "pageSize": { "location": "query", "format": "int32", "description": "Optional. The standard list page size.", "type": "integer" }, "pageToken": { "type": "string", "location": "query", "description": "Optional. The standard list page token." }, "filter": { "location": "query", "description": "Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).", "type": "string" } }, "httpMethod": "GET", "parameterOrder": [], "flatPath": "v1/reasoningEngines", "path": "v1/reasoningEngines", "response": { "$ref": "GoogleCloudAiplatformV1ListReasoningEnginesResponse" } }, "streamQuery": { "description": "Streams queries using a reasoning engine.", "response": { "$ref": "GoogleApiHttpBody" }, "httpMethod": "POST", "flatPath": "v1/reasoningEngines/{reasoningEnginesId}:streamQuery", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "required": true, "type": "string", "pattern": "^reasoningEngines/[^/]+$", "location": "path" } }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.reasoningEngines.streamQuery", "request": { "$ref": "GoogleCloudAiplatformV1StreamQueryReasoningEngineRequest" }, "path": "v1/{+name}:streamQuery" }, "asyncQuery": { "description": "Async query using a reasoning engine.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1AsyncQueryReasoningEngineRequest" }, "parameters": { "name": { "type": "string", "description": "Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^reasoningEngines/[^/]+$", "required": true } }, "id": "aiplatform.reasoningEngines.asyncQuery", "httpMethod": "POST", "path": "v1/{+name}:asyncQuery", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}:asyncQuery", "parameterOrder": [ "name" ] }, "patch": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "request": { "$ref": "GoogleCloudAiplatformV1ReasoningEngine" }, "flatPath": "v1/reasoningEngines/{reasoningEnginesId}", "httpMethod": "PATCH", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.reasoningEngines.patch", "parameters": { "updateMask": { "format": "google-fieldmask", "type": "string", "description": "Optional. Mask specifying which fields to update.", "location": "query" }, "name": { "description": "Identifier. The resource name of the ReasoningEngine. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`", "location": "path", "pattern": "^reasoningEngines/[^/]+$", "required": true, "type": "string" } }, "description": "Updates a reasoning engine.", "path": "v1/{+name}" } } }, "metadataStores": { "resources": { "operations": { "methods": { "wait": { "flatPath": "v1/metadataStores/{metadataStoresId}/operations/{operationsId}:wait", "response": { "$ref": "GoogleLongrunningOperation" }, "httpMethod": "POST", "id": "aiplatform.metadataStores.operations.wait", "path": "v1/{+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.", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "pattern": "^metadataStores/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "type": "string", "required": true }, "timeout": { "type": "string", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration" } } }, "get": { "parameters": { "name": { "required": true, "type": "string", "pattern": "^metadataStores/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "location": "path" } }, "flatPath": "v1/metadataStores/{metadataStoresId}/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": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}", "parameterOrder": [ "name" ], "id": "aiplatform.metadataStores.operations.get", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "required": true, "type": "string", "pattern": "^metadataStores/[^/]+/operations/[^/]+$" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "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`.", "id": "aiplatform.metadataStores.operations.cancel", "httpMethod": "POST", "flatPath": "v1/metadataStores/{metadataStoresId}/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}:cancel" }, "delete": { "parameterOrder": [ "name" ], "httpMethod": "DELETE", "flatPath": "v1/metadataStores/{metadataStoresId}/operations/{operationsId}", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.metadataStores.operations.delete", "parameters": { "name": { "pattern": "^metadataStores/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted.", "type": "string", "required": true } }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}" }, "list": { "path": "v1/{+name}/operations", "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "aiplatform.metadataStores.operations.list", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameters": { "name": { "type": "string", "required": true, "description": "The name of the operation's parent resource.", "pattern": "^metadataStores/[^/]+$", "location": "path" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" }, "pageSize": { "description": "The standard list page size.", "format": "int32", "location": "query", "type": "integer" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" } }, "flatPath": "v1/metadataStores/{metadataStoresId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ] } } }, "artifacts": { "resources": { "operations": { "methods": { "list": { "id": "aiplatform.metadataStores.artifacts.operations.list", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "flatPath": "v1/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations", "parameters": { "filter": { "description": "The standard list filter.", "type": "string", "location": "query" }, "name": { "required": true, "pattern": "^metadataStores/[^/]+/artifacts/[^/]+$", "description": "The name of the operation's parent resource.", "type": "string", "location": "path" }, "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.", "type": "boolean", "location": "query" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "pageSize": { "format": "int32", "description": "The standard list page size.", "location": "query", "type": "integer" } }, "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.metadataStores.artifacts.operations.cancel", "flatPath": "v1/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:cancel", "httpMethod": "POST", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "path": "v1/{+name}:cancel" }, "get": { "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.metadataStores.artifacts.operations.get", "flatPath": "v1/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}", "path": "v1/{+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.", "parameters": { "name": { "location": "path", "type": "string", "pattern": "^metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource." } }, "parameterOrder": [ "name" ] }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "type": "string", "pattern": "^metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "required": true, "description": "The name of the operation resource to be deleted.", "location": "path" } }, "id": "aiplatform.metadataStores.artifacts.operations.delete", "parameterOrder": [ "name" ], "path": "v1/{+name}" }, "wait": { "parameterOrder": [ "name" ], "id": "aiplatform.metadataStores.artifacts.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "pattern": "^metadataStores/[^/]+/artifacts/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to wait on.", "required": true, "type": "string" }, "timeout": { "location": "query", "type": "string", "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." } }, "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/metadataStores/{metadataStoresId}/artifacts/{artifactsId}/operations/{operationsId}:wait", "httpMethod": "POST", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "path": "v1/{+name}:wait" } } } } }, "contexts": { "resources": { "operations": { "methods": { "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "flatPath": "v1/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.metadataStores.contexts.operations.delete", "path": "v1/{+name}", "parameters": { "name": { "required": true, "description": "The name of the operation resource to be deleted.", "pattern": "^metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`." }, "wait": { "path": "v1/{+name}:wait", "httpMethod": "POST", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.metadataStores.contexts.operations.wait", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:wait", "parameterOrder": [ "name" ], "parameters": { "name": { "pattern": "^metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "required": true, "description": "The name of the operation resource to wait on." }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "location": "query", "format": "google-duration" } } }, "cancel": { "parameterOrder": [ "name" ], "flatPath": "v1/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}:cancel", "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "POST", "path": "v1/{+name}:cancel", "parameters": { "name": { "pattern": "^metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to be cancelled.", "location": "path" } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.metadataStores.contexts.operations.cancel" }, "get": { "path": "v1/{+name}", "id": "aiplatform.metadataStores.contexts.operations.get", "parameterOrder": [ "name" ], "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "httpMethod": "GET", "parameters": { "name": { "required": true, "description": "The name of the operation resource.", "pattern": "^metadataStores/[^/]+/contexts/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations/{operationsId}" }, "list": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}/operations", "flatPath": "v1/metadataStores/{metadataStoresId}/contexts/{contextsId}/operations", "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "pageSize": { "format": "int32", "location": "query", "description": "The standard list page size.", "type": "integer" }, "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "name": { "type": "string", "required": true, "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^metadataStores/[^/]+/contexts/[^/]+$" }, "returnPartialSuccess": { "location": "query", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean" } }, "id": "aiplatform.metadataStores.contexts.operations.list" } } } } }, "executions": { "resources": { "operations": { "methods": { "list": { "parameters": { "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "name": { "location": "path", "description": "The name of the operation's parent resource.", "type": "string", "pattern": "^metadataStores/[^/]+/executions/[^/]+$", "required": true }, "pageSize": { "format": "int32", "type": "integer", "location": "query", "description": "The standard list page size." }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "flatPath": "v1/metadataStores/{metadataStoresId}/executions/{executionsId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "path": "v1/{+name}/operations", "httpMethod": "GET", "id": "aiplatform.metadataStores.executions.operations.list", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "response": { "$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/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}", "parameterOrder": [ "name" ], "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "pattern": "^metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "type": "string", "required": true } }, "httpMethod": "GET", "id": "aiplatform.metadataStores.executions.operations.get", "path": "v1/{+name}" }, "delete": { "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource to be deleted.", "type": "string", "required": true, "location": "path", "pattern": "^metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$" } }, "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "DELETE", "id": "aiplatform.metadataStores.executions.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": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}" }, "wait": { "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "parameters": { "name": { "description": "The name of the operation resource to wait on.", "required": true, "type": "string", "pattern": "^metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "location": "path" }, "timeout": { "type": "string", "location": "query", "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.", "format": "google-duration" } }, "response": { "$ref": "GoogleLongrunningOperation" }, "id": "aiplatform.metadataStores.executions.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:wait", "parameterOrder": [ "name" ], "path": "v1/{+name}:wait", "httpMethod": "POST" }, "cancel": { "id": "aiplatform.metadataStores.executions.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "pattern": "^metadataStores/[^/]+/executions/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "required": true } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "flatPath": "v1/metadataStores/{metadataStoresId}/executions/{executionsId}/operations/{operationsId}:cancel", "httpMethod": "POST", "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`.", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" } } } } } } } }, "ragEngineConfig": { "resources": { "operations": { "methods": { "list": { "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "The standard list page size." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean", "location": "query" }, "name": { "required": true, "type": "string", "location": "path", "pattern": "^ragEngineConfig$", "description": "The name of the operation's parent resource." }, "filter": { "type": "string", "location": "query", "description": "The standard list filter." }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "aiplatform.ragEngineConfig.operations.list", "path": "v1/{+name}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/ragEngineConfig/operations", "httpMethod": "GET", "parameterOrder": [ "name" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" } }, "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "path": "v1/{+name}", "parameters": { "name": { "location": "path", "type": "string", "pattern": "^ragEngineConfig/operations/[^/]+$", "required": true, "description": "The name of the operation resource." } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "flatPath": "v1/ragEngineConfig/operations/{operationsId}", "httpMethod": "GET", "id": "aiplatform.ragEngineConfig.operations.get" }, "cancel": { "path": "v1/{+name}:cancel", "httpMethod": "POST", "id": "aiplatform.ragEngineConfig.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/ragEngineConfig/operations/{operationsId}:cancel", "parameterOrder": [ "name" ], "parameters": { "name": { "required": true, "type": "string", "description": "The name of the operation resource to be cancelled.", "pattern": "^ragEngineConfig/operations/[^/]+$", "location": "path" } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." }, "delete": { "path": "v1/{+name}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameters": { "name": { "required": true, "pattern": "^ragEngineConfig/operations/[^/]+$", "type": "string", "location": "path", "description": "The name of the operation resource to be deleted." } }, "id": "aiplatform.ragEngineConfig.operations.delete", "parameterOrder": [ "name" ], "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/ragEngineConfig/operations/{operationsId}" }, "wait": { "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/ragEngineConfig/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "id": "aiplatform.ragEngineConfig.operations.wait", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^ragEngineConfig/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "location": "path" }, "timeout": { "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "type": "string", "format": "google-duration", "location": "query" } }, "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done." } } } } }, "migratableResources": { "resources": { "operations": { "methods": { "list": { "flatPath": "v1/migratableResources/{migratableResourcesId}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "id": "aiplatform.migratableResources.operations.list", "path": "v1/{+name}/operations", "parameters": { "filter": { "location": "query", "description": "The standard list filter.", "type": "string" }, "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "pageSize": { "description": "The standard list page size.", "type": "integer", "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" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "type": "string", "required": true, "pattern": "^migratableResources/[^/]+$" } }, "httpMethod": "GET", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ] }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "path": "v1/{+name}", "id": "aiplatform.migratableResources.operations.delete", "parameters": { "name": { "pattern": "^migratableResources/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "description": "The name of the operation resource to be deleted.", "required": true } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/migratableResources/{migratableResourcesId}/operations/{operationsId}" }, "cancel": { "path": "v1/{+name}:cancel", "httpMethod": "POST", "parameters": { "name": { "type": "string", "description": "The name of the operation resource to be cancelled.", "location": "path", "required": true, "pattern": "^migratableResources/[^/]+/operations/[^/]+$" } }, "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.migratableResources.operations.cancel", "flatPath": "v1/migratableResources/{migratableResourcesId}/operations/{operationsId}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`." }, "get": { "parameters": { "name": { "location": "path", "type": "string", "pattern": "^migratableResources/[^/]+/operations/[^/]+$", "description": "The name of the operation resource.", "required": true } }, "path": "v1/{+name}", "parameterOrder": [ "name" ], "id": "aiplatform.migratableResources.operations.get", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "GET", "response": { "$ref": "GoogleLongrunningOperation" }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "flatPath": "v1/migratableResources/{migratableResourcesId}/operations/{operationsId}" }, "wait": { "parameters": { "name": { "location": "path", "pattern": "^migratableResources/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to wait on.", "required": true }, "timeout": { "location": "query", "format": "google-duration", "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." } }, "response": { "$ref": "GoogleLongrunningOperation" }, "path": "v1/{+name}:wait", "flatPath": "v1/migratableResources/{migratableResourcesId}/operations/{operationsId}:wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "httpMethod": "POST", "id": "aiplatform.migratableResources.operations.wait" } } } } }, "dataLabelingJobs": { "resources": { "operations": { "methods": { "get": { "id": "aiplatform.dataLabelingJobs.operations.get", "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunningOperation" }, "parameterOrder": [ "name" ], "flatPath": "v1/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}", "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "pattern": "^dataLabelingJobs/[^/]+/operations/[^/]+$", "required": true, "type": "string", "description": "The name of the operation resource.", "location": "path" } }, "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service." }, "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "required": true, "pattern": "^dataLabelingJobs/[^/]+/operations/[^/]+$", "type": "string" } }, "id": "aiplatform.dataLabelingJobs.operations.cancel", "flatPath": "v1/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:cancel", "httpMethod": "POST", "response": { "$ref": "GoogleProtobufEmpty" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}:cancel", "parameterOrder": [ "name" ] }, "list": { "flatPath": "v1/dataLabelingJobs/{dataLabelingJobsId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "path": "v1/{+name}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "httpMethod": "GET", "id": "aiplatform.dataLabelingJobs.operations.list", "parameterOrder": [ "name" ], "parameters": { "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", "type": "string", "description": "The standard list page token." }, "name": { "type": "string", "description": "The name of the operation's parent resource.", "location": "path", "required": true, "pattern": "^dataLabelingJobs/[^/]+$" }, "pageSize": { "description": "The standard list page size.", "format": "int32", "type": "integer", "location": "query" } }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}", "parameters": { "name": { "pattern": "^dataLabelingJobs/[^/]+/operations/[^/]+$", "location": "path", "type": "string", "required": true, "description": "The name of the operation resource to be deleted." } }, "response": { "$ref": "GoogleProtobufEmpty" }, "path": "v1/{+name}", "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "id": "aiplatform.dataLabelingJobs.operations.delete", "httpMethod": "DELETE" }, "wait": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "timeout": { "type": "string", "location": "query", "format": "google-duration", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used." }, "name": { "type": "string", "description": "The name of the operation resource to wait on.", "required": true, "pattern": "^dataLabelingJobs/[^/]+/operations/[^/]+$", "location": "path" } }, "id": "aiplatform.dataLabelingJobs.operations.wait", "httpMethod": "POST", "flatPath": "v1/dataLabelingJobs/{dataLabelingJobsId}/operations/{operationsId}:wait", "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.", "path": "v1/{+name}:wait", "response": { "$ref": "GoogleLongrunningOperation" } } } } } }, "memoryBanks": { "resources": { "memories": { "resources": { "operations": { "methods": { "get": { "parameterOrder": [ "name" ], "httpMethod": "GET", "id": "aiplatform.memoryBanks.memories.operations.get", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/memoryBanks/{memoryBanksId}/memories/{memoriesId}/operations/{operationsId}", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "description": "The name of the operation resource.", "type": "string", "location": "path", "pattern": "^memoryBanks/[^/]+/memories/[^/]+/operations/[^/]+$", "required": true } } }, "wait": { "httpMethod": "POST", "response": { "$ref": "GoogleLongrunningOperation" }, "flatPath": "v1/memoryBanks/{memoryBanksId}/memories/{memoriesId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "id": "aiplatform.memoryBanks.memories.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.", "parameters": { "timeout": { "location": "query", "format": "google-duration", "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." }, "name": { "required": true, "type": "string", "description": "The name of the operation resource to wait on.", "pattern": "^memoryBanks/[^/]+/memories/[^/]+/operations/[^/]+$", "location": "path" } }, "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "parameters": { "name": { "required": true, "description": "The name of the operation resource to be cancelled.", "pattern": "^memoryBanks/[^/]+/memories/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } }, "id": "aiplatform.memoryBanks.memories.operations.cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "flatPath": "v1/memoryBanks/{memoryBanksId}/memories/{memoriesId}/operations/{operationsId}:cancel", "httpMethod": "POST", "path": "v1/{+name}:cancel" }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "parameterOrder": [ "name" ], "flatPath": "v1/memoryBanks/{memoryBanksId}/memories/{memoriesId}/operations", "httpMethod": "GET", "id": "aiplatform.memoryBanks.memories.operations.list", "parameters": { "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" }, "pageSize": { "location": "query", "description": "The standard list page size.", "type": "integer", "format": "int32" }, "filter": { "location": "query", "type": "string", "description": "The standard list filter." }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "name": { "type": "string", "description": "The name of the operation's parent resource.", "required": true, "pattern": "^memoryBanks/[^/]+/memories/[^/]+$", "location": "path" } }, "path": "v1/{+name}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`." }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "description": "The name of the operation resource to be deleted.", "pattern": "^memoryBanks/[^/]+/memories/[^/]+/operations/[^/]+$", "location": "path", "type": "string" } }, "flatPath": "v1/memoryBanks/{memoryBanksId}/memories/{memoriesId}/operations/{operationsId}", "httpMethod": "DELETE", "id": "aiplatform.memoryBanks.memories.operations.delete", "response": { "$ref": "GoogleProtobufEmpty" }, "parameterOrder": [ "name" ] } } } } }, "operations": { "methods": { "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "parameters": { "name": { "location": "path", "description": "The name of the operation resource to be cancelled.", "pattern": "^memoryBanks/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "id": "aiplatform.memoryBanks.operations.cancel", "path": "v1/{+name}:cancel", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [ "name" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/memoryBanks/{memoryBanksId}/operations/{operationsId}:cancel", "httpMethod": "POST" }, "delete": { "id": "aiplatform.memoryBanks.operations.delete", "httpMethod": "DELETE", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v1/{+name}", "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/memoryBanks/{memoryBanksId}/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`.", "parameterOrder": [ "name" ], "parameters": { "name": { "type": "string", "required": true, "pattern": "^memoryBanks/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to be deleted." } } }, "get": { "httpMethod": "GET", "path": "v1/{+name}", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.memoryBanks.operations.get", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "required": true, "pattern": "^memoryBanks/[^/]+/operations/[^/]+$" } }, "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": "v1/memoryBanks/{memoryBanksId}/operations/{operationsId}", "response": { "$ref": "GoogleLongrunningOperation" } }, "wait": { "path": "v1/{+name}:wait", "parameterOrder": [ "name" ], "httpMethod": "POST", "id": "aiplatform.memoryBanks.operations.wait", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/memoryBanks/{memoryBanksId}/operations/{operationsId}:wait", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "parameters": { "name": { "location": "path", "pattern": "^memoryBanks/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource to wait on.", "required": true }, "timeout": { "type": "string", "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration" } } }, "list": { "path": "v1/{+name}/operations", "flatPath": "v1/memoryBanks/{memoryBanksId}/operations", "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "httpMethod": "GET", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "id": "aiplatform.memoryBanks.operations.list", "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", "location": "path", "description": "The name of the operation's parent resource.", "pattern": "^memoryBanks/[^/]+$", "required": true }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "pageSize": { "description": "The standard list page size.", "format": "int32", "location": "query", "type": "integer" }, "pageToken": { "description": "The standard list page token.", "type": "string", "location": "query" } }, "parameterOrder": [ "name" ] } } } } }, "indexEndpoints": { "resources": { "operations": { "methods": { "get": { "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "flatPath": "v1/indexEndpoints/{indexEndpointsId}/operations/{operationsId}", "id": "aiplatform.indexEndpoints.operations.get", "parameterOrder": [ "name" ], "httpMethod": "GET", "path": "v1/{+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.", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "type": "string", "pattern": "^indexEndpoints/[^/]+/operations/[^/]+$", "required": true } } }, "wait": { "parameterOrder": [ "name" ], "id": "aiplatform.indexEndpoints.operations.wait", "flatPath": "v1/indexEndpoints/{indexEndpointsId}/operations/{operationsId}:wait", "path": "v1/{+name}:wait", "httpMethod": "POST", "description": "Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.", "response": { "$ref": "GoogleLongrunningOperation" }, "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "required": true, "type": "string", "pattern": "^indexEndpoints/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource to wait on." }, "timeout": { "location": "query", "description": "The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.", "format": "google-duration", "type": "string" } } }, "delete": { "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "httpMethod": "DELETE", "response": { "$ref": "GoogleProtobufEmpty" }, "id": "aiplatform.indexEndpoints.operations.delete", "flatPath": "v1/indexEndpoints/{indexEndpointsId}/operations/{operationsId}", "path": "v1/{+name}", "parameterOrder": [ "name" ], "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameters": { "name": { "location": "path", "pattern": "^indexEndpoints/[^/]+/operations/[^/]+$", "description": "The name of the operation resource to be deleted.", "type": "string", "required": true } } }, "list": { "response": { "$ref": "GoogleLongrunningListOperationsResponse" }, "flatPath": "v1/indexEndpoints/{indexEndpointsId}/operations", "httpMethod": "GET", "id": "aiplatform.indexEndpoints.operations.list", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "parameters": { "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": { "required": true, "type": "string", "pattern": "^indexEndpoints/[^/]+$", "description": "The name of the operation's parent resource.", "location": "path" }, "pageSize": { "location": "query", "description": "The standard list page size.", "type": "integer", "format": "int32" }, "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "filter": { "description": "The standard list filter.", "type": "string", "location": "query" } }, "path": "v1/{+name}/operations", "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ] }, "cancel": { "scopes": [ "https://www.googleapis.com/auth/aiplatform", "https://www.googleapis.com/auth/cloud-platform" ], "response": { "$ref": "GoogleProtobufEmpty" }, "flatPath": "v1/indexEndpoints/{indexEndpointsId}/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`.", "id": "aiplatform.indexEndpoints.operations.cancel", "httpMethod": "POST", "parameters": { "name": { "location": "path", "pattern": "^indexEndpoints/[^/]+/operations/[^/]+$", "type": "string", "required": true, "description": "The name of the operation resource to be cancelled." } }, "parameterOrder": [ "name" ], "path": "v1/{+name}:cancel" } } } } } }, "protocol": "rest", "description": "Build, scale, govern, and optimize sophisticated agents and models.", "kind": "discovery#restDescription", "auth": { "oauth2": { "scopes": { "https://www.googleapis.com/auth/cloud-platform": { "description": "See, edit, configure, and delete your Google Cloud data and see the email address for your Google Account." }, "https://www.googleapis.com/auth/aiplatform": { "description": "See, edit, configure, and delete your Google Cloud Vertex AI data and see the email address for your Google Account" }, "https://www.googleapis.com/auth/cloud-platform.read-only": { "description": "View your data across Google Cloud services and see the email address of your Google Account" } } } }, "discoveryVersion": "v1", "parameters": { "fields": { "type": "string", "location": "query", "description": "Selector specifying which fields to include in a partial response." }, "prettyPrint": { "default": "true", "description": "Returns response with indentations and line breaks.", "location": "query", "type": "boolean" }, "upload_protocol": { "type": "string", "description": "Upload protocol for media (e.g. \"raw\", \"multipart\").", "location": "query" }, "$.xgafv": { "location": "query", "enumDescriptions": [ "v1 error format", "v2 error format" ], "type": "string", "description": "V1 error format.", "enum": [ "1", "2" ] }, "quotaUser": { "type": "string", "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" }, "alt": { "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" ], "enum": [ "json", "media", "proto" ], "description": "Data format for response.", "default": "json", "location": "query" }, "key": { "location": "query", "type": "string", "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": { "description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\").", "location": "query", "type": "string" }, "oauth_token": { "location": "query", "type": "string", "description": "OAuth 2.0 token for the current user." }, "callback": { "type": "string", "description": "JSONP", "location": "query" }, "access_token": { "description": "OAuth access token.", "location": "query", "type": "string" } }, "rootUrl": "https://aiplatform.googleapis.com/", "version_module": true, "title": "Agent Platform API", "endpoints": [ { "endpointUrl": "https://africa-south1-aiplatform.googleapis.com/", "location": "africa-south1", "description": "Locational Endpoint" }, { "endpointUrl": "https://asia-east1-aiplatform.googleapis.com/", "description": "Locational Endpoint", "location": "asia-east1" }, { "location": "asia-east2", "description": "Locational Endpoint", "endpointUrl": "https://asia-east2-aiplatform.googleapis.com/" }, { "location": "asia-northeast1", "endpointUrl": "https://asia-northeast1-aiplatform.googleapis.com/", "description": "Locational Endpoint" }, { "endpointUrl": "https://asia-northeast2-aiplatform.googleapis.com/", "location": "asia-northeast2", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://asia-northeast3-aiplatform.googleapis.com/", "location": "asia-northeast3" }, { "location": "asia-south1", "description": "Locational Endpoint", "endpointUrl": "https://asia-south1-aiplatform.googleapis.com/" }, { "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" }, { "description": "Locational Endpoint", "location": "asia-southeast2", "endpointUrl": "https://asia-southeast2-aiplatform.googleapis.com/" }, { "description": "Locational Endpoint", "location": "asia-southeast3", "endpointUrl": "https://asia-southeast3-aiplatform.googleapis.com/" }, { "description": "Locational Endpoint", "endpointUrl": "https://australia-southeast1-aiplatform.googleapis.com/", "location": "australia-southeast1" }, { "description": "Locational Endpoint", "endpointUrl": "https://australia-southeast2-aiplatform.googleapis.com/", "location": "australia-southeast2" }, { "endpointUrl": "https://europe-central2-aiplatform.googleapis.com/", "description": "Locational Endpoint", "location": "europe-central2" }, { "description": "Locational Endpoint", "endpointUrl": "https://europe-north1-aiplatform.googleapis.com/", "location": "europe-north1" }, { "location": "europe-north2", "endpointUrl": "https://europe-north2-aiplatform.googleapis.com/", "description": "Locational Endpoint" }, { "location": "europe-southwest1", "endpointUrl": "https://europe-southwest1-aiplatform.googleapis.com/", "description": "Locational Endpoint" }, { "location": "europe-west1", "endpointUrl": "https://europe-west1-aiplatform.googleapis.com/", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "endpointUrl": "https://europe-west10-aiplatform.googleapis.com/", "location": "europe-west10" }, { "description": "Locational Endpoint", "location": "europe-west15", "endpointUrl": "https://europe-west15-aiplatform.googleapis.com/" }, { "description": "Locational Endpoint", "location": "europe-west2", "endpointUrl": "https://europe-west2-aiplatform.googleapis.com/" }, { "endpointUrl": "https://europe-west3-aiplatform.googleapis.com/", "description": "Locational Endpoint", "location": "europe-west3" }, { "endpointUrl": "https://europe-west4-aiplatform.googleapis.com/", "location": "europe-west4", "description": "Locational Endpoint" }, { "location": "europe-west6", "description": "Locational Endpoint", "endpointUrl": "https://europe-west6-aiplatform.googleapis.com/" }, { "location": "europe-west8", "endpointUrl": "https://europe-west8-aiplatform.googleapis.com/", "description": "Locational Endpoint" }, { "location": "europe-west9", "description": "Locational Endpoint", "endpointUrl": "https://europe-west9-aiplatform.googleapis.com/" }, { "location": "europe-west12", "description": "Locational Endpoint", "endpointUrl": "https://europe-west12-aiplatform.googleapis.com/" }, { "location": "me-central1", "endpointUrl": "https://me-central1-aiplatform.googleapis.com/", "description": "Locational Endpoint" }, { "endpointUrl": "https://me-central2-aiplatform.googleapis.com/", "description": "Locational Endpoint", "location": "me-central2" }, { "description": "Locational Endpoint", "location": "me-west1", "endpointUrl": "https://me-west1-aiplatform.googleapis.com/" }, { "description": "Locational Endpoint", "endpointUrl": "https://northamerica-northeast1-aiplatform.googleapis.com/", "location": "northamerica-northeast1" }, { "location": "northamerica-northeast2", "endpointUrl": "https://northamerica-northeast2-aiplatform.googleapis.com/", "description": "Locational Endpoint" }, { "location": "southamerica-east1", "endpointUrl": "https://southamerica-east1-aiplatform.googleapis.com/", "description": "Locational Endpoint" }, { "endpointUrl": "https://southamerica-west1-aiplatform.googleapis.com/", "description": "Locational Endpoint", "location": "southamerica-west1" }, { "location": "us-central1", "endpointUrl": "https://us-central1-aiplatform.googleapis.com/", "description": "Locational Endpoint" }, { "location": "us-central2", "description": "Locational Endpoint", "endpointUrl": "https://us-central2-aiplatform.googleapis.com/" }, { "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" }, { "endpointUrl": "https://us-east7-aiplatform.googleapis.com/", "location": "us-east7", "description": "Locational Endpoint" }, { "description": "Locational Endpoint", "location": "us-south1", "endpointUrl": "https://us-south1-aiplatform.googleapis.com/" }, { "endpointUrl": "https://us-west1-aiplatform.googleapis.com/", "description": "Locational Endpoint", "location": "us-west1" }, { "location": "us-west2", "description": "Locational Endpoint", "endpointUrl": "https://us-west2-aiplatform.googleapis.com/" }, { "description": "Locational Endpoint", "endpointUrl": "https://us-west3-aiplatform.googleapis.com/", "location": "us-west3" }, { "location": "us-west4", "endpointUrl": "https://us-west4-aiplatform.googleapis.com/", "description": "Locational Endpoint" }, { "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" }, { "description": "Regional Endpoint", "endpointUrl": "https://aiplatform.us.rep.googleapis.com/", "location": "us" }, { "endpointUrl": "https://aiplatform.eu.rep.googleapis.com/", "description": "Regional Endpoint", "location": "eu" }, { "description": "Regional Endpoint", "endpointUrl": "https://aiplatform-preprod.us.rep.googleapis.com/", "location": "us" }, { "description": "Regional Endpoint", "location": "eu", "endpointUrl": "https://aiplatform-preprod.eu.rep.googleapis.com/" } ], "baseUrl": "https://aiplatform.googleapis.com/", "name": "aiplatform", "version": "v1", "servicePath": "", "ownerName": "Google", "fullyEncodeReservedExpansion": true, "id": "aiplatform:v1", "batchPath": "batch" }