Vertex AI API Connector Overview

The Workflows connector defines the built-in functions that can be used to access other Google Cloud products within a workflow.

This page provides an overview of the individual connector. There is no need to import or load connector libraries in a workflow—connectors work out of the box when used in a call step.

Vertex AI API

Train high-quality custom machine learning models with minimal machine learning expertise and effort. To learn more, see the Vertex AI API documentation.

Vertex AI connector sample

YAML

# This workflow demonstrates how to use the aiplatform (Vertex AI) connector.
# This workflow creates a Vertex AI custom Job and then deletes the
# job once the long-running operation of creating the job completes.
# Expected successful output: "SUCCESS"
main:
  steps:
    - init:
        assign:
          - location: ${sys.get_env("GOOGLE_CLOUD_LOCATION")}
          - project: ${sys.get_env("GOOGLE_CLOUD_PROJECT_ID")}
          # Follow https://cloud.google.com/vertex-ai/docs/training/create-custom-container to build
          # a custom container image for training.
          - container_image_uri: "IMAGE_URI"
    - create_custom_job:
        call: googleapis.aiplatform.v1.projects.locations.customJobs.create
        args:
          parent: ${"projects/" + project + "/locations/" + location}
          region: ${location}
          body:
            displayName: "example-custom-job"
            jobSpec:
              workerPoolSpecs:
                - machineSpec:
                    machineType: "n1-standard-4"
                    acceleratorType: "NVIDIA_TESLA_V100"
                    acceleratorCount: 1
                  replicaCount: 1
                  containerSpec:
                    imageUri: ${container_image_uri}
                    command: []
                    args: []
        result: customJobsResponse
    - delete_custom_job:
        call: googleapis.aiplatform.v1.projects.locations.customJobs.delete
        args:
          name: ${customJobsResponse.name}
          region: ${location}
        result: deleteCustomJobResponse
    - return:
        return: "SUCCESS"

JSON

{
  "main": {
    "steps": [
      {
        "init": {
          "assign": [
            {
              "location": "${sys.get_env(\"GOOGLE_CLOUD_LOCATION\")}"
            },
            {
              "project": "${sys.get_env(\"GOOGLE_CLOUD_PROJECT_ID\")}"
            },
            {
              "container_image_uri": "IMAGE_URI"
            }
          ]
        }
      },
      {
        "create_custom_job": {
          "call": "googleapis.aiplatform.v1.projects.locations.customJobs.create",
          "args": {
            "parent": "${\"projects/\" + project + \"/locations/\" + location}",
            "region": "${location}",
            "body": {
              "displayName": "example-custom-job",
              "jobSpec": {
                "workerPoolSpecs": [
                  {
                    "machineSpec": {
                      "machineType": "n1-standard-4",
                      "acceleratorType": "NVIDIA_TESLA_V100",
                      "acceleratorCount": 1
                    },
                    "replicaCount": 1,
                    "containerSpec": {
                      "imageUri": "${container_image_uri}",
                      "command": [],
                      "args": []
                    }
                  }
                ]
              }
            }
          },
          "result": "customJobsResponse"
        }
      },
      {
        "delete_custom_job": {
          "call": "googleapis.aiplatform.v1.projects.locations.customJobs.delete",
          "args": {
            "name": "${customJobsResponse.name}",
            "region": "${location}"
          },
          "result": "deleteCustomJobResponse"
        }
      },
      {
        "return": {
          "return": "SUCCESS"
        }
      }
    ]
  }
}

Module: googleapis.aiplatform.v1.projects.locations.batchPredictionJobs

Functions
`cancel`	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.
`create`	Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start.
`delete`	Deletes a BatchPredictionJob. Can only be called on jobs that already finished.
`get`	Gets a BatchPredictionJob
`list`	Lists BatchPredictionJobs in a Location.

Module: googleapis.aiplatform.v1.projects.locations.customJobs

Functions
`cancel`	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`.
`create`	Creates a CustomJob. A created CustomJob right away will be attempted to be run.
`delete`	Deletes a CustomJob.
`get`	Gets a CustomJob.
`list`	Lists CustomJobs in a Location.

Module: googleapis.aiplatform.v1.projects.locations.dataLabelingJobs

Functions
`cancel`	Cancels a DataLabelingJob. Success of cancellation is not guaranteed.
`create`	Creates a DataLabelingJob.
`delete`	Deletes a DataLabelingJob.
`get`	Gets a DataLabelingJob.
`list`	Lists DataLabelingJobs in a Location.

Module: googleapis.aiplatform.v1.projects.locations.datasets

Functions
`create`	Creates a Dataset.
`delete`	Deletes a Dataset.
`export`	Exports data from a Dataset.
`get`	Gets a Dataset.
`list`	Lists Datasets in a Location.
`patch`	Updates a Dataset.
`searchDataItems`	Searches DataItems in a Dataset.

Module: googleapis.aiplatform.v1.projects.locations.datasets.annotationSpecs

Functions
`get`	Gets an AnnotationSpec.

Module: googleapis.aiplatform.v1.projects.locations.datasets.dataItems

Functions
`list`	Lists DataItems in a Dataset.

Module: googleapis.aiplatform.v1.projects.locations.datasets.dataItems.annotations

Functions
`list`	Lists Annotations belongs to a dataitem

Module: googleapis.aiplatform.v1.projects.locations.datasets.datasetVersions

Functions
`create`	Create a version from a Dataset.
`delete`	Deletes a Dataset version.
`get`	Gets a Dataset version.
`list`	Lists DatasetVersions in a Dataset.
`restore`	Restores a dataset version.

Module: googleapis.aiplatform.v1.projects.locations.datasets.savedQueries

Functions
`delete`	Deletes a SavedQuery.
`list`	Lists SavedQueries in a Dataset.

Module: googleapis.aiplatform.v1.projects.locations.deploymentResourcePools

Functions
`create`	Create a DeploymentResourcePool.
`delete`	Delete a DeploymentResourcePool.
`get`	Get a DeploymentResourcePool.
`list`	List DeploymentResourcePools in a location.
`queryDeployedModels`	List DeployedModels that have been deployed on this DeploymentResourcePool.

Module: googleapis.aiplatform.v1.projects.locations.endpoints

Functions
`create`	Creates an Endpoint.
`delete`	Deletes an Endpoint.
`deployModel`	Deploys a Model into this Endpoint, creating a DeployedModel within it.
`explain`	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.
`generateContent`	Generate content with multimodal inputs.
`get`	Gets an Endpoint.
`list`	Lists Endpoints in a Location.
`mutateDeployedModel`	Updates an existing deployed model. Updatable fields include `min_replica_count`, `max_replica_count`, `autoscaling_metric_specs`, `disable_container_logging` (v1 only), and `enable_container_logging` (v1beta1 only).
`patch`	Updates an Endpoint.
`predict`	Perform an online prediction.
`rawPredict`	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.
`serverStreamingPredict`	Perform a server-side streaming online prediction request for Vertex LLM streaming.
`streamGenerateContent`	Generate content with multimodal inputs with streaming support.
`streamRawPredict`	Perform a streaming online prediction with an arbitrary HTTP payload.
`undeployModel`	Undeploys a Model from an Endpoint, removing a DeployedModel from it, and freeing all resources it's using.

Module: googleapis.aiplatform.v1.projects.locations.featureGroups

Functions
`create`	Creates a new FeatureGroup in a given project and location.
`delete`	Deletes a single FeatureGroup.
`get`	Gets details of a single FeatureGroup.
`list`	Lists FeatureGroups in a given project and location.
`patch`	Updates the parameters of a single FeatureGroup.

Module: googleapis.aiplatform.v1.projects.locations.featureGroups.features

Functions
`create`	Creates a new Feature in a given FeatureGroup.
`delete`	Deletes a single Feature.
`get`	Gets details of a single Feature.
`list`	Lists Features in a given FeatureGroup.
`patch`	Updates the parameters of a single Feature.

Module: googleapis.aiplatform.v1.projects.locations.featureOnlineStores

Functions
`create`	Creates a new FeatureOnlineStore in a given project and location.
`delete`	Deletes a single FeatureOnlineStore. The FeatureOnlineStore must not contain any FeatureViews.
`get`	Gets details of a single FeatureOnlineStore.
`list`	Lists FeatureOnlineStores in a given project and location.
`patch`	Updates the parameters of a single FeatureOnlineStore.

Module: googleapis.aiplatform.v1.projects.locations.featureOnlineStores.featureViews

Functions
`create`	Creates a new FeatureView in a given FeatureOnlineStore.
`delete`	Deletes a single FeatureView.
`fetchFeatureValues`	Fetch feature values under a FeatureView.
`get`	Gets details of a single FeatureView.
`list`	Lists FeatureViews in a given FeatureOnlineStore.
`patch`	Updates the parameters of a single FeatureView.
`searchNearestEntities`	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.
`sync`	Triggers on-demand sync for the FeatureView.

Module: googleapis.aiplatform.v1.projects.locations.featureOnlineStores.featureViews.featureViewSyncs

Functions
`get`	Gets details of a single FeatureViewSync.
`list`	Lists FeatureViewSyncs in a given FeatureView.

Module: googleapis.aiplatform.v1.projects.locations.featurestores

Functions
`batchReadFeatureValues`	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.
`create`	Creates a new Featurestore in a given project and location.
`delete`	Deletes a single Featurestore. The Featurestore must not contain any EntityTypes or `force` must be set to true for the request to succeed.
`get`	Gets details of a single Featurestore.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`list`	Lists Featurestores in a given project and location.
`patch`	Updates the parameters of a single Featurestore.
`searchFeatures`	Searches Features matching a query in a given project.
`setIamPolicy`	Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
`testIamPermissions`	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.

Module: googleapis.aiplatform.v1.projects.locations.featurestores.entityTypes

Functions
`create`	Creates a new EntityType in a given Featurestore.
`delete`	Deletes a single EntityType. The EntityType must not have any Features or `force` must be set to true for the request to succeed.
`deleteFeatureValues`	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.
`exportFeatureValues`	Exports Feature values from all the entities of a target EntityType.
`get`	Gets details of a single EntityType.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`importFeatureValues`	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.
`list`	Lists EntityTypes in a given Featurestore.
`patch`	Updates the parameters of a single EntityType.
`readFeatureValues`	Reads Feature values of a specific entity of an EntityType. For reading feature values of multiple entities of an EntityType, please use StreamingReadFeatureValues.
`setIamPolicy`	Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
`streamingReadFeatureValues`	Reads Feature values for multiple entities. Depending on their size, data for different entities may be broken up across multiple responses.
`testIamPermissions`	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.
`writeFeatureValues`	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.

Module: googleapis.aiplatform.v1.projects.locations.featurestores.entityTypes.features

Functions
`batchCreate`	Creates a batch of Features in a given EntityType.
`create`	Creates a new Feature in a given EntityType.
`delete`	Deletes a single Feature.
`get`	Gets details of a single Feature.
`list`	Lists Features in a given EntityType.
`patch`	Updates the parameters of a single Feature.

Module: googleapis.aiplatform.v1.projects.locations.hyperparameterTuningJobs

Functions
`cancel`	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`.
`create`	Creates a HyperparameterTuningJob
`delete`	Deletes a HyperparameterTuningJob.
`get`	Gets a HyperparameterTuningJob
`list`	Lists HyperparameterTuningJobs in a Location.

Module: googleapis.aiplatform.v1.projects.locations.indexEndpoints

Functions
`create`	Creates an IndexEndpoint.
`delete`	Deletes an IndexEndpoint.
`deployIndex`	Deploys an Index into this IndexEndpoint, creating a DeployedIndex within it. Only non-empty Indexes can be deployed.
`get`	Gets an IndexEndpoint.
`list`	Lists IndexEndpoints in a Location.
`mutateDeployedIndex`	Update an existing DeployedIndex under an IndexEndpoint.
`patch`	Updates an IndexEndpoint.
`undeployIndex`	Undeploys an Index from an IndexEndpoint, removing a DeployedIndex from it, and freeing all resources it's using.

Module: googleapis.aiplatform.v1.projects.locations.indexes

Functions
`create`	Creates an Index.
`delete`	Deletes an Index. An Index can only be deleted when all its DeployedIndexes had been undeployed.
`get`	Gets an Index.
`list`	Lists Indexes in a Location.
`patch`	Updates an Index.
`removeDatapoints`	Remove Datapoints from an Index.
`upsertDatapoints`	Add/update Datapoints into an Index.

Module: googleapis.aiplatform.v1.projects.locations.metadataStores

Functions
`create`	Initializes a MetadataStore, including allocation of resources.
`delete`	Deletes a single MetadataStore and all its child resources (Artifacts, Executions, and Contexts).
`get`	Retrieves a specific MetadataStore.
`list`	Lists MetadataStores for a Location.

Module: googleapis.aiplatform.v1.projects.locations.metadataStores.artifacts

Functions
`create`	Creates an Artifact associated with a MetadataStore.
`delete`	Deletes an Artifact.
`get`	Retrieves a specific Artifact.
`list`	Lists Artifacts in the MetadataStore.
`patch`	Updates a stored Artifact.
`purge`	Purges Artifacts.
`queryArtifactLineageSubgraph`	Retrieves lineage of an Artifact represented through Artifacts and Executions connected by Event edges and returned as a LineageSubgraph.

Module: googleapis.aiplatform.v1.projects.locations.metadataStores.contexts

Functions
`addContextArtifactsAndExecutions`	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.
`addContextChildren`	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.
`create`	Creates a Context associated with a MetadataStore.
`delete`	Deletes a stored Context.
`get`	Retrieves a specific Context.
`list`	Lists Contexts on the MetadataStore.
`patch`	Updates a stored Context.
`purge`	Purges Contexts.
`queryContextLineageSubgraph`	Retrieves Artifacts and Executions within the specified Context, connected by Event edges and returned as a LineageSubgraph.
`removeContextChildren`	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.

Module: googleapis.aiplatform.v1.projects.locations.metadataStores.executions

Functions
`addExecutionEvents`	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.
`create`	Creates an Execution associated with a MetadataStore.
`delete`	Deletes an Execution.
`get`	Retrieves a specific Execution.
`list`	Lists Executions in the MetadataStore.
`patch`	Updates a stored Execution.
`purge`	Purges Executions.
`queryExecutionInputsAndOutputs`	Obtains the set of input and output Artifacts for this Execution, in the form of LineageSubgraph that also contains the Execution and connecting Events.

Module: googleapis.aiplatform.v1.projects.locations.metadataStores.metadataSchemas

Functions
`create`	Creates a MetadataSchema.
`get`	Retrieves a specific MetadataSchema.
`list`	Lists MetadataSchemas.

Module: googleapis.aiplatform.v1.projects.locations.migratableResources

Functions
`batchMigrate`	Batch migrates resources from ml.googleapis.com, automl.googleapis.com, and datalabeling.googleapis.com to Vertex AI.
`search`	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.

Module: googleapis.aiplatform.v1.projects.locations.modelDeploymentMonitoringJobs

Functions
`create`	Creates a ModelDeploymentMonitoringJob. It will run periodically on a configured interval.
`delete`	Deletes a ModelDeploymentMonitoringJob.
`get`	Gets a ModelDeploymentMonitoringJob.
`list`	Lists ModelDeploymentMonitoringJobs in a Location.
`patch`	Updates a ModelDeploymentMonitoringJob.
`pause`	Pauses a ModelDeploymentMonitoringJob. If the job is running, the server makes a best effort to cancel the job. Will mark ModelDeploymentMonitoringJob.state to 'PAUSED'.
`resume`	Resumes a paused ModelDeploymentMonitoringJob. It will start to run from next scheduled time. A deleted ModelDeploymentMonitoringJob can't be resumed.
`searchModelDeploymentMonitoringStatsAnomalies`	Searches Model Monitoring Statistics generated within a given time window.

Module: googleapis.aiplatform.v1.projects.locations.models

Functions
`copy`	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.
`delete`	Deletes a Model. A model cannot be deleted if any Endpoint resource has a DeployedModel based on the model in its deployed_models field.
`deleteVersion`	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.
`export`	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.
`get`	Gets a Model.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`list`	Lists Models in a Location.
`listVersions`	Lists versions of the specified model.
`mergeVersionAliases`	Merges a set of aliases for a Model version.
`patch`	Updates a Model.
`setIamPolicy`	Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
`testIamPermissions`	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.
`updateExplanationDataset`	Incrementally update the dataset used for an examples model.
`upload`	Uploads a Model artifact into Vertex AI.

Module: googleapis.aiplatform.v1.projects.locations.models.evaluations

Functions
`get`	Gets a ModelEvaluation.
`list`	Lists ModelEvaluations in a Model.

Module: googleapis.aiplatform.v1.projects.locations.models.evaluations.slices

Functions
`batchImport`	Imports a list of externally generated EvaluatedAnnotations.
`get`	Gets a ModelEvaluationSlice.
`list`	Lists ModelEvaluationSlices in a ModelEvaluation.

Module: googleapis.aiplatform.v1.projects.locations.nasJobs

Functions
`cancel`	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`.
`create`	Creates a NasJob
`delete`	Deletes a NasJob.
`get`	Gets a NasJob
`list`	Lists NasJobs in a Location.

Module: googleapis.aiplatform.v1.projects.locations.nasJobs.nasTrialDetails

Functions
`get`	Gets a NasTrialDetail.
`list`	List top NasTrialDetails of a NasJob.

Module: googleapis.aiplatform.v1.projects.locations.notebookRuntimeTemplates

Functions
`create`	Creates a NotebookRuntimeTemplate.
`delete`	Deletes a NotebookRuntimeTemplate.
`get`	Gets a NotebookRuntimeTemplate.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`list`	Lists NotebookRuntimeTemplates in a Location.
`setIamPolicy`	Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
`testIamPermissions`	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.

Module: googleapis.aiplatform.v1.projects.locations.notebookRuntimes

Functions
`assign`	Assigns a NotebookRuntime to a user for a particular Notebook file. This method will either returns an existing assignment or generates a new one.
`delete`	Deletes a NotebookRuntime.
`get`	Gets a NotebookRuntime.
`list`	Lists NotebookRuntimes in a Location.
`start`	Starts a NotebookRuntime.

Module: googleapis.aiplatform.v1.projects.locations.operations

Functions
`cancel`	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`	Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
`get`	Gets the latest 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`	Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.
`wait`	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.

Module: googleapis.aiplatform.v1.projects.locations.persistentResources

Functions
`create`	Creates a PersistentResource.
`delete`	Deletes a PersistentResource.
`get`	Gets a PersistentResource.
`list`	Lists PersistentResources in a Location.
`patch`	Updates a PersistentResource.
`reboot`	Reboots a PersistentResource.

Module: googleapis.aiplatform.v1.projects.locations.pipelineJobs

Functions
`batchCancel`	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.
`batchDelete`	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.
`cancel`	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`	Creates a PipelineJob. A PipelineJob will run immediately when created.
`delete`	Deletes a PipelineJob.
`get`	Gets a PipelineJob.
`list`	Lists PipelineJobs in a Location.

Module: googleapis.aiplatform.v1.projects.locations.publishers.models

Functions
`generateContent`	Generate content with multimodal inputs.
`predict`	Perform an online prediction.
`rawPredict`	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.
`serverStreamingPredict`	Perform a server-side streaming online prediction request for Vertex LLM streaming.
`streamGenerateContent`	Generate content with multimodal inputs with streaming support.
`streamRawPredict`	Perform a streaming online prediction with an arbitrary HTTP payload.

Module: googleapis.aiplatform.v1.projects.locations.schedules

Functions
`create`	Creates a Schedule.
`delete`	Deletes a Schedule.
`get`	Gets a Schedule.
`list`	Lists Schedules in a Location.
`patch`	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.
`pause`	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.
`resume`	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.catchUp is set up true, all missed runs will be scheduled for backfill first.

Module: googleapis.aiplatform.v1.projects.locations.specialistPools

Functions
`create`	Creates a SpecialistPool.
`delete`	Deletes a SpecialistPool as well as all Specialists in the pool.
`get`	Gets a SpecialistPool.
`list`	Lists SpecialistPools in a Location.
`patch`	Updates a SpecialistPool.

Module: googleapis.aiplatform.v1.projects.locations.studies

Functions
`create`	Creates a Study. A resource name will be generated after creation of the Study.
`delete`	Deletes a Study.
`get`	Gets a Study by name.
`list`	Lists all the studies in a region for an associated project.
`lookup`	Looks a study up using the user-defined display_name field instead of the fully qualified resource name.

Module: googleapis.aiplatform.v1.projects.locations.studies.trials

Functions
`addTrialMeasurement`	Adds a measurement of the objective metrics to a Trial. This measurement is assumed to have been taken before the Trial is complete.
`checkTrialEarlyStoppingState`	Checks whether a Trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.
`complete`	Marks a Trial as complete.
`create`	Adds a user provided Trial to a Study.
`delete`	Deletes a Trial.
`get`	Gets a Trial.
`list`	Lists the Trials associated with a Study.
`listOptimalTrials`	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
`stop`	Stops a Trial.
`suggest`	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.

Module: googleapis.aiplatform.v1.projects.locations.tensorboards

Functions
`batchRead`	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.
`create`	Creates a Tensorboard.
`delete`	Deletes a Tensorboard.
`get`	Gets a Tensorboard.
`list`	Lists Tensorboards in a Location.
`patch`	Updates a Tensorboard.
`readSize`	Returns the storage size for a given TensorBoard instance.
`readUsage`	Returns a list of monthly active users for a given TensorBoard instance.

Module: googleapis.aiplatform.v1.projects.locations.tensorboards.experiments

Functions
`batchCreate`	Batch create TensorboardTimeSeries that belong to a TensorboardExperiment.
`create`	Creates a TensorboardExperiment.
`delete`	Deletes a TensorboardExperiment.
`get`	Gets a TensorboardExperiment.
`list`	Lists TensorboardExperiments in a Location.
`patch`	Updates a TensorboardExperiment.
`write`	Write time series data points of multiple TensorboardTimeSeries in multiple TensorboardRun's. If any data fail to be ingested, an error is returned.

Module: googleapis.aiplatform.v1.projects.locations.tensorboards.experiments.runs

Functions
`batchCreate`	Batch create TensorboardRuns.
`create`	Creates a TensorboardRun.
`delete`	Deletes a TensorboardRun.
`get`	Gets a TensorboardRun.
`list`	Lists TensorboardRuns in a Location.
`patch`	Updates a TensorboardRun.
`write`	Write time series data points into multiple TensorboardTimeSeries under a TensorboardRun. If any data fail to be ingested, an error is returned.

Module: googleapis.aiplatform.v1.projects.locations.tensorboards.experiments.runs.timeSeries

Functions
`create`	Creates a TensorboardTimeSeries.
`delete`	Deletes a TensorboardTimeSeries.
`exportTensorboardTimeSeries`	Exports a TensorboardTimeSeries' data. Data is returned in paginated responses.
`get`	Gets a TensorboardTimeSeries.
`list`	Lists TensorboardTimeSeries in a Location.
`patch`	Updates a TensorboardTimeSeries.
`read`	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.
`readBlobData`	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.

Module: googleapis.aiplatform.v1.projects.locations.trainingPipelines

Functions
`cancel`	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`.
`create`	Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run.
`delete`	Deletes a TrainingPipeline.
`get`	Gets a TrainingPipeline.
`list`	Lists TrainingPipelines in a Location.

Module: googleapis.aiplatform.v1.projects.locations.tuningJobs

Functions
`cancel`	Cancels a TuningJob. Starts asynchronous cancellation on the TuningJob. 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 TuningJob is not deleted; instead it becomes a job with a TuningJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and TuningJob.state is set to `CANCELLED`.
`create`	Creates a TuningJob. A created TuningJob right away will be attempted to be run.
`get`	Gets a TuningJob.
`list`	Lists TuningJobs in a Location.

Module: googleapis.aiplatform.v1beta1.media

Functions
`upload`	Upload a file into a RagCorpus.

Module: googleapis.aiplatform.v1beta1.projects

Functions
`getCacheConfig`	Gets a GenAI cache config.
`updateCacheConfig`	Updates a cache config.

Module: googleapis.aiplatform.v1beta1.projects.locations

Functions
`evaluateInstances`	Evaluates instances based on a given metric.
`retrieveContexts`	Retrieves relevant contexts for a query.

Module: googleapis.aiplatform.v1beta1.projects.locations.batchPredictionJobs

Functions
`cancel`	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.
`create`	Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start.
`delete`	Deletes a BatchPredictionJob. Can only be called on jobs that already finished.
`get`	Gets a BatchPredictionJob
`list`	Lists BatchPredictionJobs in a Location.

Module: googleapis.aiplatform.v1beta1.projects.locations.customJobs

Functions
`cancel`	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`.
`create`	Creates a CustomJob. A created CustomJob right away will be attempted to be run.
`delete`	Deletes a CustomJob.
`get`	Gets a CustomJob.
`list`	Lists CustomJobs in a Location.

Module: googleapis.aiplatform.v1beta1.projects.locations.dataLabelingJobs

Functions
`cancel`	Cancels a DataLabelingJob. Success of cancellation is not guaranteed.
`create`	Creates a DataLabelingJob.
`delete`	Deletes a DataLabelingJob.
`get`	Gets a DataLabelingJob.
`list`	Lists DataLabelingJobs in a Location.

Module: googleapis.aiplatform.v1beta1.projects.locations.datasets

Functions
`create`	Creates a Dataset.
`delete`	Deletes a Dataset.
`export`	Exports data from a Dataset.
`get`	Gets a Dataset.
`list`	Lists Datasets in a Location.
`patch`	Updates a Dataset.
`searchDataItems`	Searches DataItems in a Dataset.

Module: googleapis.aiplatform.v1beta1.projects.locations.datasets.annotationSpecs

Functions
`get`	Gets an AnnotationSpec.

Module: googleapis.aiplatform.v1beta1.projects.locations.datasets.dataItems

Functions
`list`	Lists DataItems in a Dataset.

Module: googleapis.aiplatform.v1beta1.projects.locations.datasets.dataItems.annotations

Functions
`list`	Lists Annotations belongs to a dataitem

Module: googleapis.aiplatform.v1beta1.projects.locations.datasets.datasetVersions

Functions
`create`	Create a version from a Dataset.
`delete`	Deletes a Dataset version.
`get`	Gets a Dataset version.
`list`	Lists DatasetVersions in a Dataset.
`restore`	Restores a dataset version.

Module: googleapis.aiplatform.v1beta1.projects.locations.datasets.savedQueries

Functions
`delete`	Deletes a SavedQuery.
`list`	Lists SavedQueries in a Dataset.

Module: googleapis.aiplatform.v1beta1.projects.locations.deploymentResourcePools

Functions
`create`	Create a DeploymentResourcePool.
`delete`	Delete a DeploymentResourcePool.
`get`	Get a DeploymentResourcePool.
`list`	List DeploymentResourcePools in a location.
`queryDeployedModels`	List DeployedModels that have been deployed on this DeploymentResourcePool.

Module: googleapis.aiplatform.v1beta1.projects.locations.endpoints

Functions
`countTokens`	Perform a token counting.
`create`	Creates an Endpoint.
`delete`	Deletes an Endpoint.
`deployModel`	Deploys a Model into this Endpoint, creating a DeployedModel within it.
`explain`	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.
`generateContent`	Generate content with multimodal inputs.
`get`	Gets an Endpoint.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`list`	Lists Endpoints in a Location.
`mutateDeployedModel`	Updates an existing deployed model. Updatable fields include `min_replica_count`, `max_replica_count`, `autoscaling_metric_specs`, `disable_container_logging` (v1 only), and `enable_container_logging` (v1beta1 only).
`patch`	Updates an Endpoint.
`predict`	Perform an online prediction.
`rawPredict`	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.
`serverStreamingPredict`	Perform a server-side streaming online prediction request for Vertex LLM streaming.
`setIamPolicy`	Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
`streamGenerateContent`	Generate content with multimodal inputs with streaming support.
`testIamPermissions`	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.
`undeployModel`	Undeploys a Model from an Endpoint, removing a DeployedModel from it, and freeing all resources it's using.

Module: googleapis.aiplatform.v1beta1.projects.locations.extensions

Functions
`delete`	Deletes an Extension.
`get`	Gets an Extension.
`list`	Lists Extensions in a location.
`patch`	Updates an Extension.

Module: googleapis.aiplatform.v1beta1.projects.locations.featureGroups

Functions
`create`	Creates a new FeatureGroup in a given project and location.
`delete`	Deletes a single FeatureGroup.
`get`	Gets details of a single FeatureGroup.
`list`	Lists FeatureGroups in a given project and location.
`patch`	Updates the parameters of a single FeatureGroup.

Module: googleapis.aiplatform.v1beta1.projects.locations.featureGroups.features

Functions
`create`	Creates a new Feature in a given FeatureGroup.
`delete`	Deletes a single Feature.
`get`	Gets details of a single Feature.
`list`	Lists Features in a given FeatureGroup.
`patch`	Updates the parameters of a single Feature.

Module: googleapis.aiplatform.v1beta1.projects.locations.featureOnlineStores

Functions
`create`	Creates a new FeatureOnlineStore in a given project and location.
`delete`	Deletes a single FeatureOnlineStore. The FeatureOnlineStore must not contain any FeatureViews.
`get`	Gets details of a single FeatureOnlineStore.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`list`	Lists FeatureOnlineStores in a given project and location.
`patch`	Updates the parameters of a single FeatureOnlineStore.
`setIamPolicy`	Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
`testIamPermissions`	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.

Module: googleapis.aiplatform.v1beta1.projects.locations.featureOnlineStores.featureViews

Functions
`create`	Creates a new FeatureView in a given FeatureOnlineStore.
`delete`	Deletes a single FeatureView.
`fetchFeatureValues`	Fetch feature values under a FeatureView.
`get`	Gets details of a single FeatureView.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`list`	Lists FeatureViews in a given FeatureOnlineStore.
`patch`	Updates the parameters of a single FeatureView.
`searchNearestEntities`	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.
`setIamPolicy`	Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
`streamingFetchFeatureValues`	Bidirectional streaming RPC to fetch feature values under a FeatureView. Requests may not have a one-to-one mapping to responses and responses may be returned out-of-order to reduce latency.
`sync`	Triggers on-demand sync for the FeatureView.
`testIamPermissions`	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.

Module: googleapis.aiplatform.v1beta1.projects.locations.featureOnlineStores.featureViews.featureViewSyncs

Functions
`get`	Gets details of a single FeatureViewSync.
`list`	Lists FeatureViewSyncs in a given FeatureView.

Module: googleapis.aiplatform.v1beta1.projects.locations.featurestores

Functions
`batchReadFeatureValues`	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.
`create`	Creates a new Featurestore in a given project and location.
`delete`	Deletes a single Featurestore. The Featurestore must not contain any EntityTypes or `force` must be set to true for the request to succeed.
`get`	Gets details of a single Featurestore.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`list`	Lists Featurestores in a given project and location.
`patch`	Updates the parameters of a single Featurestore.
`searchFeatures`	Searches Features matching a query in a given project.
`setIamPolicy`	Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
`testIamPermissions`	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.

Module: googleapis.aiplatform.v1beta1.projects.locations.featurestores.entityTypes

Functions
`create`	Creates a new EntityType in a given Featurestore.
`delete`	Deletes a single EntityType. The EntityType must not have any Features or `force` must be set to true for the request to succeed.
`deleteFeatureValues`	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.
`exportFeatureValues`	Exports Feature values from all the entities of a target EntityType.
`get`	Gets details of a single EntityType.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`importFeatureValues`	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.
`list`	Lists EntityTypes in a given Featurestore.
`patch`	Updates the parameters of a single EntityType.
`readFeatureValues`	Reads Feature values of a specific entity of an EntityType. For reading feature values of multiple entities of an EntityType, please use StreamingReadFeatureValues.
`setIamPolicy`	Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
`streamingReadFeatureValues`	Reads Feature values for multiple entities. Depending on their size, data for different entities may be broken up across multiple responses.
`testIamPermissions`	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.
`writeFeatureValues`	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.

Module: googleapis.aiplatform.v1beta1.projects.locations.featurestores.entityTypes.features

Functions
`batchCreate`	Creates a batch of Features in a given EntityType.
`create`	Creates a new Feature in a given EntityType.
`delete`	Deletes a single Feature.
`get`	Gets details of a single Feature.
`list`	Lists Features in a given EntityType.
`patch`	Updates the parameters of a single Feature.

Module: googleapis.aiplatform.v1beta1.projects.locations.hyperparameterTuningJobs

Functions
`cancel`	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`.
`create`	Creates a HyperparameterTuningJob
`delete`	Deletes a HyperparameterTuningJob.
`get`	Gets a HyperparameterTuningJob
`list`	Lists HyperparameterTuningJobs in a Location.

Module: googleapis.aiplatform.v1beta1.projects.locations.indexEndpoints

Functions
`create`	Creates an IndexEndpoint.
`delete`	Deletes an IndexEndpoint.
`deployIndex`	Deploys an Index into this IndexEndpoint, creating a DeployedIndex within it. Only non-empty Indexes can be deployed.
`get`	Gets an IndexEndpoint.
`list`	Lists IndexEndpoints in a Location.
`mutateDeployedIndex`	Update an existing DeployedIndex under an IndexEndpoint.
`patch`	Updates an IndexEndpoint.
`undeployIndex`	Undeploys an Index from an IndexEndpoint, removing a DeployedIndex from it, and freeing all resources it's using.

Module: googleapis.aiplatform.v1beta1.projects.locations.indexes

Functions
`create`	Creates an Index.
`delete`	Deletes an Index. An Index can only be deleted when all its DeployedIndexes had been undeployed.
`get`	Gets an Index.
`list`	Lists Indexes in a Location.
`patch`	Updates an Index.
`removeDatapoints`	Remove Datapoints from an Index.
`upsertDatapoints`	Add/update Datapoints into an Index.

Module: googleapis.aiplatform.v1beta1.projects.locations.metadataStores

Functions
`create`	Initializes a MetadataStore, including allocation of resources.
`delete`	Deletes a single MetadataStore and all its child resources (Artifacts, Executions, and Contexts).
`get`	Retrieves a specific MetadataStore.
`list`	Lists MetadataStores for a Location.

Module: googleapis.aiplatform.v1beta1.projects.locations.metadataStores.artifacts

Functions
`create`	Creates an Artifact associated with a MetadataStore.
`delete`	Deletes an Artifact.
`get`	Retrieves a specific Artifact.
`list`	Lists Artifacts in the MetadataStore.
`patch`	Updates a stored Artifact.
`purge`	Purges Artifacts.
`queryArtifactLineageSubgraph`	Retrieves lineage of an Artifact represented through Artifacts and Executions connected by Event edges and returned as a LineageSubgraph.

Module: googleapis.aiplatform.v1beta1.projects.locations.metadataStores.contexts

Functions
`addContextArtifactsAndExecutions`	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.
`addContextChildren`	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.
`create`	Creates a Context associated with a MetadataStore.
`delete`	Deletes a stored Context.
`get`	Retrieves a specific Context.
`list`	Lists Contexts on the MetadataStore.
`patch`	Updates a stored Context.
`purge`	Purges Contexts.
`queryContextLineageSubgraph`	Retrieves Artifacts and Executions within the specified Context, connected by Event edges and returned as a LineageSubgraph.
`removeContextChildren`	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.

Module: googleapis.aiplatform.v1beta1.projects.locations.metadataStores.executions

Functions
`addExecutionEvents`	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.
`create`	Creates an Execution associated with a MetadataStore.
`delete`	Deletes an Execution.
`get`	Retrieves a specific Execution.
`list`	Lists Executions in the MetadataStore.
`patch`	Updates a stored Execution.
`purge`	Purges Executions.
`queryExecutionInputsAndOutputs`	Obtains the set of input and output Artifacts for this Execution, in the form of LineageSubgraph that also contains the Execution and connecting Events.

Module: googleapis.aiplatform.v1beta1.projects.locations.metadataStores.metadataSchemas

Functions
`create`	Creates a MetadataSchema.
`get`	Retrieves a specific MetadataSchema.
`list`	Lists MetadataSchemas.

Module: googleapis.aiplatform.v1beta1.projects.locations.migratableResources

Functions
`batchMigrate`	Batch migrates resources from ml.googleapis.com, automl.googleapis.com, and datalabeling.googleapis.com to Vertex AI.
`search`	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.

Module: googleapis.aiplatform.v1beta1.projects.locations.modelDeploymentMonitoringJobs

Functions
`create`	Creates a ModelDeploymentMonitoringJob. It will run periodically on a configured interval.
`delete`	Deletes a ModelDeploymentMonitoringJob.
`get`	Gets a ModelDeploymentMonitoringJob.
`list`	Lists ModelDeploymentMonitoringJobs in a Location.
`patch`	Updates a ModelDeploymentMonitoringJob.
`pause`	Pauses a ModelDeploymentMonitoringJob. If the job is running, the server makes a best effort to cancel the job. Will mark ModelDeploymentMonitoringJob.state to 'PAUSED'.
`resume`	Resumes a paused ModelDeploymentMonitoringJob. It will start to run from next scheduled time. A deleted ModelDeploymentMonitoringJob can't be resumed.
`searchModelDeploymentMonitoringStatsAnomalies`	Searches Model Monitoring Statistics generated within a given time window.

Module: googleapis.aiplatform.v1beta1.projects.locations.modelMonitors

Functions
`create`	Creates a ModelMonitor.
`delete`	Deletes a ModelMonitor.
`get`	Gets a ModelMonitor.
`list`	Lists ModelMonitors in a Location.
`patch`	Updates a ModelMonitor.
`searchModelMonitoringAlerts`	Returns the Model Monitoring alerts.
`searchModelMonitoringStats`	Searches Model Monitoring Stats generated within a given time window.

Module: googleapis.aiplatform.v1beta1.projects.locations.modelMonitors.modelMonitoringJobs

Functions
`create`	Creates a ModelMonitoringJob.
`delete`	Deletes a ModelMonitoringJob.
`get`	Gets a ModelMonitoringJob.
`list`	Lists ModelMonitoringJobs. Callers may choose to read across multiple Monitors as per AIP-159 by using '-' (the hyphen or dash character) as a wildcard character instead of modelMonitor id in the parent. Format `projects/{project_id}/locations/{location}/moodelMonitors/-/modelMonitoringJobs`

Module: googleapis.aiplatform.v1beta1.projects.locations.models

Functions
`copy`	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.
`delete`	Deletes a Model. A model cannot be deleted if any Endpoint resource has a DeployedModel based on the model in its deployed_models field.
`deleteVersion`	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.
`export`	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.
`get`	Gets a Model.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`list`	Lists Models in a Location.
`listVersions`	Lists versions of the specified model.
`mergeVersionAliases`	Merges a set of aliases for a Model version.
`patch`	Updates a Model.
`setIamPolicy`	Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
`testIamPermissions`	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.
`updateExplanationDataset`	Incrementally update the dataset used for an examples model.
`upload`	Uploads a Model artifact into Vertex AI.

Module: googleapis.aiplatform.v1beta1.projects.locations.models.evaluations

Functions
`get`	Gets a ModelEvaluation.
`list`	Lists ModelEvaluations in a Model.

Module: googleapis.aiplatform.v1beta1.projects.locations.models.evaluations.slices

Functions
`batchImport`	Imports a list of externally generated EvaluatedAnnotations.
`get`	Gets a ModelEvaluationSlice.
`list`	Lists ModelEvaluationSlices in a ModelEvaluation.

Module: googleapis.aiplatform.v1beta1.projects.locations.notebookRuntimeTemplates

Functions
`create`	Creates a NotebookRuntimeTemplate.
`delete`	Deletes a NotebookRuntimeTemplate.
`get`	Gets a NotebookRuntimeTemplate.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`list`	Lists NotebookRuntimeTemplates in a Location.
`setIamPolicy`	Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
`testIamPermissions`	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.

Module: googleapis.aiplatform.v1beta1.projects.locations.notebookRuntimes

Functions
`assign`	Assigns a NotebookRuntime to a user for a particular Notebook file. This method will either returns an existing assignment or generates a new one.
`delete`	Deletes a NotebookRuntime.
`get`	Gets a NotebookRuntime.
`list`	Lists NotebookRuntimes in a Location.
`start`	Starts a NotebookRuntime.

Module: googleapis.aiplatform.v1beta1.projects.locations.operations

Functions
`cancel`	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`	Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
`get`	Gets the latest 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`	Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.
`wait`	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.

Module: googleapis.aiplatform.v1beta1.projects.locations.persistentResources

Functions
`create`	Creates a PersistentResource.
`delete`	Deletes a PersistentResource.
`get`	Gets a PersistentResource.
`list`	Lists PersistentResources in a Location.
`patch`	Updates a PersistentResource.
`reboot`	Reboots a PersistentResource.

Module: googleapis.aiplatform.v1beta1.projects.locations.pipelineJobs

Functions
`batchCancel`	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.
`batchDelete`	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.
`cancel`	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`	Creates a PipelineJob. A PipelineJob will run immediately when created.
`delete`	Deletes a PipelineJob.
`get`	Gets a PipelineJob.
`list`	Lists PipelineJobs in a Location.

Module: googleapis.aiplatform.v1beta1.projects.locations.publishers.models

Functions
`countTokens`	Perform a token counting.
`generateContent`	Generate content with multimodal inputs.
`getIamPolicy`	Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
`predict`	Perform an online prediction.
`rawPredict`	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.
`serverStreamingPredict`	Perform a server-side streaming online prediction request for Vertex LLM streaming.
`streamGenerateContent`	Generate content with multimodal inputs with streaming support.

Module: googleapis.aiplatform.v1beta1.projects.locations.ragCorpora

Functions
`create`	Creates a RagCorpus.
`delete`	Deletes a RagCorpus.
`get`	Gets a RagCorpus.
`list`	Lists RagCorpora in a Location.

Module: googleapis.aiplatform.v1beta1.projects.locations.ragCorpora.ragFiles

Functions
`delete`	Deletes a RagFile.
`get`	Gets a RagFile.
`list`	Lists RagFiles in a RagCorpus.

Module: googleapis.aiplatform.v1beta1.projects.locations.reasoningEngines

Functions
`create`	Creates a reasoning engine.
`delete`	Deletes a reasoning engine.
`get`	Gets a reasoning engine.
`list`	Lists reasoning engines in a location.
`query`	Queries using a reasoning engine.

Module: googleapis.aiplatform.v1beta1.projects.locations.schedules

Functions
`create`	Creates a Schedule.
`delete`	Deletes a Schedule.
`get`	Gets a Schedule.
`list`	Lists Schedules in a Location.
`patch`	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.
`pause`	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.
`resume`	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.catchUp is set up true, all missed runs will be scheduled for backfill first.

Module: googleapis.aiplatform.v1beta1.projects.locations.specialistPools

Functions
`create`	Creates a SpecialistPool.
`delete`	Deletes a SpecialistPool as well as all Specialists in the pool.
`get`	Gets a SpecialistPool.
`list`	Lists SpecialistPools in a Location.
`patch`	Updates a SpecialistPool.

Module: googleapis.aiplatform.v1beta1.projects.locations.studies

Functions
`create`	Creates a Study. A resource name will be generated after creation of the Study.
`delete`	Deletes a Study.
`get`	Gets a Study by name.
`list`	Lists all the studies in a region for an associated project.
`lookup`	Looks a study up using the user-defined display_name field instead of the fully qualified resource name.

Module: googleapis.aiplatform.v1beta1.projects.locations.studies.trials

Functions
`addTrialMeasurement`	Adds a measurement of the objective metrics to a Trial. This measurement is assumed to have been taken before the Trial is complete.
`checkTrialEarlyStoppingState`	Checks whether a Trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.
`complete`	Marks a Trial as complete.
`create`	Adds a user provided Trial to a Study.
`delete`	Deletes a Trial.
`get`	Gets a Trial.
`list`	Lists the Trials associated with a Study.
`listOptimalTrials`	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
`stop`	Stops a Trial.
`suggest`	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.

Module: googleapis.aiplatform.v1beta1.projects.locations.tensorboards

Functions
`batchRead`	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.
`create`	Creates a Tensorboard.
`delete`	Deletes a Tensorboard.
`get`	Gets a Tensorboard.
`list`	Lists Tensorboards in a Location.
`patch`	Updates a Tensorboard.
`readSize`	Returns the storage size for a given TensorBoard instance.
`readUsage`	Returns a list of monthly active users for a given TensorBoard instance.

Module: googleapis.aiplatform.v1beta1.projects.locations.tensorboards.experiments

Functions
`batchCreate`	Batch create TensorboardTimeSeries that belong to a TensorboardExperiment.
`create`	Creates a TensorboardExperiment.
`delete`	Deletes a TensorboardExperiment.
`get`	Gets a TensorboardExperiment.
`list`	Lists TensorboardExperiments in a Location.
`patch`	Updates a TensorboardExperiment.
`write`	Write time series data points of multiple TensorboardTimeSeries in multiple TensorboardRun's. If any data fail to be ingested, an error is returned.

Module: googleapis.aiplatform.v1beta1.projects.locations.tensorboards.experiments.runs

Functions
`batchCreate`	Batch create TensorboardRuns.
`create`	Creates a TensorboardRun.
`delete`	Deletes a TensorboardRun.
`get`	Gets a TensorboardRun.
`list`	Lists TensorboardRuns in a Location.
`patch`	Updates a TensorboardRun.
`write`	Write time series data points into multiple TensorboardTimeSeries under a TensorboardRun. If any data fail to be ingested, an error is returned.

Module: googleapis.aiplatform.v1beta1.projects.locations.tensorboards.experiments.runs.timeSeries

Functions
`create`	Creates a TensorboardTimeSeries.
`delete`	Deletes a TensorboardTimeSeries.
`exportTensorboardTimeSeries`	Exports a TensorboardTimeSeries' data. Data is returned in paginated responses.
`get`	Gets a TensorboardTimeSeries.
`list`	Lists TensorboardTimeSeries in a Location.
`patch`	Updates a TensorboardTimeSeries.
`read`	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.
`readBlobData`	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.

Module: googleapis.aiplatform.v1beta1.projects.locations.trainingPipelines

Functions
`cancel`	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`.
`create`	Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run.
`delete`	Deletes a TrainingPipeline.
`get`	Gets a TrainingPipeline.
`list`	Lists TrainingPipelines in a Location.

Module: googleapis.aiplatform.v1beta1.projects.locations.tuningJobs

Functions
`cancel`	Cancels a TuningJob. Starts asynchronous cancellation on the TuningJob. 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 TuningJob is not deleted; instead it becomes a job with a TuningJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and TuningJob.state is set to `CANCELLED`.
`create`	Creates a TuningJob. A created TuningJob right away will be attempted to be run.
`get`	Gets a TuningJob.
`list`	Lists TuningJobs in a Location.