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.

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

JSON

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.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.

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.

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.

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.

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.

Functions
upload	Upload a file into a RagCorpus.

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.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.

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.

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.

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.

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.