Class PredictionServiceClient (1.52.0) 

PredictionServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1beta1.services.prediction_service.transports.base.PredictionServiceTransport, typing.Callable[[...], google.cloud.aiplatform_v1beta1.services.prediction_service.transports.base.PredictionServiceTransport]]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

A service for online predictions and explanations.

Properties

api_endpoint

Return the API endpoint used by the client instance.

Returns
Type Description
str The API endpoint used by the client instance.

transport

Returns the transport used by the client instance.

Returns
Type Description
PredictionServiceTransport The transport used by the client instance.

universe_domain

Return the universe domain used by the client instance.

Returns
Type Description
str The universe domain used by the client instance.

Methods

PredictionServiceClient

PredictionServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1beta1.services.prediction_service.transports.base.PredictionServiceTransport, typing.Callable[[...], google.cloud.aiplatform_v1beta1.services.prediction_service.transports.base.PredictionServiceTransport]]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Instantiates the prediction service client.

Parameters
Name Description
credentials Optional[google.auth.credentials.Credentials]

The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.
transport Optional[Union[str,PredictionServiceTransport,Callable[..., PredictionServiceTransport]]]

The transport to use, or a Callable that constructs and returns a new transport. If a Callable is given, it will be called with the same set of initialization arguments as used in the PredictionServiceTransport constructor. If set to None, a transport is chosen automatically. NOTE: "rest" transport functionality is currently in a beta state (preview). We welcome your feedback via an issue in this library's source repository.
client_options Optional[Union[google.api_core.client_options.ClientOptions, dict]]

Custom options for the client. 1. The api_endpoint property can be used to override the default endpoint provided by the client when transport is not explicitly provided. Only if this property is not set and transport was not explicitly provided, the endpoint is determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment variable, which have one of the following values: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto-switch to the default mTLS endpoint if client certificate is present; this is the default value). 2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the client_cert_source property can be used to provide a client certificate for mTLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used. 3. The universe_domain property can be used to override the default "googleapis.com" universe. Note that the api_endpoint property still takes precedence; and universe_domain is currently not supported for mTLS.
client_info google.api_core.gapic_v1.client_info.ClientInfo

The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you're developing your own client library.
Exceptions
Type Description
google.auth.exceptions.MutualTLSChannelError If mutual TLS transport creation failed for any reason.

__exit__

__exit__(type, value, traceback)

Releases underlying transport's resources.

cancel_operation

cancel_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.CancelOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

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.

Parameters
Name Description
request .operations_pb2.CancelOperationRequest

The request object. Request message for CancelOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

common_billing_account_path

common_billing_account_path(billing_account: str) -> str

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str) -> str

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str) -> str

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str) -> str

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str) -> str

Returns a fully-qualified project string.

count_tokens

count_tokens(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.prediction_service.CountTokensRequest,
            dict,
        ]
    ] = None,
    *,
    endpoint: typing.Optional[str] = None,
    instances: typing.Optional[
        typing.MutableSequence[google.protobuf.struct_pb2.Value]
    ] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.prediction_service.CountTokensResponse

Perform a token counting.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_count_tokens():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    instances = aiplatform_v1beta1.Value()
    instances.null_value = "NULL_VALUE"

    contents = aiplatform_v1beta1.Content()
    contents.parts.text = "text_value"

    request = aiplatform_v1beta1.CountTokensRequest(
        endpoint="endpoint_value",
        model="model_value",
        instances=instances,
        contents=contents,
    )

    # Make the request
    response = client.count_tokens(request=request)

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.CountTokensRequest, dict]

The request object. Request message for PredictionService.CountTokens.
endpoint str

Required. The name of the Endpoint requested to perform token counting. Format: projects/{project}/locations/{location}/endpoints/{endpoint} This corresponds to the endpoint field on the request instance; if request is provided, this should not be set.
instances MutableSequence[google.protobuf.struct_pb2.Value]

Required. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model. This corresponds to the instances field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1beta1.types.CountTokensResponse Response message for PredictionService.CountTokens.

delete_operation

delete_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.DeleteOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

Deletes a long-running operation.

This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters
Name Description
request .operations_pb2.DeleteOperationRequest

The request object. Request message for DeleteOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

direct_predict

direct_predict(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.prediction_service.DirectPredictRequest,
            dict,
        ]
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.prediction_service.DirectPredictResponse

Perform an unary online prediction request to a gRPC model server for Vertex first-party products and frameworks.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_direct_predict():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.DirectPredictRequest(
        endpoint="endpoint_value",
    )

    # Make the request
    response = client.direct_predict(request=request)

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.DirectPredictRequest, dict]

The request object. Request message for PredictionService.DirectPredict.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1beta1.types.DirectPredictResponse Response message for PredictionService.DirectPredict.

direct_raw_predict

direct_raw_predict(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.prediction_service.DirectRawPredictRequest,
            dict,
        ]
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.prediction_service.DirectRawPredictResponse

Perform an unary online prediction request to a gRPC model server for custom containers.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_direct_raw_predict():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.DirectRawPredictRequest(
        endpoint="endpoint_value",
    )

    # Make the request
    response = client.direct_raw_predict(request=request)

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.DirectRawPredictRequest, dict]

The request object. Request message for PredictionService.DirectRawPredict.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1beta1.types.DirectRawPredictResponse Response message for PredictionService.DirectRawPredict.

endpoint_path

endpoint_path(project: str, location: str, endpoint: str) -> str

Returns a fully-qualified endpoint string.

explain

explain(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.prediction_service.ExplainRequest,
            dict,
        ]
    ] = None,
    *,
    endpoint: typing.Optional[str] = None,
    instances: typing.Optional[
        typing.MutableSequence[google.protobuf.struct_pb2.Value]
    ] = None,
    parameters: typing.Optional[google.protobuf.struct_pb2.Value] = None,
    deployed_model_id: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.prediction_service.ExplainResponse

Perform an online explanation.

If xref_deployed_model_id is specified, the corresponding DeployModel must have xref_explanation_spec populated. If xref_deployed_model_id is not specified, all DeployedModels must have xref_explanation_spec populated.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_explain():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    instances = aiplatform_v1beta1.Value()
    instances.null_value = "NULL_VALUE"

    request = aiplatform_v1beta1.ExplainRequest(
        endpoint="endpoint_value",
        instances=instances,
    )

    # Make the request
    response = client.explain(request=request)

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.ExplainRequest, dict]

The request object. Request message for PredictionService.Explain.
endpoint str

Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint} This corresponds to the endpoint field on the request instance; if request is provided, this should not be set.
instances MutableSequence[google.protobuf.struct_pb2.Value]

Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] instance_schema_uri. This corresponds to the instances field on the request instance; if request is provided, this should not be set.
parameters google.protobuf.struct_pb2.Value

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] parameters_schema_uri. This corresponds to the parameters field on the request instance; if request is provided, this should not be set.
deployed_model_id str

If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split. This corresponds to the deployed_model_id field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1beta1.types.ExplainResponse Response message for PredictionService.Explain.

from_service_account_file

from_service_account_file(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter
Name Description
filename str

The path to the service account private key json file.
Returns
Type Description
PredictionServiceClient The constructed client.

from_service_account_info

from_service_account_info(info: dict, *args, **kwargs)

Creates an instance of this client using the provided credentials info.

Parameter
Name Description
info dict

The service account private key info.
Returns
Type Description
PredictionServiceClient The constructed client.

from_service_account_json

from_service_account_json(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter
Name Description
filename str

The path to the service account private key json file.
Returns
Type Description
PredictionServiceClient The constructed client.

generate_content

generate_content(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.prediction_service.GenerateContentRequest,
            dict,
        ]
    ] = None,
    *,
    model: typing.Optional[str] = None,
    contents: typing.Optional[
        typing.MutableSequence[google.cloud.aiplatform_v1beta1.types.content.Content]
    ] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.prediction_service.GenerateContentResponse

Generate content with multimodal inputs.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_generate_content():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    contents = aiplatform_v1beta1.Content()
    contents.parts.text = "text_value"

    request = aiplatform_v1beta1.GenerateContentRequest(
        model="model_value",
        contents=contents,
    )

    # Make the request
    response = client.generate_content(request=request)

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.GenerateContentRequest, dict]

The request object. Request message for [PredictionService.GenerateContent].
model str

Required. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers//models/ This corresponds to the model field on the request instance; if request is provided, this should not be set.
contents MutableSequence[google.cloud.aiplatform_v1beta1.types.Content]

Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request. This corresponds to the contents field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1beta1.types.GenerateContentResponse Response message for [PredictionService.GenerateContent].

get_iam_policy

get_iam_policy(
    request: typing.Optional[google.iam.v1.iam_policy_pb2.GetIamPolicyRequest] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy

Gets the IAM access control policy for a function.

Returns an empty policy if the function exists and does not have a policy set.

Parameters
Name Description
request .iam_policy_pb2.GetIamPolicyRequest

The request object. Request message for GetIamPolicy method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.policy_pb2.Policy Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:eve@example.com"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:mike@example.com="" -="" group:admins@example.com="" -="" domain:google.com="" -="" serviceaccount:my-project-id@appspot.gserviceaccount.com="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:eve@example.com="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __.

get_location

get_location(
    request: typing.Optional[
        google.cloud.location.locations_pb2.GetLocationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.Location

Gets information about a location.

Parameters
Name Description
request .location_pb2.GetLocationRequest

The request object. Request message for GetLocation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.location_pb2.Location Location object.

get_mtls_endpoint_and_cert_source

get_mtls_endpoint_and_cert_source(
    client_options: typing.Optional[
        google.api_core.client_options.ClientOptions
    ] = None,
)

Deprecated. Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variable is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameter
Name Description
client_options google.api_core.client_options.ClientOptions

Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.
Exceptions
Type Description
google.auth.exceptions.MutualTLSChannelError If any errors happen.
Returns
Type Description
Tuple[str, Callable[[], Tuple[bytes, bytes]]] returns the API endpoint and the client cert source to use.

get_operation

get_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.GetOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation

Gets the latest state of a long-running operation.

Parameters
Name Description
request .operations_pb2.GetOperationRequest

The request object. Request message for GetOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.operations_pb2.Operation An Operation object.

list_locations

list_locations(
    request: typing.Optional[
        google.cloud.location.locations_pb2.ListLocationsRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.ListLocationsResponse

Lists information about the supported locations for this service.

Parameters
Name Description
request .location_pb2.ListLocationsRequest

The request object. Request message for ListLocations method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.location_pb2.ListLocationsResponse Response message for ListLocations method.

list_operations

list_operations(
    request: typing.Optional[
        google.longrunning.operations_pb2.ListOperationsRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.ListOperationsResponse

Lists operations that match the specified filter in the request.

Parameters
Name Description
request .operations_pb2.ListOperationsRequest

The request object. Request message for ListOperations method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.operations_pb2.ListOperationsResponse Response message for ListOperations method.

model_path

model_path(project: str, location: str, model: str) -> str

Returns a fully-qualified model string.

parse_common_billing_account_path

parse_common_billing_account_path(path: str) -> typing.Dict[str, str]

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str) -> typing.Dict[str, str]

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str) -> typing.Dict[str, str]

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str) -> typing.Dict[str, str]

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str) -> typing.Dict[str, str]

Parse a project path into its component segments.

parse_endpoint_path

parse_endpoint_path(path: str) -> typing.Dict[str, str]

Parses a endpoint path into its component segments.

parse_model_path

parse_model_path(path: str) -> typing.Dict[str, str]

Parses a model path into its component segments.

parse_rag_corpus_path

parse_rag_corpus_path(path: str) -> typing.Dict[str, str]

Parses a rag_corpus path into its component segments.

predict

predict(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.prediction_service.PredictRequest,
            dict,
        ]
    ] = None,
    *,
    endpoint: typing.Optional[str] = None,
    instances: typing.Optional[
        typing.MutableSequence[google.protobuf.struct_pb2.Value]
    ] = None,
    parameters: typing.Optional[google.protobuf.struct_pb2.Value] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.prediction_service.PredictResponse

Perform an online prediction.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_predict():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    instances = aiplatform_v1beta1.Value()
    instances.null_value = "NULL_VALUE"

    request = aiplatform_v1beta1.PredictRequest(
        endpoint="endpoint_value",
        instances=instances,
    )

    # Make the request
    response = client.predict(request=request)

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.PredictRequest, dict]

The request object. Request message for PredictionService.Predict.
endpoint str

Required. The name of the Endpoint requested to serve the prediction. Format: projects/{project}/locations/{location}/endpoints/{endpoint} This corresponds to the endpoint field on the request instance; if request is provided, this should not be set.
instances MutableSequence[google.protobuf.struct_pb2.Value]

Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] instance_schema_uri. This corresponds to the instances field on the request instance; if request is provided, this should not be set.
parameters google.protobuf.struct_pb2.Value

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] parameters_schema_uri. This corresponds to the parameters field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1beta1.types.PredictResponse Response message for PredictionService.Predict.

rag_corpus_path

rag_corpus_path(project: str, location: str, rag_corpus: str) -> str

Returns a fully-qualified rag_corpus string.

raw_predict

raw_predict(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.prediction_service.RawPredictRequest,
            dict,
        ]
    ] = None,
    *,
    endpoint: typing.Optional[str] = None,
    http_body: typing.Optional[google.api.httpbody_pb2.HttpBody] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api.httpbody_pb2.HttpBody

Perform an online prediction with an arbitrary HTTP payload.

The response includes the following HTTP headers:

  • X-Vertex-AI-Endpoint-Id: ID of the xref_Endpoint that served this prediction.

  • X-Vertex-AI-Deployed-Model-Id: ID of the Endpoint's xref_DeployedModel that served this prediction.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_raw_predict():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.RawPredictRequest(
        endpoint="endpoint_value",
    )

    # Make the request
    response = client.raw_predict(request=request)

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.RawPredictRequest, dict]

The request object. Request message for PredictionService.RawPredict.
endpoint str

Required. The name of the Endpoint requested to serve the prediction. Format: projects/{project}/locations/{location}/endpoints/{endpoint} This corresponds to the endpoint field on the request instance; if request is provided, this should not be set.
http_body google.api.httpbody_pb2.HttpBody

The prediction input. Supports HTTP headers and arbitrary data payload. A DeployedModel may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the RawPredict method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the predict_schemata.instance_schema_uri field when you create a Model. This schema applies when you deploy the Model as a DeployedModel to an Endpoint and use the RawPredict method. This corresponds to the http_body field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.api.httpbody_pb2.HttpBody Message that represents an arbitrary HTTP body. It should only be used for payload formats that can't be represented as JSON, such as raw binary or an HTML page. This message can be used both in streaming and non-streaming API methods in the request as well as the response. It can be used as a top-level request field, which is convenient if one wants to extract parameters from either the URL or HTTP template into the request fields and also want access to the raw HTTP body. Example: message GetResourceRequest { // A unique request id. string request_id = 1; // The raw HTTP body is bound to this field. google.api.HttpBody http_body = 2; } service ResourceService { rpc GetResource(GetResourceRequest) returns (google.api.HttpBody); rpc UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); } Example with streaming methods: service CaldavService { rpc GetCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); rpc UpdateCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); } Use of this type only changes how the request and response bodies are handled, all other features will continue to work unchanged.

server_streaming_predict

server_streaming_predict(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.prediction_service.StreamingPredictRequest,
            dict,
        ]
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> typing.Iterable[
    google.cloud.aiplatform_v1beta1.types.prediction_service.StreamingPredictResponse
]

Perform a server-side streaming online prediction request for Vertex LLM streaming.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_server_streaming_predict():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.StreamingPredictRequest(
        endpoint="endpoint_value",
    )

    # Make the request
    stream = client.server_streaming_predict(request=request)

    # Handle the response
    for response in stream:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.StreamingPredictRequest, dict]

The request object. Request message for PredictionService.StreamingPredict. The first message must contain endpoint field and optionally [input][]. The subsequent messages must contain [input][].
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
Iterable[google.cloud.aiplatform_v1beta1.types.StreamingPredictResponse] Response message for PredictionService.StreamingPredict.

set_iam_policy

set_iam_policy(
    request: typing.Optional[google.iam.v1.iam_policy_pb2.SetIamPolicyRequest] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Parameters
Name Description
request .iam_policy_pb2.SetIamPolicyRequest

The request object. Request message for SetIamPolicy method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.policy_pb2.Policy Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:eve@example.com"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:mike@example.com="" -="" group:admins@example.com="" -="" domain:google.com="" -="" serviceaccount:my-project-id@appspot.gserviceaccount.com="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:eve@example.com="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __.

stream_direct_predict

stream_direct_predict(
    requests: typing.Optional[
        typing.Iterator[
            google.cloud.aiplatform_v1beta1.types.prediction_service.StreamDirectPredictRequest
        ]
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> typing.Iterable[
    google.cloud.aiplatform_v1beta1.types.prediction_service.StreamDirectPredictResponse
]

Perform a streaming online prediction request to a gRPC model server for Vertex first-party products and frameworks.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_stream_direct_predict():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.StreamDirectPredictRequest(
        endpoint="endpoint_value",
    )

    # This method expects an iterator which contains
    # 'aiplatform_v1beta1.StreamDirectPredictRequest' objects
    # Here we create a generator that yields a single `request` for
    # demonstrative purposes.
    requests = [request]

    def request_generator():
        for request in requests:
            yield request

    # Make the request
    stream = client.stream_direct_predict(requests=request_generator())

    # Handle the response
    for response in stream:
        print(response)
Parameters
Name Description
requests Iterator[google.cloud.aiplatform_v1beta1.types.StreamDirectPredictRequest]

The request object iterator. Request message for PredictionService.StreamDirectPredict. The first message must contain endpoint field and optionally [input][]. The subsequent messages must contain [input][].
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
Iterable[google.cloud.aiplatform_v1beta1.types.StreamDirectPredictResponse] Response message for PredictionService.StreamDirectPredict.

stream_direct_raw_predict

stream_direct_raw_predict(
    requests: typing.Optional[
        typing.Iterator[
            google.cloud.aiplatform_v1beta1.types.prediction_service.StreamDirectRawPredictRequest
        ]
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> typing.Iterable[
    google.cloud.aiplatform_v1beta1.types.prediction_service.StreamDirectRawPredictResponse
]

Perform a streaming online prediction request to a gRPC model server for custom containers.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_stream_direct_raw_predict():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.StreamDirectRawPredictRequest(
        endpoint="endpoint_value",
    )

    # This method expects an iterator which contains
    # 'aiplatform_v1beta1.StreamDirectRawPredictRequest' objects
    # Here we create a generator that yields a single `request` for
    # demonstrative purposes.
    requests = [request]

    def request_generator():
        for request in requests:
            yield request

    # Make the request
    stream = client.stream_direct_raw_predict(requests=request_generator())

    # Handle the response
    for response in stream:
        print(response)
Parameters
Name Description
requests Iterator[google.cloud.aiplatform_v1beta1.types.StreamDirectRawPredictRequest]

The request object iterator. Request message for PredictionService.StreamDirectRawPredict. The first message must contain endpoint and method_name fields and optionally input. The subsequent messages must contain input. method_name in the subsequent messages have no effect.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
Iterable[google.cloud.aiplatform_v1beta1.types.StreamDirectRawPredictResponse] Response message for PredictionService.StreamDirectRawPredict.

stream_generate_content

stream_generate_content(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.prediction_service.GenerateContentRequest,
            dict,
        ]
    ] = None,
    *,
    model: typing.Optional[str] = None,
    contents: typing.Optional[
        typing.MutableSequence[google.cloud.aiplatform_v1beta1.types.content.Content]
    ] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> typing.Iterable[
    google.cloud.aiplatform_v1beta1.types.prediction_service.GenerateContentResponse
]

Generate content with multimodal inputs with streaming support.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_stream_generate_content():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    contents = aiplatform_v1beta1.Content()
    contents.parts.text = "text_value"

    request = aiplatform_v1beta1.GenerateContentRequest(
        model="model_value",
        contents=contents,
    )

    # Make the request
    stream = client.stream_generate_content(request=request)

    # Handle the response
    for response in stream:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.GenerateContentRequest, dict]

The request object. Request message for [PredictionService.GenerateContent].
model str

Required. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers//models/ This corresponds to the model field on the request instance; if request is provided, this should not be set.
contents MutableSequence[google.cloud.aiplatform_v1beta1.types.Content]

Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request. This corresponds to the contents field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
Iterable[google.cloud.aiplatform_v1beta1.types.GenerateContentResponse] Response message for [PredictionService.GenerateContent].

streaming_predict

streaming_predict(
    requests: typing.Optional[
        typing.Iterator[
            google.cloud.aiplatform_v1beta1.types.prediction_service.StreamingPredictRequest
        ]
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> typing.Iterable[
    google.cloud.aiplatform_v1beta1.types.prediction_service.StreamingPredictResponse
]

Perform a streaming online prediction request for Vertex first-party products and frameworks.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_streaming_predict():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.StreamingPredictRequest(
        endpoint="endpoint_value",
    )

    # This method expects an iterator which contains
    # 'aiplatform_v1beta1.StreamingPredictRequest' objects
    # Here we create a generator that yields a single `request` for
    # demonstrative purposes.
    requests = [request]

    def request_generator():
        for request in requests:
            yield request

    # Make the request
    stream = client.streaming_predict(requests=request_generator())

    # Handle the response
    for response in stream:
        print(response)
Parameters
Name Description
requests Iterator[google.cloud.aiplatform_v1beta1.types.StreamingPredictRequest]

The request object iterator. Request message for PredictionService.StreamingPredict. The first message must contain endpoint field and optionally [input][]. The subsequent messages must contain [input][].
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
Iterable[google.cloud.aiplatform_v1beta1.types.StreamingPredictResponse] Response message for PredictionService.StreamingPredict.

streaming_raw_predict

streaming_raw_predict(
    requests: typing.Optional[
        typing.Iterator[
            google.cloud.aiplatform_v1beta1.types.prediction_service.StreamingRawPredictRequest
        ]
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> typing.Iterable[
    google.cloud.aiplatform_v1beta1.types.prediction_service.StreamingRawPredictResponse
]

Perform a streaming online prediction request through gRPC.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_streaming_raw_predict():
    # Create a client
    client = aiplatform_v1beta1.PredictionServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.StreamingRawPredictRequest(
        endpoint="endpoint_value",
    )

    # This method expects an iterator which contains
    # 'aiplatform_v1beta1.StreamingRawPredictRequest' objects
    # Here we create a generator that yields a single `request` for
    # demonstrative purposes.
    requests = [request]

    def request_generator():
        for request in requests:
            yield request

    # Make the request
    stream = client.streaming_raw_predict(requests=request_generator())

    # Handle the response
    for response in stream:
        print(response)
Parameters
Name Description
requests Iterator[google.cloud.aiplatform_v1beta1.types.StreamingRawPredictRequest]

The request object iterator. Request message for PredictionService.StreamingRawPredict. The first message must contain endpoint and method_name fields and optionally input. The subsequent messages must contain input. method_name in the subsequent messages have no effect.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
Iterable[google.cloud.aiplatform_v1beta1.types.StreamingRawPredictResponse] Response message for PredictionService.StreamingRawPredict.

test_iam_permissions

test_iam_permissions(
    request: typing.Optional[
        google.iam.v1.iam_policy_pb2.TestIamPermissionsRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.iam_policy_pb2.TestIamPermissionsResponse

Tests the specified IAM permissions against the IAM access control policy for a function.

If the function does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Parameters
Name Description
request .iam_policy_pb2.TestIamPermissionsRequest

The request object. Request message for TestIamPermissions method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.iam_policy_pb2.TestIamPermissionsResponse Response message for TestIamPermissions method.

wait_operation

wait_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.WaitOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation

Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state.

If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters
Name Description
request .operations_pb2.WaitOperationRequest

The request object. Request message for WaitOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.operations_pb2.Operation An Operation object.