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PredictionServiceAsyncClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.services.prediction_service.transports.base.PredictionServiceTransport, typing.Callable[[...], google.cloud.aiplatform_v1.services.prediction_service.transports.base.PredictionServiceTransport]]] = 'grpc_asyncio', client_options: typing.Optional[google.api_core.client_options.ClientOptions] = 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
PredictionServiceAsyncClient
PredictionServiceAsyncClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.services.prediction_service.transports.base.PredictionServiceTransport, typing.Callable[[...], google.cloud.aiplatform_v1.services.prediction_service.transports.base.PredictionServiceTransport]]] = 'grpc_asyncio', client_options: typing.Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
Instantiates the prediction service async 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 to use. 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 |
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 |
Exceptions | |
---|---|
Type | Description |
google.auth.exceptions.MutualTlsChannelError |
If mutual TLS transport creation failed for any reason. |
cancel_operation
cancel_operation(
request: typing.Optional[
google.longrunning.operations_pb2.CancelOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
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 |
The request object. Request message for |
retry |
google.api_core.retry_async.AsyncRetry
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.
delete_operation
delete_operation(
request: typing.Optional[
google.longrunning.operations_pb2.DeleteOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
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 |
The request object. Request message for |
retry |
google.api_core.retry_async.AsyncRetry
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_v1.types.prediction_service.DirectPredictRequest,
dict,
]
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
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_v1.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_v1
async def sample_direct_predict():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.DirectPredictRequest(
endpoint="endpoint_value",
)
# Make the request
response = await client.direct_predict(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.DirectPredictRequest, dict]]
The request object. Request message for PredictionService.DirectPredict. |
retry |
google.api_core.retry_async.AsyncRetry
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_v1.types.DirectPredictResponse |
Response message for PredictionService.DirectPredict. |
direct_raw_predict
direct_raw_predict(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.prediction_service.DirectRawPredictRequest,
dict,
]
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
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_v1.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_v1
async def sample_direct_raw_predict():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.DirectRawPredictRequest(
endpoint="endpoint_value",
)
# Make the request
response = await client.direct_raw_predict(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.DirectRawPredictRequest, dict]]
The request object. Request message for PredictionService.DirectRawPredict. |
retry |
google.api_core.retry_async.AsyncRetry
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_v1.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_v1.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_async.AsyncRetry,
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_v1.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_v1
async def sample_explain():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
instances = aiplatform_v1.Value()
instances.null_value = "NULL_VALUE"
request = aiplatform_v1.ExplainRequest(
endpoint="endpoint_value",
instances=instances,
)
# Make the request
response = await client.explain(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.ExplainRequest, dict]]
The request object. Request message for PredictionService.Explain. |
endpoint |
Required. The name of the Endpoint requested to serve the explanation. Format: |
instances |
:class:
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.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] instance_schema_uri. This corresponds to the |
parameters |
The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] parameters_schema_uri. This corresponds to the |
deployed_model_id |
If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
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_v1.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 |
PredictionServiceAsyncClient |
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 |
PredictionServiceAsyncClient |
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 |
PredictionServiceAsyncClient |
The constructed client. |
generate_content
generate_content(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.prediction_service.GenerateContentRequest,
dict,
]
] = None,
*,
model: typing.Optional[str] = None,
contents: typing.Optional[
typing.MutableSequence[google.cloud.aiplatform_v1.types.content.Content]
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
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_v1.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_v1
async def sample_generate_content():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
contents = aiplatform_v1.Content()
contents.parts.text = "text_value"
request = aiplatform_v1.GenerateContentRequest(
model="model_value",
contents=contents,
)
# Make the request
response = await client.generate_content(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.GenerateContentRequest, dict]]
The request object. Request message for [PredictionService.GenerateContent]. |
model |
Required. The name of the publisher model requested to serve the prediction. Format: |
contents |
:class:
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 |
retry |
google.api_core.retry_async.AsyncRetry
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_v1.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_async.AsyncRetry,
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 |
The request object. Request message for |
retry |
google.api_core.retry_async.AsyncRetry
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 |
|
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_async.AsyncRetry,
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 |
The request object. Request message for |
retry |
google.api_core.retry_async.AsyncRetry
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 object. |
get_mtls_endpoint_and_cert_source
get_mtls_endpoint_and_cert_source(
client_options: typing.Optional[
google.api_core.client_options.ClientOptions
] = None,
)
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 |
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_async.AsyncRetry,
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 |
The request object. Request message for |
retry |
google.api_core.retry_async.AsyncRetry
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 |
|
An Operation object. |
get_transport_class
get_transport_class() -> (
typing.Type[
google.cloud.aiplatform_v1.services.prediction_service.transports.base.PredictionServiceTransport
]
)
Returns an appropriate transport class.
Parameter | |
---|---|
Name | Description |
label |
typing.Optional[str]
The name of the desired transport. If none is provided, then the first transport in the registry is used. |
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_async.AsyncRetry,
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 |
The request object. Request message for |
retry |
google.api_core.retry_async.AsyncRetry
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 |
|
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_async.AsyncRetry,
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 |
The request object. Request message for |
retry |
google.api_core.retry_async.AsyncRetry
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 |
|
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.
predict
predict(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.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_async.AsyncRetry,
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_v1.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_v1
async def sample_predict():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
instances = aiplatform_v1.Value()
instances.null_value = "NULL_VALUE"
request = aiplatform_v1.PredictRequest(
endpoint="endpoint_value",
instances=instances,
)
# Make the request
response = await client.predict(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.PredictRequest, dict]]
The request object. Request message for PredictionService.Predict. |
endpoint |
Required. The name of the Endpoint requested to serve the prediction. Format: |
instances |
:class:
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.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] instance_schema_uri. This corresponds to the |
parameters |
The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] parameters_schema_uri. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
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_v1.types.PredictResponse |
Response message for PredictionService.Predict. |
raw_predict
raw_predict(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.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_async.AsyncRetry,
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_v1
async def sample_raw_predict():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.RawPredictRequest(
endpoint="endpoint_value",
)
# Make the request
response = await client.raw_predict(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.RawPredictRequest, dict]]
The request object. Request message for PredictionService.RawPredict. |
endpoint |
Required. The name of the Endpoint requested to serve the prediction. Format: |
http_body |
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 |
retry |
google.api_core.retry_async.AsyncRetry
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_v1.types.prediction_service.StreamingPredictRequest,
dict,
]
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
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.Awaitable[
typing.AsyncIterable[
google.cloud.aiplatform_v1.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_v1
async def sample_server_streaming_predict():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.StreamingPredictRequest(
endpoint="endpoint_value",
)
# Make the request
stream = await client.server_streaming_predict(request=request)
# Handle the response
async for response in stream:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.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_async.AsyncRetry
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 |
AsyncIterable[google.cloud.aiplatform_v1.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_async.AsyncRetry,
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 |
The request object. Request message for |
retry |
google.api_core.retry_async.AsyncRetry
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 |
|
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.AsyncIterator[
google.cloud.aiplatform_v1.types.prediction_service.StreamDirectPredictRequest
]
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
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.Awaitable[
typing.AsyncIterable[
google.cloud.aiplatform_v1.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_v1
async def sample_stream_direct_predict():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.StreamDirectPredictRequest(
endpoint="endpoint_value",
)
# This method expects an iterator which contains
# 'aiplatform_v1.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 = await client.stream_direct_predict(requests=request_generator())
# Handle the response
async for response in stream:
print(response)
Parameters | |
---|---|
Name | Description |
requests |
AsyncIterator[
The request object AsyncIterator. 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_async.AsyncRetry
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 |
AsyncIterable[google.cloud.aiplatform_v1.types.StreamDirectPredictResponse] |
Response message for PredictionService.StreamDirectPredict. |
stream_direct_raw_predict
stream_direct_raw_predict(
requests: typing.Optional[
typing.AsyncIterator[
google.cloud.aiplatform_v1.types.prediction_service.StreamDirectRawPredictRequest
]
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
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.Awaitable[
typing.AsyncIterable[
google.cloud.aiplatform_v1.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_v1
async def sample_stream_direct_raw_predict():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.StreamDirectRawPredictRequest(
endpoint="endpoint_value",
)
# This method expects an iterator which contains
# 'aiplatform_v1.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 = await client.stream_direct_raw_predict(requests=request_generator())
# Handle the response
async for response in stream:
print(response)
Parameters | |
---|---|
Name | Description |
requests |
AsyncIterator[
The request object AsyncIterator. 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_async.AsyncRetry
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 |
AsyncIterable[google.cloud.aiplatform_v1.types.StreamDirectRawPredictResponse] |
Response message for PredictionService.StreamDirectRawPredict. |
stream_generate_content
stream_generate_content(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.prediction_service.GenerateContentRequest,
dict,
]
] = None,
*,
model: typing.Optional[str] = None,
contents: typing.Optional[
typing.MutableSequence[google.cloud.aiplatform_v1.types.content.Content]
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
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.Awaitable[
typing.AsyncIterable[
google.cloud.aiplatform_v1.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_v1
async def sample_stream_generate_content():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
contents = aiplatform_v1.Content()
contents.parts.text = "text_value"
request = aiplatform_v1.GenerateContentRequest(
model="model_value",
contents=contents,
)
# Make the request
stream = await client.stream_generate_content(request=request)
# Handle the response
async for response in stream:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.GenerateContentRequest, dict]]
The request object. Request message for [PredictionService.GenerateContent]. |
model |
Required. The name of the publisher model requested to serve the prediction. Format: |
contents |
:class:
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 |
retry |
google.api_core.retry_async.AsyncRetry
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 |
AsyncIterable[google.cloud.aiplatform_v1.types.GenerateContentResponse] |
Response message for [PredictionService.GenerateContent]. |
stream_raw_predict
stream_raw_predict(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.prediction_service.StreamRawPredictRequest,
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_async.AsyncRetry,
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.Awaitable[typing.AsyncIterable[google.api.httpbody_pb2.HttpBody]]
Perform a streaming online prediction with an arbitrary HTTP payload.
# 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_v1
async def sample_stream_raw_predict():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.StreamRawPredictRequest(
endpoint="endpoint_value",
)
# Make the request
stream = await client.stream_raw_predict(request=request)
# Handle the response
async for response in stream:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.StreamRawPredictRequest, dict]]
The request object. Request message for PredictionService.StreamRawPredict. |
endpoint |
Required. The name of the Endpoint requested to serve the prediction. Format: |
http_body |
The prediction input. Supports HTTP headers and arbitrary data payload. This corresponds to the |
retry |
google.api_core.retry_async.AsyncRetry
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 |
AsyncIterable[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. |
streaming_predict
streaming_predict(
requests: typing.Optional[
typing.AsyncIterator[
google.cloud.aiplatform_v1.types.prediction_service.StreamingPredictRequest
]
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
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.Awaitable[
typing.AsyncIterable[
google.cloud.aiplatform_v1.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_v1
async def sample_streaming_predict():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.StreamingPredictRequest(
endpoint="endpoint_value",
)
# This method expects an iterator which contains
# 'aiplatform_v1.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 = await client.streaming_predict(requests=request_generator())
# Handle the response
async for response in stream:
print(response)
Parameters | |
---|---|
Name | Description |
requests |
AsyncIterator[
The request object AsyncIterator. 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_async.AsyncRetry
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 |
AsyncIterable[google.cloud.aiplatform_v1.types.StreamingPredictResponse] |
Response message for PredictionService.StreamingPredict. |
streaming_raw_predict
streaming_raw_predict(
requests: typing.Optional[
typing.AsyncIterator[
google.cloud.aiplatform_v1.types.prediction_service.StreamingRawPredictRequest
]
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
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.Awaitable[
typing.AsyncIterable[
google.cloud.aiplatform_v1.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_v1
async def sample_streaming_raw_predict():
# Create a client
client = aiplatform_v1.PredictionServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.StreamingRawPredictRequest(
endpoint="endpoint_value",
)
# This method expects an iterator which contains
# 'aiplatform_v1.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 = await client.streaming_raw_predict(requests=request_generator())
# Handle the response
async for response in stream:
print(response)
Parameters | |
---|---|
Name | Description |
requests |
AsyncIterator[
The request object AsyncIterator. 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_async.AsyncRetry
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 |
AsyncIterable[google.cloud.aiplatform_v1.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_async.AsyncRetry,
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 |
The request object. Request message for |
retry |
google.api_core.retry_async.AsyncRetry
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 |
|
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_async.AsyncRetry,
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 |
The request object. Request message for |
retry |
google.api_core.retry_async.AsyncRetry
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 |
|
An Operation object. |